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"content": "\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n\n\n\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n\n\n\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n\n\n\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n\n\n\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n\n\n\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n\n\n\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n\n\n\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">\u003cstrong>Making students slow down\u003c/strong>\u003c/h2>\n\n\n\n\u003cp>The researchers think AI helped because it walked students through their mistakes instead of simply showing them a solution.\u003c/p>\n\n\n\n\u003cp>Without AI, students could see a step-by-step example after getting a problem wrong. But a student can easily skim through the steps to a solution and move on, without figuring out what went wrong.\u003c/p>\n\n\n\n\u003ch4 class=\"wp-block-heading\">\u003cstrong>Numi, an AI tutor, guides students step by step\u003c/strong>\u003c/h4>\n\n\n\n\u003cfigure class=\"wp-block-image size-full\">\u003cimg loading=\"lazy\" decoding=\"async\" width=\"346\" height=\"810\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png\" alt=\"\" class=\"wp-image-66544\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png 346w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image-160x375.png 160w\" sizes=\"auto, (max-width: 346px) 100vw, 346px\">\u003c/figure>\n\n\n\n\u003cp>Right after a mistake, an AI tutor called “Numi” walks a student through a solution step-by-step for dividing two numbers: 3 \u003csup>6\u003c/sup>/\u003csub>7\u003c/sub> ÷ 4 \u003csup>5\u003c/sup>/\u003csub>2\u003c/sub>.\u003c/p>\n\n\n\n\u003cp 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Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n\n\n\n\u003cp>The AI tutor, by contrast, could respond directly to a student’s work and guide the student through the mistake.\u003c/p>\n\n\n\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n\n\n\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n\n\n\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n\n\n\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n\n\n\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n\n\n\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n\n\n\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n\n\n\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n\n\n\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"innerHTML": "\n\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n",
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"innerHTML": "\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n",
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"\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n",
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"\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n",
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"\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n"
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"innerHTML": "\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n",
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"\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n"
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"innerHTML": "\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n",
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"\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n",
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"\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n"
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"innerHTML": "\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n",
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"\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n"
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\">Here Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n",
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Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n"
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"innerHTML": "\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n",
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"\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n"
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"innerHTML": "\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n",
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"\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n"
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"innerHTML": "\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n",
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"\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n"
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"innerHTML": "\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n",
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"\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n"
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"innerHTML": "\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n",
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"\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n"
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"innerHTML": "\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n",
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"innerHTML": "\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n",
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"\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n"
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"excerpt": "A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n\n\n\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n\n\n\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n\n\n\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n\n\n\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n\n\n\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n\n\n\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n\n\n\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">\u003cstrong>Making students slow down\u003c/strong>\u003c/h2>\n\n\n\n\u003cp>The researchers think AI helped because it walked students through their mistakes instead of simply showing them a solution.\u003c/p>\n\n\n\n\u003cp>Without AI, students could see a step-by-step example after getting a problem wrong. But a student can easily skim through the steps to a solution and move on, without figuring out what went wrong.\u003c/p>\n\n\n\n\u003ch4 class=\"wp-block-heading\">\u003cstrong>Numi, an AI tutor, guides students step by step\u003c/strong>\u003c/h4>\n\n\n\n\u003cfigure class=\"wp-block-image size-full\">\u003cimg loading=\"lazy\" decoding=\"async\" width=\"346\" height=\"810\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png\" alt=\"\" class=\"wp-image-66544\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png 346w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image-160x375.png 160w\" sizes=\"auto, (max-width: 346px) 100vw, 346px\">\u003c/figure>\n\n\n\n\u003cp>Right after a mistake, an AI tutor called “Numi” walks a student through a solution step-by-step for dividing two numbers: 3 \u003csup>6\u003c/sup>/\u003csub>7\u003c/sub> ÷ 4 \u003csup>5\u003c/sup>/\u003csub>2\u003c/sub>.\u003c/p>\n\n\n\n\u003cp 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\">Here Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n\n\n\n\u003cp>The AI tutor, by contrast, could respond directly to a student’s work and guide the student through the mistake.\u003c/p>\n\n\n\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n\n\n\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n\n\n\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n\n\n\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n\n\n\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n\n\n\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n\n\n\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n\n\n\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n\n\n\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"title": "Who Misses Out When Tutoring Starts Too Late?",
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"content": "\u003cp>\u003ca href=\"#episode-transcript\">\u003ci>View the full episode transcript.\u003c/i>\u003c/a>\u003c/p>\n\u003cp>For 30 years, Bellevue Elementary in Santa Rosa has relied on AmeriCorps services to support their students that need extra help. But when federal funding was cut, and later reinstated, that programming stalled, leaving some students behind.\u003c/p>\n\u003cp>In this episode, principal Nina Craig explains how the loss of tutors affected instruction and student relationships, while new AmeriCorps members, Maya Nurse and Elena Zeoli, describe stepping into classrooms with limited time and resources. We learn how even a few missed months of literacy support reduces how many students can be served.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe loading=\"lazy\" frameborder=\"0\" height=\"200\" scrolling=\"no\" src=\"https://playlist.megaphone.fm?e=KQINC1557384124\" width=\"100%\" class=\"iframe-class\">\u003c/iframe>\u003c/p>\n\u003ch2 id=\"episode-transcript\">Episode Transcript\u003c/h2>\n\u003cp>\u003cstrong>Marlena Jackson-Retondo: \u003c/strong>Welcome to Mind Shift, where we explore the future of learning and how we raise our kids. I’m Marlena Jackson Rotondo. It’s almost Winter break at Bellevue Elementary in Santa Rosa, California, and tutoring sessions for the school year have just begun. The schools to AmeriCorps tutors have gone through a crash course of training to prepare for the reading and writing support they’ll provide for the rest of the year.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>AmeriCorps is an independent government agency whose volunteer members provide educational support and services to schools across the country.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>On this morning, a small group of fourth graders reluctantly file into the room.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>They’ve been pulled out of their classroom to spend 30 minutes with the tutors, Maya Nurse and Elena Zeoli.\u003c/p>\n\u003cp>Maya has the students get straight to work reading a story out loud from a workbook In unison.\u003c/p>\n\u003cp>\u003cstrong>Mya Nurse:\u003c/strong> We’re gonna start with our choral style of reading today.\u003c/p>\n\u003cp>\u003cstrong>Mya Nurse:\u003c/strong> Ready? Go!\u003c/p>\n\u003cp>\u003cstrong>All reading:\u003c/strong> My mother says to me, I choose a pretty paper fan with a picture of leaves and fireflies. I will keep my fan forever. When I grow up I will look at it and remember this night.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The tutors stop the students every couple of sentences to ask about vocabulary in the text.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> So what happened?\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> What unexpectedly happened? The wet… they were warned about the weather. They thought the waves were only gonna get to how tall? Do you remember from the first page? Student: mmmm….\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The students seem timid, and when they do speak up, it’s very quiet. And sometimes the students don’t answer the questions at all, but Maya and Elena, unfazed by the silence, move on.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> This is normal student behavior for the first week of tutoring at Bellevue Elementary, but what isn’t normal is that the first week of tutoring has been delayed this year by more than two months. Tutoring was supposed to start in early fall. Last April, all AmeriCorps funding was terminated by the Trump administration.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong> This ended an almost three decade long collaboration between Bellevue Elementary and AmeriCorps.\u003c/p>\n\u003cp>These cuts happened immediately and without explanation.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> It was shocking how quickly it happened. Um, uh, literally felt like overnight.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> so it kind of felt like the rug was pulled out from us.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> That’s Nina Craig Bellevue, elementary’s principal of 10 years. Before that, she was a fifth grade teacher and she recalls working with AmeriCorps members then.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> As a classroom teacher I remember them coming into my room and working with some of my students and having that partnership as a teacher\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And because the AmeriCorps members were such an integral part of the school community, the cuts were difficult for Bellevue students too.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> The relationship with the kids that was established and for the kids to all of a sudden have these people gone that are such a vital part of our school.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> was really sad and really hard to explain, because they really do become a part of our school culture.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong> Through lawsuits. AmeriCorps funding cuts were reversed in June of last year, but by that time, schools like Bellevue Elementary were already behind for the next school year’s cycle of tutoring. Some schools across the district opted not to continue with tutoring and mentoring support from AmeriCorps members for the next school year.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> This is because they had to make decisions about their funding and without the certainty of AmeriCorps services, they had to go without. And because programming was delayed, Bellevue students didn’t start tutoring until December instead of October.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> there hasn’t been any tutoring offered for our third through sixth grade students until now.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> So without AmeriCorps, those students aren’t receiving any type of tutoring or intervention. And unless the teacher’s able to carve out time within their day to provide that,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> AmeriCorps members provide one of Bellevue elementary’s only forms of tier two support. That’s targeted support in a small group setting. In this case, it helps students who are struggling with reading.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> In years past, we’ve had literacy paraprofessionals that could support our tier two. Um, however, with budget cuts, this is our first year without having them.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> And so, um, we have one instructional aide. For the entire school\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> But yeah, we’re very limited.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The two AmeriCorps tutors contribute greatly to Bellevue’s tier two manpower, but it’s still not enough. The school reduced the kindergarten day by one and a half hours so that kindergarten teachers could provide extra support for Bellevue’s first and second grade classrooms. On short notice, and with no wiggle room in their budget.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Bellevue Elementary had to make some hard choices. We’ll find out how they’re doing right after this break.\u003c/p>\n\u003cp>***Midroll Break***\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>When I visited Bellevue Elementary back in December, I spoke with Fonzi, a fourth grader, receiving small group literacy tutoring for 30 minutes per day, four days per week.\u003c/p>\n\u003cp>\u003cstrong> Fonzi: \u003c/strong>Dog Man and then I Survived.\u003c/p>\n\u003cp>Fonzi’s telling me about the books he likes to read at home.,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> What was that one?\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> I Survived.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> What’s that one about?\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> It’s um, there’s like different books.\u003c/p>\n\u003cp>\u003cstrong> Fonzi:\u003c/strong> There’s, um, a Titanic book that, um, sunk in the ocean.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> So you read about different survival stories? Whoa, that’s pretty cool.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> He feels like there’s less reading time when he’s in his classroom.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> The things that are different is, um, we don’t like read a lot of books,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> But when he’s in his tutoring sessions, reading time, one of his favorite things to do, is extended\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> At AR time, we um, read, we read books for 15 minutes.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Fonzi is part of a small group of fourth grade students who have been identified as needing extra support with reading. During a normal year, there’s enough time for two groups of students to cycle through tutoring support from AmeriCorps members. But this year, since tutoring at Bellevue started late, AmeriCorps members only have time to help half of the students that they normally would.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> At sites like Bellevue, the AmeriCorps tutors have become a staple in the school community.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> There’s so many ways AmeriCorps impacts because of the tutoring, the recess playtime, the mentoring. It’s so much connection. You guys probably know more of the kids’ names than I do, um, at this point. And you just started\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And for Maya and Elena who are just starting their careers, the program offers them a glimpse into their professional future\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I know I want to do a job where I’m helping people and so I thought this was a great opportunity to, yeah, like, get some real life experience where I’m like serving others and I’m thinking of maybe doing something with social work.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> The opportunity to work with students in a school setting also offered Maya something new.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I’ve never worked with kids, and so I was kind of like, I feel like I don’t know what I’m doing. Like, I don’t know if I..\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> …If I can do this, at first, you know, I was a little timid, but then you kind of just jump in and, um, you start connecting with the kids.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>When I spoke with the tutoring pair back in December, Elena was already feeling optimistic about her future.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> So far this job I feel extremely passionate about, which is, it’s just really nice waking up in the morning and I, I wake up early, like I wake up before my alarm clock ’cause I’m just excited to come to the school.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> A couple months later, Maya and Elena felt comfortable in their roles,\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I just like know what I’m doing a little more. I kinda have a sense of like, we have a daily routine. I have really like good relationships with students now, so I’m like so excited to see them every day and they’re excited to see me and yeah, it’s great. It’s really good.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And the AmeriCorps tutors have also noticed improvements in their students as well.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> One of my students in sixth grade, in one of his tests, he was and like the 26th percentile for reading in like November. And now he is like in the 42nd percentile and I’m like, whoa, that’s so like rewarding and exciting that he’s like doing so much better and able to do that on his own now, like do it more on his own.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> But the reality of having to work within the school’s limited resources has also sunk in for Maya.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> Sometimes also it’s like really hard to see like how some students struggle so much in school or like, you know, and I can only do so much and help them so much in that 30 minutes.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> yeah, just doing the best you can every day with what you have.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> Cat was going to wait the cat, and then this could change to hundreds of bugs in one.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> He called his keys and…\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>I walked into the tutoring classroom in February.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> It felt like a transformed space with students who were relaxed and eager to learn.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Elena had also noticed a difference in her students too.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> I feel like they’re a lot more confident in answering questions and what to write down. So I feel like that’s. That’s like the biggest difference I’ve seen is like their confidence in what they’re writing.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> So the door, what’s the door? Who does he know? What’s the door? It’s D, the OOR. Yeah. I thought it was E-D-O-O-O-R-H. What? All right.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Fonzi has also gained confidence in his reading abilities since December. He told me he’s reading three to four books a day and even tackling some chapter books.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> When I first came in and reading groups, um, we started reading books and stuff and I kind of got into it and I started reading books every day.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> The benefits of extra reading support provided by the AmeriCorps tutors at school has extended into Fonzie’s home life as well. He and his siblings made up a reading game that they like to play at home.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> We guess, like, the book that they have. They don’t show the covers. And we, guess, and then if we get it right, the people that have the book that the people say, they’re eliminated.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Even though there won’t be enough time to bring in another group of fourth graders for tutoring this school year, Elena and Maya look forward to the rest of their time with the students that they are able to help.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Thank you to Bellevue Elementary’s faculty and staff who contributed their time to make this episode possible.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The MindShift team includes me, Marlena Jackson-Retondo, Nimah Gobir, and Ki Sung. Our editor is Chris Hambrick. Seth Samuel is our sound designer. Jen Chien is head of podcasts and Ethan Toven-Lindsey is KQED’s, editor-in-chief. We receive additional support from Maha Sanad.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Mindshift is supported in part by the generosity of the William and Flora Hewlett Foundation and members of KQED, some members of the KQED podcast team are represented by the Screen Actors Guild, American Federation of Television and Radio artists. San Francisco, Northern California Local.\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Thanks for listening.\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003ca href=\"#episode-transcript\">\u003ci>View the full episode transcript.\u003c/i>\u003c/a>\u003c/p>\n\u003cp>For 30 years, Bellevue Elementary in Santa Rosa has relied on AmeriCorps services to support their students that need extra help. But when federal funding was cut, and later reinstated, that programming stalled, leaving some students behind.\u003c/p>\n\u003cp>In this episode, principal Nina Craig explains how the loss of tutors affected instruction and student relationships, while new AmeriCorps members, Maya Nurse and Elena Zeoli, describe stepping into classrooms with limited time and resources. We learn how even a few missed months of literacy support reduces how many students can be served.\u003c/p>\n\u003cp>\u003c!-- iframe plugin v.4.3 wordpress.org/plugins/iframe/ -->\u003cbr>\n\u003ciframe loading=\"lazy\" frameborder=\"0\" height=\"200\" scrolling=\"no\" src=\"https://playlist.megaphone.fm?e=KQINC1557384124\" width=\"100%\" class=\"iframe-class\">\u003c/iframe>\u003c/div>",
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"content": "\u003cdiv class=\"post-content post-body\">\u003ch2 id=\"episode-transcript\">Episode Transcript\u003c/h2>\n\u003cp>\u003cstrong>Marlena Jackson-Retondo: \u003c/strong>Welcome to Mind Shift, where we explore the future of learning and how we raise our kids. I’m Marlena Jackson Rotondo. It’s almost Winter break at Bellevue Elementary in Santa Rosa, California, and tutoring sessions for the school year have just begun. The schools to AmeriCorps tutors have gone through a crash course of training to prepare for the reading and writing support they’ll provide for the rest of the year.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>AmeriCorps is an independent government agency whose volunteer members provide educational support and services to schools across the country.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>On this morning, a small group of fourth graders reluctantly file into the room.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>They’ve been pulled out of their classroom to spend 30 minutes with the tutors, Maya Nurse and Elena Zeoli.\u003c/p>\n\u003cp>Maya has the students get straight to work reading a story out loud from a workbook In unison.\u003c/p>\n\u003cp>\u003cstrong>Mya Nurse:\u003c/strong> We’re gonna start with our choral style of reading today.\u003c/p>\n\u003cp>\u003cstrong>Mya Nurse:\u003c/strong> Ready? Go!\u003c/p>\n\u003cp>\u003cstrong>All reading:\u003c/strong> My mother says to me, I choose a pretty paper fan with a picture of leaves and fireflies. I will keep my fan forever. When I grow up I will look at it and remember this night.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The tutors stop the students every couple of sentences to ask about vocabulary in the text.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> So what happened?\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> What unexpectedly happened? The wet… they were warned about the weather. They thought the waves were only gonna get to how tall? Do you remember from the first page? Student: mmmm….\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The students seem timid, and when they do speak up, it’s very quiet. And sometimes the students don’t answer the questions at all, but Maya and Elena, unfazed by the silence, move on.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> This is normal student behavior for the first week of tutoring at Bellevue Elementary, but what isn’t normal is that the first week of tutoring has been delayed this year by more than two months. Tutoring was supposed to start in early fall. Last April, all AmeriCorps funding was terminated by the Trump administration.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong> This ended an almost three decade long collaboration between Bellevue Elementary and AmeriCorps.\u003c/p>\n\u003cp>These cuts happened immediately and without explanation.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> It was shocking how quickly it happened. Um, uh, literally felt like overnight.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> so it kind of felt like the rug was pulled out from us.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> That’s Nina Craig Bellevue, elementary’s principal of 10 years. Before that, she was a fifth grade teacher and she recalls working with AmeriCorps members then.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> As a classroom teacher I remember them coming into my room and working with some of my students and having that partnership as a teacher\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And because the AmeriCorps members were such an integral part of the school community, the cuts were difficult for Bellevue students too.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> The relationship with the kids that was established and for the kids to all of a sudden have these people gone that are such a vital part of our school.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> was really sad and really hard to explain, because they really do become a part of our school culture.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong> Through lawsuits. AmeriCorps funding cuts were reversed in June of last year, but by that time, schools like Bellevue Elementary were already behind for the next school year’s cycle of tutoring. Some schools across the district opted not to continue with tutoring and mentoring support from AmeriCorps members for the next school year.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> This is because they had to make decisions about their funding and without the certainty of AmeriCorps services, they had to go without. And because programming was delayed, Bellevue students didn’t start tutoring until December instead of October.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> there hasn’t been any tutoring offered for our third through sixth grade students until now.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> So without AmeriCorps, those students aren’t receiving any type of tutoring or intervention. And unless the teacher’s able to carve out time within their day to provide that,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> AmeriCorps members provide one of Bellevue elementary’s only forms of tier two support. That’s targeted support in a small group setting. In this case, it helps students who are struggling with reading.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> In years past, we’ve had literacy paraprofessionals that could support our tier two. Um, however, with budget cuts, this is our first year without having them.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> And so, um, we have one instructional aide. For the entire school\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> But yeah, we’re very limited.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The two AmeriCorps tutors contribute greatly to Bellevue’s tier two manpower, but it’s still not enough. The school reduced the kindergarten day by one and a half hours so that kindergarten teachers could provide extra support for Bellevue’s first and second grade classrooms. On short notice, and with no wiggle room in their budget.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Bellevue Elementary had to make some hard choices. We’ll find out how they’re doing right after this break.\u003c/p>\n\u003cp>***Midroll Break***\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>When I visited Bellevue Elementary back in December, I spoke with Fonzi, a fourth grader, receiving small group literacy tutoring for 30 minutes per day, four days per week.\u003c/p>\n\u003cp>\u003cstrong> Fonzi: \u003c/strong>Dog Man and then I Survived.\u003c/p>\n\u003cp>Fonzi’s telling me about the books he likes to read at home.,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> What was that one?\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> I Survived.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> What’s that one about?\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> It’s um, there’s like different books.\u003c/p>\n\u003cp>\u003cstrong> Fonzi:\u003c/strong> There’s, um, a Titanic book that, um, sunk in the ocean.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> So you read about different survival stories? Whoa, that’s pretty cool.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> He feels like there’s less reading time when he’s in his classroom.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> The things that are different is, um, we don’t like read a lot of books,\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> But when he’s in his tutoring sessions, reading time, one of his favorite things to do, is extended\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> At AR time, we um, read, we read books for 15 minutes.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Fonzi is part of a small group of fourth grade students who have been identified as needing extra support with reading. During a normal year, there’s enough time for two groups of students to cycle through tutoring support from AmeriCorps members. But this year, since tutoring at Bellevue started late, AmeriCorps members only have time to help half of the students that they normally would.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> At sites like Bellevue, the AmeriCorps tutors have become a staple in the school community.\u003c/p>\n\u003cp>\u003cstrong>Nina Craig:\u003c/strong> There’s so many ways AmeriCorps impacts because of the tutoring, the recess playtime, the mentoring. It’s so much connection. You guys probably know more of the kids’ names than I do, um, at this point. And you just started\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And for Maya and Elena who are just starting their careers, the program offers them a glimpse into their professional future\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I know I want to do a job where I’m helping people and so I thought this was a great opportunity to, yeah, like, get some real life experience where I’m like serving others and I’m thinking of maybe doing something with social work.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> The opportunity to work with students in a school setting also offered Maya something new.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I’ve never worked with kids, and so I was kind of like, I feel like I don’t know what I’m doing. Like, I don’t know if I..\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> …If I can do this, at first, you know, I was a little timid, but then you kind of just jump in and, um, you start connecting with the kids.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>When I spoke with the tutoring pair back in December, Elena was already feeling optimistic about her future.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> So far this job I feel extremely passionate about, which is, it’s just really nice waking up in the morning and I, I wake up early, like I wake up before my alarm clock ’cause I’m just excited to come to the school.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> A couple months later, Maya and Elena felt comfortable in their roles,\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> I just like know what I’m doing a little more. I kinda have a sense of like, we have a daily routine. I have really like good relationships with students now, so I’m like so excited to see them every day and they’re excited to see me and yeah, it’s great. It’s really good.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> And the AmeriCorps tutors have also noticed improvements in their students as well.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> One of my students in sixth grade, in one of his tests, he was and like the 26th percentile for reading in like November. And now he is like in the 42nd percentile and I’m like, whoa, that’s so like rewarding and exciting that he’s like doing so much better and able to do that on his own now, like do it more on his own.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> But the reality of having to work within the school’s limited resources has also sunk in for Maya.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> Sometimes also it’s like really hard to see like how some students struggle so much in school or like, you know, and I can only do so much and help them so much in that 30 minutes.\u003c/p>\n\u003cp>\u003cstrong>Maya Nurse:\u003c/strong> yeah, just doing the best you can every day with what you have.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> Cat was going to wait the cat, and then this could change to hundreds of bugs in one.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> He called his keys and…\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>I walked into the tutoring classroom in February.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> It felt like a transformed space with students who were relaxed and eager to learn.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Elena had also noticed a difference in her students too.\u003c/p>\n\u003cp>\u003cstrong>Elena Zeoli:\u003c/strong> I feel like they’re a lot more confident in answering questions and what to write down. So I feel like that’s. That’s like the biggest difference I’ve seen is like their confidence in what they’re writing.\u003c/p>\n\u003cp>\u003cstrong>ambi:\u003c/strong> So the door, what’s the door? Who does he know? What’s the door? It’s D, the OOR. Yeah. I thought it was E-D-O-O-O-R-H. What? All right.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Fonzi has also gained confidence in his reading abilities since December. He told me he’s reading three to four books a day and even tackling some chapter books.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> When I first came in and reading groups, um, we started reading books and stuff and I kind of got into it and I started reading books every day.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> The benefits of extra reading support provided by the AmeriCorps tutors at school has extended into Fonzie’s home life as well. He and his siblings made up a reading game that they like to play at home.\u003c/p>\n\u003cp>\u003cstrong>Fonzi:\u003c/strong> We guess, like, the book that they have. They don’t show the covers. And we, guess, and then if we get it right, the people that have the book that the people say, they’re eliminated.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Even though there won’t be enough time to bring in another group of fourth graders for tutoring this school year, Elena and Maya look forward to the rest of their time with the students that they are able to help.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo:\u003c/strong> Thank you to Bellevue Elementary’s faculty and staff who contributed their time to make this episode possible.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>The MindShift team includes me, Marlena Jackson-Retondo, Nimah Gobir, and Ki Sung. Our editor is Chris Hambrick. Seth Samuel is our sound designer. Jen Chien is head of podcasts and Ethan Toven-Lindsey is KQED’s, editor-in-chief. We receive additional support from Maha Sanad.\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Mindshift is supported in part by the generosity of the William and Flora Hewlett Foundation and members of KQED, some members of the KQED podcast team are represented by the Screen Actors Guild, American Federation of Television and Radio artists. San Francisco, Northern California Local.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cstrong>Jackson-Retondo: \u003c/strong>Thanks for listening.\u003c/p>\n\n\u003c/div>"
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"content": "\u003cp>It’s easy to get swept up in the hype about artificial intelligence tutors. But the evidence so far suggests caution.\u003c/p>\n\u003cp>Some studies have found that chatbot tutors can \u003ca href=\"https://www.pnas.org/doi/10.1073/pnas.2422633122\">backfire\u003c/a> because students \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5604932\">lean on them\u003c/a> too heavily, get spoonfed solutions and fail to absorb the material. Even when AI tutors are designed not to give away answers, they haven’t consistently produced better results than learning the old-fashioned way without AI.\u003c/p>\n\u003cp>Still, researchers who have produced these skeptical studies haven’t given up hope. Some are still experimenting, trying to build better AI tutors.\u003c/p>\n\u003cp>One promising idea has less to do with how an AI tutor explains concepts and more with what it asks students to practice next.\u003c/p>\n\u003cp>A team at the University of Pennsylvania, which included some AI skeptics, recently tested this approach in a \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358\">study\u003c/a> of close to 800 Taiwanese high school students learning Python programming. All the students used the same AI tutor, which was designed not to give away answers.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>But there was one key difference. Half the students were randomly assigned to a fixed sequence of practice problems, progressing from easy to hard. The other half received a personalized sequence with the AI tutor continuously adjusting the difficulty of each problem based on how the student was performing and interacting with the chatbot.\u003c/p>\n\u003cp>The idea is based on what educators call the “zone of proximal development.” When problems are too easy, students get bored. When they’re too hard, students get frustrated. The goal is to keep students in a sweet spot: challenged, but not overwhelmed.\u003c/p>\n\u003cp>The researchers found that students in the personalized group did better on a final exam than students in the fixed problem group. The difference was characterized as the equivalent of 6 to 9 months of additional schooling, an eye-catching claim for an after-school online course that lasted only five months. The AI tutor’s inventor, Angel Chung, a doctoral student at the Wharton School, acknowledged that her conversion of statistical units was “not a perfect estimate.” (A \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358\">draft paper\u003c/a> about the experiment was posted online in March 2026, but has not yet been published in a peer-reviewed journal.)\u003c/p>\n\u003cp>Still, this is early evidence that small tweaks — in this case, calibrating the difficulty of the practice problems to the student — can make a difference.\u003c/p>\n\u003cp>Chung said that ChatGPT’s responses may already feel very personal because they are directly responding to a student’s unique questions. But that level of personalization isn’t enough. “Students usually don’t know what they don’t know,” said Chung. “The student doesn’t have the ability to ask the right questions to get the best tutoring.”\u003c/p>\n\u003cp>To address this, Chung’s team combined a large language model with a separate machine-learning algorithm that analyzes how students interact with the online course platform — how they answer the practice questions, how many times they revise or edit their coding, and the quality of their conversations with the chatbot — and uses that information to decide which problem to serve up next.\u003c/p>\n\u003ch2>\u003cstrong>How different students interact with the chatbot tutor\u003c/strong>\u003c/h2>\n\u003cfigure id=\"attachment_66238\" class=\"wp-caption alignnone\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-66238\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1.png\" alt=\"List of chatbot prompts\" width=\"780\" height=\"418\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1-160x86.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1-768x412.png 768w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Source: Chung et al, Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning, March 2026\u003c/figcaption>\u003c/figure>\n\u003cp>In other words, personalization isn’t just about tailoring explanations. It’s about tailoring the learning path itself.\u003c/p>\n\u003cp>That idea isn’t new.\u003c/p>\n\u003cp>Long before generative AI tools like ChatGPT were invented, education researchers developed “intelligent tutoring systems” that tried to do something similar: estimate what a student knew and deliver the right next problem. These earlier systems couldn’t produce natural conversations, but they could provide hints and instant feedback. Rigorous studies found that well-designed versions helped students learn significantly more.\u003c/p>\n\u003cp>Their Achilles’ heel was engagement. Many students simply didn’t want to use them.\u003c/p>\n\u003cp>Today’s AI tools could help address that problem. Students might feel more interested in a chatbot that converses with them in an almost human way.\u003c/p>\n\u003cp>In the University of Pennsylvania study, students in the personalized group spent more time practicing, about three additional minutes per problem, adding up to about an hour per module in the Python course, compared with half as much time (a half hour or less) for the comparison students. The researchers think these students did better because they were more engaged in their practice work.\u003c/p>\n\u003cp>Students’ previous knowledge of a subject affected how well the personalized sequencing worked. Students who were new to Python gained more than those who already had Python experience, who did just as well with the fixed sequence of practice problems. Students from less elite high schools also appeared to benefit more.\u003c/p>\n\u003ch2>\u003cstrong>How students’ background affected results\u003c/strong>\u003c/h2>\n\u003cfigure id=\"attachment_66239\" class=\"wp-caption alignnone\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-66239\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2.png\" alt=\"Chart showing skill vs. prior experience\" width=\"780\" height=\"500\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2-160x103.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2-768x492.png 768w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">All students had access to the same AI tutor. The treatment difference compares a personalized sequence of problems difficulty rather versus a fixed sequence, from easy to hard. Source: Chung et al, Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning, March 2026\u003c/figcaption>\u003c/figure>\n\u003cp>All the Taiwanese students in this study volunteered for an optional computer programming course that could strengthen their college applications. Many were highly motivated, with highly educated parents, and many already had prior coding experience.\u003c/p>\n\u003cp>It’s not clear whether the chatbot would work as well with less motivated students who are behind at school and most in need of extra help.\u003c/p>\n\u003cp>One possible solution: fusing new and old.\u003c/p>\n\u003cp>Ken Koedinger, a professor at Carnegie Mellon University and a pioneer of intelligent tutoring systems, is experimenting with using \u003ca href=\"https://dl.acm.org/doi/abs/10.1145/3698205.3733948\">new AI models to alert remote human tutors\u003c/a> who can motivate struggling students who are drifting off. “We are having more success,” said Koedinger.\u003c/p>\n\u003cp>Humans aren’t obsolete — yet.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-python/\">\u003cem>AI tutors\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>It’s easy to get swept up in the hype about artificial intelligence tutors. But the evidence so far suggests caution.\u003c/p>\n\u003cp>Some studies have found that chatbot tutors can \u003ca href=\"https://www.pnas.org/doi/10.1073/pnas.2422633122\">backfire\u003c/a> because students \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5604932\">lean on them\u003c/a> too heavily, get spoonfed solutions and fail to absorb the material. Even when AI tutors are designed not to give away answers, they haven’t consistently produced better results than learning the old-fashioned way without AI.\u003c/p>\n\u003cp>Still, researchers who have produced these skeptical studies haven’t given up hope. Some are still experimenting, trying to build better AI tutors.\u003c/p>\n\u003cp>One promising idea has less to do with how an AI tutor explains concepts and more with what it asks students to practice next.\u003c/p>\n\u003cp>A team at the University of Pennsylvania, which included some AI skeptics, recently tested this approach in a \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358\">study\u003c/a> of close to 800 Taiwanese high school students learning Python programming. All the students used the same AI tutor, which was designed not to give away answers.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>But there was one key difference. Half the students were randomly assigned to a fixed sequence of practice problems, progressing from easy to hard. The other half received a personalized sequence with the AI tutor continuously adjusting the difficulty of each problem based on how the student was performing and interacting with the chatbot.\u003c/p>\n\u003cp>The idea is based on what educators call the “zone of proximal development.” When problems are too easy, students get bored. When they’re too hard, students get frustrated. The goal is to keep students in a sweet spot: challenged, but not overwhelmed.\u003c/p>\n\u003cp>The researchers found that students in the personalized group did better on a final exam than students in the fixed problem group. The difference was characterized as the equivalent of 6 to 9 months of additional schooling, an eye-catching claim for an after-school online course that lasted only five months. The AI tutor’s inventor, Angel Chung, a doctoral student at the Wharton School, acknowledged that her conversion of statistical units was “not a perfect estimate.” (A \u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6423358\">draft paper\u003c/a> about the experiment was posted online in March 2026, but has not yet been published in a peer-reviewed journal.)\u003c/p>\n\u003cp>Still, this is early evidence that small tweaks — in this case, calibrating the difficulty of the practice problems to the student — can make a difference.\u003c/p>\n\u003cp>Chung said that ChatGPT’s responses may already feel very personal because they are directly responding to a student’s unique questions. But that level of personalization isn’t enough. “Students usually don’t know what they don’t know,” said Chung. “The student doesn’t have the ability to ask the right questions to get the best tutoring.”\u003c/p>\n\u003cp>To address this, Chung’s team combined a large language model with a separate machine-learning algorithm that analyzes how students interact with the online course platform — how they answer the practice questions, how many times they revise or edit their coding, and the quality of their conversations with the chatbot — and uses that information to decide which problem to serve up next.\u003c/p>\n\u003ch2>\u003cstrong>How different students interact with the chatbot tutor\u003c/strong>\u003c/h2>\n\u003cfigure id=\"attachment_66238\" class=\"wp-caption alignnone\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-66238\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1.png\" alt=\"List of chatbot prompts\" width=\"780\" height=\"418\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1-160x86.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-1-768x412.png 768w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Source: Chung et al, Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning, March 2026\u003c/figcaption>\u003c/figure>\n\u003cp>In other words, personalization isn’t just about tailoring explanations. It’s about tailoring the learning path itself.\u003c/p>\n\u003cp>That idea isn’t new.\u003c/p>\n\u003cp>Long before generative AI tools like ChatGPT were invented, education researchers developed “intelligent tutoring systems” that tried to do something similar: estimate what a student knew and deliver the right next problem. These earlier systems couldn’t produce natural conversations, but they could provide hints and instant feedback. Rigorous studies found that well-designed versions helped students learn significantly more.\u003c/p>\n\u003cp>Their Achilles’ heel was engagement. Many students simply didn’t want to use them.\u003c/p>\n\u003cp>Today’s AI tools could help address that problem. Students might feel more interested in a chatbot that converses with them in an almost human way.\u003c/p>\n\u003cp>In the University of Pennsylvania study, students in the personalized group spent more time practicing, about three additional minutes per problem, adding up to about an hour per module in the Python course, compared with half as much time (a half hour or less) for the comparison students. The researchers think these students did better because they were more engaged in their practice work.\u003c/p>\n\u003cp>Students’ previous knowledge of a subject affected how well the personalized sequencing worked. Students who were new to Python gained more than those who already had Python experience, who did just as well with the fixed sequence of practice problems. Students from less elite high schools also appeared to benefit more.\u003c/p>\n\u003ch2>\u003cstrong>How students’ background affected results\u003c/strong>\u003c/h2>\n\u003cfigure id=\"attachment_66239\" class=\"wp-caption alignnone\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-66239\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2.png\" alt=\"Chart showing skill vs. prior experience\" width=\"780\" height=\"500\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2-160x103.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/04/Barshay-AI-Tutor-2-768x492.png 768w\" sizes=\"auto, (max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">All students had access to the same AI tutor. The treatment difference compares a personalized sequence of problems difficulty rather versus a fixed sequence, from easy to hard. Source: Chung et al, Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning, March 2026\u003c/figcaption>\u003c/figure>\n\u003cp>All the Taiwanese students in this study volunteered for an optional computer programming course that could strengthen their college applications. Many were highly motivated, with highly educated parents, and many already had prior coding experience.\u003c/p>\n\u003cp>It’s not clear whether the chatbot would work as well with less motivated students who are behind at school and most in need of extra help.\u003c/p>\n\u003cp>One possible solution: fusing new and old.\u003c/p>\n\u003cp>Ken Koedinger, a professor at Carnegie Mellon University and a pioneer of intelligent tutoring systems, is experimenting with using \u003ca href=\"https://dl.acm.org/doi/abs/10.1145/3698205.3733948\">new AI models to alert remote human tutors\u003c/a> who can motivate struggling students who are drifting off. “We are having more success,” said Koedinger.\u003c/p>\n\u003cp>Humans aren’t obsolete — yet.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-python/\">\u003cem>AI tutors\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>Rigorous research rarely shows that any teaching approach produces large and consistent benefits for students. But tutoring seemed to be a rare exception. Before the pandemic, \u003ca href=\"https://www.nber.org/papers/w27476\">almost 100 studies\u003c/a> pointed to impressive math or reading gains for students who were paired with a tutor at least three times a week and used a proven curriculum or set of lesson plans.\u003c/p>\n\u003cp>Some students gained an extra year’s worth of learning — far greater than the benefit of smaller classes, summer school or a fantastic teacher. These were rigorous randomized controlled trials, akin to the way that drugs or vaccines are tested, comparing test scores of tutored students against those who weren’t. The expense, sometimes surpassing \u003ca href=\"https://www.nber.org/system/files/working_papers/w28531/w28531.pdf\">$4,000 a year\u003c/a> per student, seemed worth it for what researchers called high-dosage tutoring.\u003c/p>\n\u003cp>On the strength of that evidence, the Biden administration urged schools to invest their pandemic recovery funds in intensive tutoring to help students catch up academically. \u003ca href=\"https://nces.ed.gov/whatsnew/press_releases/7_18_2024.asp\">Forty-six percent\u003c/a> of public schools heeded that call, according to a 2024 federal survey, though it’s unclear exactly how much of the $190 billion in pandemic recovery funds have been spent on high-dosage tutoring and how many students received it.\u003c/p>\n\u003cp>Even with ample money, schools immediately reported \u003ca href=\"https://hechingerreport.org/proof-points-early-data-on-high-dosage-tutoring-shows-schools-are-sometimes-finding-it-tough-to-deliver-even-low-doses/\">problems in ramping up\u003c/a> high-quality tutoring for so many students. In 2024, researchers documented either tiny or no academic benefits from large-scale tutoring efforts in \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">Nashville\u003c/a>, Tennessee, and \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-absenteeism/\">Washington, D.C\u003c/a>.\u003c/p>\n\u003cp>New evidence from the 2023-24 school year reinforces those results. Researchers are rigorously studying large-scale tutoring efforts around the nation and testing whether effective tutoring can be done more cheaply. A dozen researchers studied more than 20,000 students in Miami; Chicago; Atlanta; Winston-Salem and Greensboro, North Carolina; Greenville, South Carolina; schools throughout New Mexico, and a California charter school network. This was also a randomized controlled study in which 9,000 students were randomly assigned to get tutoring and compared with 11,000 students who didn’t get that extra help.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>Their preliminary results were “sobering,” according to a \u003ca href=\"https://www.mdrc.org/sites/default/files/UChicago-Education-Lab-PLI-Interim-Report-06.2025.pdf\">June report\u003c/a> by the University of Chicago Education Lab and MDRC, a research organization.\u003c/p>\n\u003cp>The researchers found that tutoring during the 2023-24 school year produced only one or two months’ worth of extra learning in reading or math — a tiny fraction of what the pre-pandemic research had produced. Each minute of tutoring that students received appeared to be as effective as in the pre-pandemic research, but students weren’t getting enough minutes of tutoring altogether. “Overall we still see that the dosage students are getting falls far short of what would be needed to fully realize the promise of high-dosage tutoring,” the report said.\u003c/p>\n\u003cp>Monica Bhatt, a researcher at the University of Chicago Education Lab and one of the report’s authors, said schools struggled to set up large tutoring programs. “The problem is the logistics of getting it delivered,” said Bhatt. Effective high-dosage tutoring involves big changes to bell schedules and classroom space, along with the challenge of hiring and training tutors. Educators need to make it a priority for it to happen, Bhatt said.\u003c/p>\n\u003cp>Some of the earlier, pre-pandemic tutoring studies involved large numbers of students, too, but those tutoring programs were carefully designed and implemented, often with researchers involved. In most cases, they were ideal setups. There was much greater variability in the quality of post-pandemic programs.\u003c/p>\n\u003cp>“For those of us that run experiments, one of the deep sources of frustration is that what you end up with is not what you tested and wanted to see,” said Philip Oreopoulos, an economist at the University of Toronto, whose \u003ca href=\"https://www.nber.org/papers/w27476\">2020 review of tutoring evidence\u003c/a> influenced policymakers. Oreopoulos was also an author of the June report.\u003c/p>\n\u003cp>“After you spend lots of people’s money and lots of time and effort, things don’t always go the way you hope. There’s a lot of fires to put out at the beginning or throughout because teachers or tutors aren’t doing what you want, or the hiring isn’t going well,” Oreopoulos said.\u003c/p>\n\u003cp>Another reason for the lackluster results could be that schools offered a lot of extra help to everyone after the pandemic, even to students who didn’t receive tutoring. In the pre-pandemic research, students in the “business as usual” control group often received no extra help at all, making the difference between tutoring and no tutoring far more stark. After the pandemic, students — tutored and non-tutored alike — had extra math and reading periods, sometimes called “labs” for review and practice work. More than three-quarters of the 20,000 students in this June analysis had access to computer-assisted instruction in math or reading, possibly muting the effects of tutoring.\u003c/p>\n\u003cp>The report did find that cheaper tutoring programs appeared to be just as effective (or ineffective) as the more expensive ones, an indication that the cheaper models are worth further testing. The cheaper models averaged $1,200 per student and had tutors working with eight students at a time, similar to small group instruction, often combining online practice work with human attention. The more expensive models averaged $2,000 per student and had tutors working with three to four students at once. By contrast, many of the pre-pandemic tutoring programs involved smaller 1-to-1 or 2-to-1 student-to-tutor ratios.\u003c/p>\n\u003cp>Despite the disappointing results, researchers said that educators shouldn’t give up. “High-dosage tutoring is still a district or state’s best bet to improve student learning, given that the learning impact per minute of tutoring is largely robust,” the report concludes. The task now is to figure out how to improve implementation and increase the hours that students are receiving. “Our recommendation for the field is to focus on increasing dosage — and, thereby learning gains,” Bhatt said.\u003c/p>\n\u003cp>That doesn’t mean that schools need to invest more in tutoring and saturate schools with effective tutors. That’s not realistic with the end of federal pandemic recovery funds.\u003c/p>\n\u003cp>Instead of tutoring for the masses, Bhatt said researchers are turning their attention to targeting a limited amount of tutoring to the right students. “We are focused on understanding which tutoring models work for which kinds of students.”\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-tutoring-effectiveness/\">\u003cem>tutoring effectiveness\u003c/em>\u003c/a>\u003cem> was written by Jill Barshay and produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>Rigorous research rarely shows that any teaching approach produces large and consistent benefits for students. But tutoring seemed to be a rare exception. Before the pandemic, \u003ca href=\"https://www.nber.org/papers/w27476\">almost 100 studies\u003c/a> pointed to impressive math or reading gains for students who were paired with a tutor at least three times a week and used a proven curriculum or set of lesson plans.\u003c/p>\n\u003cp>Some students gained an extra year’s worth of learning — far greater than the benefit of smaller classes, summer school or a fantastic teacher. These were rigorous randomized controlled trials, akin to the way that drugs or vaccines are tested, comparing test scores of tutored students against those who weren’t. The expense, sometimes surpassing \u003ca href=\"https://www.nber.org/system/files/working_papers/w28531/w28531.pdf\">$4,000 a year\u003c/a> per student, seemed worth it for what researchers called high-dosage tutoring.\u003c/p>\n\u003cp>On the strength of that evidence, the Biden administration urged schools to invest their pandemic recovery funds in intensive tutoring to help students catch up academically. \u003ca href=\"https://nces.ed.gov/whatsnew/press_releases/7_18_2024.asp\">Forty-six percent\u003c/a> of public schools heeded that call, according to a 2024 federal survey, though it’s unclear exactly how much of the $190 billion in pandemic recovery funds have been spent on high-dosage tutoring and how many students received it.\u003c/p>\n\u003cp>Even with ample money, schools immediately reported \u003ca href=\"https://hechingerreport.org/proof-points-early-data-on-high-dosage-tutoring-shows-schools-are-sometimes-finding-it-tough-to-deliver-even-low-doses/\">problems in ramping up\u003c/a> high-quality tutoring for so many students. In 2024, researchers documented either tiny or no academic benefits from large-scale tutoring efforts in \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">Nashville\u003c/a>, Tennessee, and \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-absenteeism/\">Washington, D.C\u003c/a>.\u003c/p>\n\u003cp>New evidence from the 2023-24 school year reinforces those results. Researchers are rigorously studying large-scale tutoring efforts around the nation and testing whether effective tutoring can be done more cheaply. A dozen researchers studied more than 20,000 students in Miami; Chicago; Atlanta; Winston-Salem and Greensboro, North Carolina; Greenville, South Carolina; schools throughout New Mexico, and a California charter school network. This was also a randomized controlled study in which 9,000 students were randomly assigned to get tutoring and compared with 11,000 students who didn’t get that extra help.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>Their preliminary results were “sobering,” according to a \u003ca href=\"https://www.mdrc.org/sites/default/files/UChicago-Education-Lab-PLI-Interim-Report-06.2025.pdf\">June report\u003c/a> by the University of Chicago Education Lab and MDRC, a research organization.\u003c/p>\n\u003cp>The researchers found that tutoring during the 2023-24 school year produced only one or two months’ worth of extra learning in reading or math — a tiny fraction of what the pre-pandemic research had produced. Each minute of tutoring that students received appeared to be as effective as in the pre-pandemic research, but students weren’t getting enough minutes of tutoring altogether. “Overall we still see that the dosage students are getting falls far short of what would be needed to fully realize the promise of high-dosage tutoring,” the report said.\u003c/p>\n\u003cp>Monica Bhatt, a researcher at the University of Chicago Education Lab and one of the report’s authors, said schools struggled to set up large tutoring programs. “The problem is the logistics of getting it delivered,” said Bhatt. Effective high-dosage tutoring involves big changes to bell schedules and classroom space, along with the challenge of hiring and training tutors. Educators need to make it a priority for it to happen, Bhatt said.\u003c/p>\n\u003cp>Some of the earlier, pre-pandemic tutoring studies involved large numbers of students, too, but those tutoring programs were carefully designed and implemented, often with researchers involved. In most cases, they were ideal setups. There was much greater variability in the quality of post-pandemic programs.\u003c/p>\n\u003cp>“For those of us that run experiments, one of the deep sources of frustration is that what you end up with is not what you tested and wanted to see,” said Philip Oreopoulos, an economist at the University of Toronto, whose \u003ca href=\"https://www.nber.org/papers/w27476\">2020 review of tutoring evidence\u003c/a> influenced policymakers. Oreopoulos was also an author of the June report.\u003c/p>\n\u003cp>“After you spend lots of people’s money and lots of time and effort, things don’t always go the way you hope. There’s a lot of fires to put out at the beginning or throughout because teachers or tutors aren’t doing what you want, or the hiring isn’t going well,” Oreopoulos said.\u003c/p>\n\u003cp>Another reason for the lackluster results could be that schools offered a lot of extra help to everyone after the pandemic, even to students who didn’t receive tutoring. In the pre-pandemic research, students in the “business as usual” control group often received no extra help at all, making the difference between tutoring and no tutoring far more stark. After the pandemic, students — tutored and non-tutored alike — had extra math and reading periods, sometimes called “labs” for review and practice work. More than three-quarters of the 20,000 students in this June analysis had access to computer-assisted instruction in math or reading, possibly muting the effects of tutoring.\u003c/p>\n\u003cp>The report did find that cheaper tutoring programs appeared to be just as effective (or ineffective) as the more expensive ones, an indication that the cheaper models are worth further testing. The cheaper models averaged $1,200 per student and had tutors working with eight students at a time, similar to small group instruction, often combining online practice work with human attention. The more expensive models averaged $2,000 per student and had tutors working with three to four students at once. By contrast, many of the pre-pandemic tutoring programs involved smaller 1-to-1 or 2-to-1 student-to-tutor ratios.\u003c/p>\n\u003cp>Despite the disappointing results, researchers said that educators shouldn’t give up. “High-dosage tutoring is still a district or state’s best bet to improve student learning, given that the learning impact per minute of tutoring is largely robust,” the report concludes. The task now is to figure out how to improve implementation and increase the hours that students are receiving. “Our recommendation for the field is to focus on increasing dosage — and, thereby learning gains,” Bhatt said.\u003c/p>\n\u003cp>That doesn’t mean that schools need to invest more in tutoring and saturate schools with effective tutors. That’s not realistic with the end of federal pandemic recovery funds.\u003c/p>\n\u003cp>Instead of tutoring for the masses, Bhatt said researchers are turning their attention to targeting a limited amount of tutoring to the right students. “We are focused on understanding which tutoring models work for which kinds of students.”\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-tutoring-effectiveness/\">\u003cem>tutoring effectiveness\u003c/em>\u003c/a>\u003cem> was written by Jill Barshay and produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>In early 2024, initial reports indicated that tutoring might not only help kids catch up academically after the pandemic but could also combat chronic absenteeism. More recent research, however, suggests that prediction may have been overly optimistic.\u003c/p>\n\u003cp>Stanford University researchers have been studying Washington, D.C.’s \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">$33 million\u003c/a> investment in tutoring, which provided extra help to more than 5,000 of the district’s 100,000 students in 2022-23, the second year of a three-year tutoring initiative. When researchers looked at these students’ test scores, they found \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">minimal to modest improvements in reading or math\u003c/a>.\u003c/p>\n\u003cp>“We weren’t seeing a ton of big impacts on achievement,” said Monica Lee, one of the Stanford researchers. “But what we were seeing at that point in time were promising findings that the tutoring might be doing something for attendance.”\u003c/p>\n\u003cp>That is important because \u003ca href=\"https://hechingerreport.org/proof-points-the-chronic-absenteeism-puzzle/\">absenteeism soared\u003c/a> after the pandemic. The \u003ca href=\"https://studentsupportaccelerator.org/about\">National Student Support Accelerator\u003c/a>, a Stanford-based organization that studies, promotes and seeks to improve tutoring, issued a \u003ca href=\"https://studentsupportaccelerator.org/news/early-findings-show-evidence-high-impact-tutoring-increases-student-attendance-dc-schools\">March 2024 press release\u003c/a> proclaiming that tutoring had increased student attendance in Washington, and could potentially address widespread chronic absenteeism, which was a particular scourge in the city. Soon after, Washington Mayor Muriel Bowser \u003ca href=\"https://www.washingtonpost.com/education/2024/03/20/tutoring-budget-schools/\">proposed an additional $4.8 million for tutoring\u003c/a>.\u003c/p>\n\u003cp>The lackluster academic results weren’t mentioned in the March press release or the news coverage, but were disclosed later in an \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">August report\u003c/a> by the National Student Support Accelerator. That same month, a separate group of researchers studying another large-scale tutoring effort in Nashville, Tennessee, also found \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">disappointing learning gains for students\u003c/a>. As tutoring expanded to reach thousands of students, the less it helped them in math and reading. Still, its side benefit of re-engaging students in school remained tantalizing.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>Then, in December, Stanford researchers with the National Student Support Accelerator released an academic \u003ca href=\"https://edworkingpapers.com/sites/default/files/ai24-1107.pdf\">paper\u003c/a> with more details about the heralded boost to attendance in Washington. Lee and her research team analyzed tutoring schedules for more than 4,000 of the students and calculated that a student was 7 percent less likely to be absent from school on a day when tutoring was on the schedule, compared with a day when tutoring was not on the schedule. The researchers thought that perhaps students felt like they were learning in these sessions, or enjoyed the personal attention, and looked forward to them.\u003c/p>\n\u003cp>Tutoring schedules ranged from once a week to daily. A student scheduled to receive tutoring three times a week, the recommended minimum for effective catch-up tutoring, would attend a total of 1.3 more days of school, on average, over a 180-day school year.\u003c/p>\n\u003cp>“That feels minimal, just a day or so,” Lee admitted. But she said it was “encouraging to move the needle at all,” with this group of economically disadvantaged students. More than 80 percent of the tutored students were Black. The remainder were largely Hispanic.\u003c/p>\n\u003cp>What struck me was the high average absenteeism rate among the thousands of students selected for tutoring: 17 percent. In other words, these students had missed more than 30 days, not including weekends. A large subset of them – one out of six – were considered to be “extremely absent,” missing more than 30 percent of the school year. That’s about 60 school days. “They’re missing school at an alarming rate,” said Lee.\u003c/p>\n\u003cp>No wonder these children and teens are so far behind. And no wonder Washington’s leaders wanted tutors for these kids, who were at risk of falling further behind and ultimately becoming dropouts.\u003c/p>\n\u003cp>I contacted Hedy Chang, the executive director of Attendance Works, an organization that works with schools to boost attendance, to ask how significant one additional day of school could be for chronically absent students. She said working with kids who are missing 30 days of school is important. “I am a bit concerned that this small change (1.3), while promising, might not be enough to make a difference,” she said in an email.\u003c/p>\n\u003cp>Chang consulted with her research team and they found a bright spot: small gains can add up across a school. For one student, 1.3 days is small, Chang explained. But across 100 students, that’s 130 more days. “It could be a movement towards more stability in classrooms,” Chang said.\u003c/p>\n\u003cp>Averages mask big differences. Some students’ attendance increased by a lot more. Middle school students were the most likely to attend school on a tutoring day, translating to 2.1 additional days of school for a student who was scheduled three times a week. High school students were the least likely to be motivated to attend school. Their attendance wasn’t much different between days with and without tutoring. Tutoring scheduled during the school day was more of a motivator to show up than tutoring scheduled after school. Smaller tutor-to-student ratios of 1-to-1 or 1-to-2 were more effective in reducing absenteeism than larger tutoring groups of three or four students. (All of the tutoring was in-person, not online.)\u003c/p>\n\u003cp>Much of what schools actually try in education is rarely studied and analyzed rigorously. Research like this helps school leaders reflect on what works and what doesn’t. Washington deserves credit for trying tutoring, which had shown strong benefits in \u003ca href=\"https://www.nber.org/papers/w27476\">hundreds of earlier, albeit smaller studies\u003c/a>, and for opening its doors to researchers to study its big rollout.\u003c/p>\n\u003cp>It didn’t work as well as hoped for a variety of reasons. Some of the tutoring wasn’t scheduled as often as the \u003ca href=\"https://hechingerreport.org/proof-points-taking-stock-of-tutoring/\">research advised\u003c/a>, or during the school day when attendance is highest. But the critical lesson we learn from this analysis is that some students may be too disengaged from school to take advantage of even well-designed tutoring programs. It’s useless to hire tutors for students who don’t show up.\u003c/p>\n\u003cp>The Stanford study makes the argument that tutoring itself helps to re-engage kids in school and that any improvement in attendance is worthwhile. But I question the economic value when the benefit is so tiny.\u003c/p>\n\u003cp>I don’t envy school leaders. They are dealing with masses of disengaged students and we don’t have good solutions for them.\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-tutoring-absenteeism/\">\u003cem>tutoring attendance\u003c/em>\u003c/a>\u003cem> was written by Jill Barshay and produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>In early 2024, initial reports indicated that tutoring might not only help kids catch up academically after the pandemic but could also combat chronic absenteeism. More recent research, however, suggests that prediction may have been overly optimistic.\u003c/p>\n\u003cp>Stanford University researchers have been studying Washington, D.C.’s \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">$33 million\u003c/a> investment in tutoring, which provided extra help to more than 5,000 of the district’s 100,000 students in 2022-23, the second year of a three-year tutoring initiative. When researchers looked at these students’ test scores, they found \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">minimal to modest improvements in reading or math\u003c/a>.\u003c/p>\n\u003cp>“We weren’t seeing a ton of big impacts on achievement,” said Monica Lee, one of the Stanford researchers. “But what we were seeing at that point in time were promising findings that the tutoring might be doing something for attendance.”\u003c/p>\n\u003cp>That is important because \u003ca href=\"https://hechingerreport.org/proof-points-the-chronic-absenteeism-puzzle/\">absenteeism soared\u003c/a> after the pandemic. The \u003ca href=\"https://studentsupportaccelerator.org/about\">National Student Support Accelerator\u003c/a>, a Stanford-based organization that studies, promotes and seeks to improve tutoring, issued a \u003ca href=\"https://studentsupportaccelerator.org/news/early-findings-show-evidence-high-impact-tutoring-increases-student-attendance-dc-schools\">March 2024 press release\u003c/a> proclaiming that tutoring had increased student attendance in Washington, and could potentially address widespread chronic absenteeism, which was a particular scourge in the city. Soon after, Washington Mayor Muriel Bowser \u003ca href=\"https://www.washingtonpost.com/education/2024/03/20/tutoring-budget-schools/\">proposed an additional $4.8 million for tutoring\u003c/a>.\u003c/p>\n\u003cp>The lackluster academic results weren’t mentioned in the March press release or the news coverage, but were disclosed later in an \u003ca href=\"https://studentsupportaccelerator.org/sites/default/files/Implementation%20of%20the%20OSSE%20High%20Impact%20Tutoring%20Initiative.pdf\">August report\u003c/a> by the National Student Support Accelerator. That same month, a separate group of researchers studying another large-scale tutoring effort in Nashville, Tennessee, also found \u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">disappointing learning gains for students\u003c/a>. As tutoring expanded to reach thousands of students, the less it helped them in math and reading. Still, its side benefit of re-engaging students in school remained tantalizing.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>Then, in December, Stanford researchers with the National Student Support Accelerator released an academic \u003ca href=\"https://edworkingpapers.com/sites/default/files/ai24-1107.pdf\">paper\u003c/a> with more details about the heralded boost to attendance in Washington. Lee and her research team analyzed tutoring schedules for more than 4,000 of the students and calculated that a student was 7 percent less likely to be absent from school on a day when tutoring was on the schedule, compared with a day when tutoring was not on the schedule. The researchers thought that perhaps students felt like they were learning in these sessions, or enjoyed the personal attention, and looked forward to them.\u003c/p>\n\u003cp>Tutoring schedules ranged from once a week to daily. A student scheduled to receive tutoring three times a week, the recommended minimum for effective catch-up tutoring, would attend a total of 1.3 more days of school, on average, over a 180-day school year.\u003c/p>\n\u003cp>“That feels minimal, just a day or so,” Lee admitted. But she said it was “encouraging to move the needle at all,” with this group of economically disadvantaged students. More than 80 percent of the tutored students were Black. The remainder were largely Hispanic.\u003c/p>\n\u003cp>What struck me was the high average absenteeism rate among the thousands of students selected for tutoring: 17 percent. In other words, these students had missed more than 30 days, not including weekends. A large subset of them – one out of six – were considered to be “extremely absent,” missing more than 30 percent of the school year. That’s about 60 school days. “They’re missing school at an alarming rate,” said Lee.\u003c/p>\n\u003cp>No wonder these children and teens are so far behind. And no wonder Washington’s leaders wanted tutors for these kids, who were at risk of falling further behind and ultimately becoming dropouts.\u003c/p>\n\u003cp>I contacted Hedy Chang, the executive director of Attendance Works, an organization that works with schools to boost attendance, to ask how significant one additional day of school could be for chronically absent students. She said working with kids who are missing 30 days of school is important. “I am a bit concerned that this small change (1.3), while promising, might not be enough to make a difference,” she said in an email.\u003c/p>\n\u003cp>Chang consulted with her research team and they found a bright spot: small gains can add up across a school. For one student, 1.3 days is small, Chang explained. But across 100 students, that’s 130 more days. “It could be a movement towards more stability in classrooms,” Chang said.\u003c/p>\n\u003cp>Averages mask big differences. Some students’ attendance increased by a lot more. Middle school students were the most likely to attend school on a tutoring day, translating to 2.1 additional days of school for a student who was scheduled three times a week. High school students were the least likely to be motivated to attend school. Their attendance wasn’t much different between days with and without tutoring. Tutoring scheduled during the school day was more of a motivator to show up than tutoring scheduled after school. Smaller tutor-to-student ratios of 1-to-1 or 1-to-2 were more effective in reducing absenteeism than larger tutoring groups of three or four students. (All of the tutoring was in-person, not online.)\u003c/p>\n\u003cp>Much of what schools actually try in education is rarely studied and analyzed rigorously. Research like this helps school leaders reflect on what works and what doesn’t. Washington deserves credit for trying tutoring, which had shown strong benefits in \u003ca href=\"https://www.nber.org/papers/w27476\">hundreds of earlier, albeit smaller studies\u003c/a>, and for opening its doors to researchers to study its big rollout.\u003c/p>\n\u003cp>It didn’t work as well as hoped for a variety of reasons. Some of the tutoring wasn’t scheduled as often as the \u003ca href=\"https://hechingerreport.org/proof-points-taking-stock-of-tutoring/\">research advised\u003c/a>, or during the school day when attendance is highest. But the critical lesson we learn from this analysis is that some students may be too disengaged from school to take advantage of even well-designed tutoring programs. It’s useless to hire tutors for students who don’t show up.\u003c/p>\n\u003cp>The Stanford study makes the argument that tutoring itself helps to re-engage kids in school and that any improvement in attendance is worthwhile. But I question the economic value when the benefit is so tiny.\u003c/p>\n\u003cp>I don’t envy school leaders. They are dealing with masses of disengaged students and we don’t have good solutions for them.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cp>\u003cspan style=\"font-weight: 400\">We are still in the early days of understanding the promise and peril of using generative AI in education. Very few researchers have evaluated whether students are benefiting, and one well-designed study showed that using ChatGPT for math actually \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/64575/kids-who-use-chatgpt-as-a-study-assistant-do-worse-on-tests\">\u003cspan style=\"font-weight: 400\">harmed student achievement\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first scientific proof I’ve seen that ChatGPT can actually help students learn more was posted online earlier this year. It’s a small experiment, involving fewer than 200 undergraduates. All were Harvard students taking an introductory physics class in the fall of 2023, so the findings may not be widely applicable. But students learned more than twice as much in less time when they used an AI tutor in their dorm compared with attending their usual physics class in person. Students also reported that they felt more engaged and motivated. They learned more and they liked it. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">A \u003c/span>\u003ca href=\"https://www.researchsquare.com/article/rs-4243877/v1\">\u003cspan style=\"font-weight: 400\">paper about the experiment\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> has not yet been published in a peer-reviewed journal, but other physicists at Harvard University praised it as a well-designed experiment. Students were randomly assigned to learn a topic as usual in class, or stay “home” in their dorm and learn it through an AI tutor powered by ChatGPT. Students took brief tests at the beginning and the end of class, or their AI sessions, to measure how much they learned. The following week, the in-class students learned the next topic through the AI tutor in their dorms, and the AI-tutored students went back to class. Each student learned both ways, and for both lessons – one on surface tension and one on fluid flow – the AI-tutored students learned a lot more. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">To avoid AI “hallucinations,” the tendency of chatbots to \u003ca href=\"https://www.kqed.org/mindshift/64532/researchers-combat-ai-hallucinations-in-math\">make up stuff that isn’t true\u003c/a>, the AI tutor was given all the correct solutions. But other developers of AI tutors have also supplied their bots with answer keys. Gregory Kestin, a physics lecturer at Harvard and developer of the AI tutor used in this study, argues that his effort succeeded while others have failed because he and his colleagues fine-tuned it with pedagogical best practices. For example, the Harvard scientists instructed this AI tutor to be brief, using no more than a few sentences, to avoid cognitive overload. Otherwise, he explained, ChatGPT has a tendency to be “long-winded.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The tutor, which Kestin calls “PS2 Pal,” after the Physical Sciences 2 class he teaches, was told to only give away one step at a time and not to divulge the full solution in a single message. PS2 Pal was also instructed to encourage students to think and give it a try themselves before revealing the answer. \u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp> \u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Unguided use of ChatGPT, the Harvard scientists argue, lets students complete assignments without engaging in critical thinking. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin doesn’t deliver traditional lectures. Like many physicists at Harvard, he teaches through a method called “\u003c/span>\u003ca href=\"https://hechingerreport.org/proof-points-college-students-often-dont-know-when-theyre-learning/\">\u003cspan style=\"font-weight: 400\">active learning\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” where students first work with peers on in-class problem sets as the lecturer gives feedback. Direct explanations or mini-lectures come after a bit of trial, error and struggle. Kestin sought to reproduce aspects of this teaching style with the AI tutor. Students toiled on the same set of activities and Kestin fed the AI tutor the same feedback notes that he planned to deliver in class.\u003c/span>\u003c/p>\n\u003cp>\u003cimg loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-64698\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1.png\" alt=\"\" width=\"780\" height=\"638\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1-160x131.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1-768x628.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin provocatively titled his paper about the experiment, “\u003c/span>\u003cspan style=\"font-weight: 400\">AI Tutoring Outperforms Active Learning\u003c/span>\u003cspan style=\"font-weight: 400\">,” but in an interview he told me that he doesn’t mean to suggest that AI should replace professors or traditional in-person classes. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I don’t think that this is an argument for replacing any human interaction,” said Kestin. “This allows for the human interaction to be much richer.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin says he intends to continue teaching through in-person classes, and he remains convinced that students learn a lot from each other by discussing how to solve problems in groups. He believes the best use of this AI tutor would be to introduce a new topic ahead of class – much like professors assign reading in advance. That way students with less background knowledge won’t be as behind and can participate more fully in class activities. Kestin hopes his AI tutor will allow him to spend less time on vocabulary and basics and devote more time to creative activities and advanced problems during class.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Of course, the benefits of an AI tutor depend on students actually using it. In other efforts, students often didn’t want to use earlier versions of education technology and computerized tutors. In this experiment, the “at-home” sessions with PS2 Pal were scheduled and proctored over Zoom. It’s not clear that even highly motivated Harvard students will find it engaging enough to use regularly on their own initiative. Cute emojis – another element that the Harvard scientists prompted their AI tutor to use – may not be enough to sustain long-term interest. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin’s next step is to test the tutor bot for an entire semester. He’s also been testing PS2 Pal as a study assistant with homework. Kestin said he’s seeing promising signs that it’s helpful for basic but not advanced problems. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The irony is that AI tutors may not be that effective at what we generally think of as tutoring. Kestin doesn’t think that current AI technology is good at anything that requires knowing a lot about a person, such as what the student already learned in class or what kind of explanatory metaphor might work.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“Humans have a lot of context that you can use along with your judgment in order to guide a student better than an AI can,” he said. In contrast, AI is good at introducing students to new material because you only need “limited context” about someone and “minimal judgment” for how best to teach it.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about an \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-harvard-physics/\">\u003ci>\u003cspan style=\"font-weight: 400\">AI tutor\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">We are still in the early days of understanding the promise and peril of using generative AI in education. Very few researchers have evaluated whether students are benefiting, and one well-designed study showed that using ChatGPT for math actually \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/64575/kids-who-use-chatgpt-as-a-study-assistant-do-worse-on-tests\">\u003cspan style=\"font-weight: 400\">harmed student achievement\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first scientific proof I’ve seen that ChatGPT can actually help students learn more was posted online earlier this year. It’s a small experiment, involving fewer than 200 undergraduates. All were Harvard students taking an introductory physics class in the fall of 2023, so the findings may not be widely applicable. But students learned more than twice as much in less time when they used an AI tutor in their dorm compared with attending their usual physics class in person. Students also reported that they felt more engaged and motivated. They learned more and they liked it. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">A \u003c/span>\u003ca href=\"https://www.researchsquare.com/article/rs-4243877/v1\">\u003cspan style=\"font-weight: 400\">paper about the experiment\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> has not yet been published in a peer-reviewed journal, but other physicists at Harvard University praised it as a well-designed experiment. Students were randomly assigned to learn a topic as usual in class, or stay “home” in their dorm and learn it through an AI tutor powered by ChatGPT. Students took brief tests at the beginning and the end of class, or their AI sessions, to measure how much they learned. The following week, the in-class students learned the next topic through the AI tutor in their dorms, and the AI-tutored students went back to class. Each student learned both ways, and for both lessons – one on surface tension and one on fluid flow – the AI-tutored students learned a lot more. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">To avoid AI “hallucinations,” the tendency of chatbots to \u003ca href=\"https://www.kqed.org/mindshift/64532/researchers-combat-ai-hallucinations-in-math\">make up stuff that isn’t true\u003c/a>, the AI tutor was given all the correct solutions. But other developers of AI tutors have also supplied their bots with answer keys. Gregory Kestin, a physics lecturer at Harvard and developer of the AI tutor used in this study, argues that his effort succeeded while others have failed because he and his colleagues fine-tuned it with pedagogical best practices. For example, the Harvard scientists instructed this AI tutor to be brief, using no more than a few sentences, to avoid cognitive overload. Otherwise, he explained, ChatGPT has a tendency to be “long-winded.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The tutor, which Kestin calls “PS2 Pal,” after the Physical Sciences 2 class he teaches, was told to only give away one step at a time and not to divulge the full solution in a single message. PS2 Pal was also instructed to encourage students to think and give it a try themselves before revealing the answer. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp> \u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Unguided use of ChatGPT, the Harvard scientists argue, lets students complete assignments without engaging in critical thinking. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin doesn’t deliver traditional lectures. Like many physicists at Harvard, he teaches through a method called “\u003c/span>\u003ca href=\"https://hechingerreport.org/proof-points-college-students-often-dont-know-when-theyre-learning/\">\u003cspan style=\"font-weight: 400\">active learning\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” where students first work with peers on in-class problem sets as the lecturer gives feedback. Direct explanations or mini-lectures come after a bit of trial, error and struggle. Kestin sought to reproduce aspects of this teaching style with the AI tutor. Students toiled on the same set of activities and Kestin fed the AI tutor the same feedback notes that he planned to deliver in class.\u003c/span>\u003c/p>\n\u003cp>\u003cimg loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-64698\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1.png\" alt=\"\" width=\"780\" height=\"638\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1-160x131.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-1-768x628.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin provocatively titled his paper about the experiment, “\u003c/span>\u003cspan style=\"font-weight: 400\">AI Tutoring Outperforms Active Learning\u003c/span>\u003cspan style=\"font-weight: 400\">,” but in an interview he told me that he doesn’t mean to suggest that AI should replace professors or traditional in-person classes. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I don’t think that this is an argument for replacing any human interaction,” said Kestin. “This allows for the human interaction to be much richer.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin says he intends to continue teaching through in-person classes, and he remains convinced that students learn a lot from each other by discussing how to solve problems in groups. He believes the best use of this AI tutor would be to introduce a new topic ahead of class – much like professors assign reading in advance. That way students with less background knowledge won’t be as behind and can participate more fully in class activities. Kestin hopes his AI tutor will allow him to spend less time on vocabulary and basics and devote more time to creative activities and advanced problems during class.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Of course, the benefits of an AI tutor depend on students actually using it. In other efforts, students often didn’t want to use earlier versions of education technology and computerized tutors. In this experiment, the “at-home” sessions with PS2 Pal were scheduled and proctored over Zoom. It’s not clear that even highly motivated Harvard students will find it engaging enough to use regularly on their own initiative. Cute emojis – another element that the Harvard scientists prompted their AI tutor to use – may not be enough to sustain long-term interest. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kestin’s next step is to test the tutor bot for an entire semester. He’s also been testing PS2 Pal as a study assistant with homework. Kestin said he’s seeing promising signs that it’s helpful for basic but not advanced problems. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The irony is that AI tutors may not be that effective at what we generally think of as tutoring. Kestin doesn’t think that current AI technology is good at anything that requires knowing a lot about a person, such as what the student already learned in class or what kind of explanatory metaphor might work.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“Humans have a lot of context that you can use along with your judgment in order to guide a student better than an AI can,” he said. In contrast, AI is good at introducing students to new material because you only need “limited context” about someone and “minimal judgment” for how best to teach it.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about an \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-harvard-physics/\">\u003ci>\u003cspan style=\"font-weight: 400\">AI tutor\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Matthew Kraft, an associate professor of education and economics at Brown University, was an \u003c/span>\u003ca href=\"https://www.brookings.edu/articles/getting-tutoring-right-to-reduce-covid-19-learning-loss/\">\u003cspan style=\"font-weight: 400\">early proponent\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> of giving tutors — ordinarily a luxury for the rich — to the masses after the pandemic. The research evidence was strong; more than a hundred studies had shown remarkable academic gains for students who were frequently tutored every week at school. Sometimes, they caught up two grade levels in a single year. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">After COVID-19 shuttered schools in the spring of 2020, Kraft along with a small group of academics lobbied the Biden administration to urge schools to invest in this kind of intensive tutoring across the nation to help students catch up from pandemic learning losses. \u003c/span>\u003ca href=\"https://nces.ed.gov/surveys/spp/results.asp#tutoring-may24-chart-1.\">\u003cspan style=\"font-weight: 400\">Many schools did\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> — or tried to do so. Now, in a moment of scholarly honesty and reflection, Kraft has produced a study showing that tutoring the masses isn’t so easy — even with \u003ca href=\"https://www.kqed.org/mindshift/64123/pandemic-aid-to-schools-paid-off-but-we-dont-know-how\">billions of dollars from Uncle Sam\u003c/a>. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The study, which was posted online in \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-1030\">\u003cspan style=\"font-weight: 400\">late August 2024\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, tracked almost 7,000 students who were tutored in Nashville, Tennessee, and calculated how much of their academic progress could be attributed to the sessions of tutoring they received at school between 2021 and 2023. Kraft and his research team found that tutoring produced only a small boost to reading test scores, on average, and no improvement in math. Tutoring failed to lift course grades in either subject.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“These results are not as large as many in the education sector had hoped,” said Kraft in an interview. That’s something of an academic understatement. The one and only positive result for students was a tiny fraction of what earlier tutoring studies had found.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I was and continue to be incredibly impressed with the rigorous and wide body of evidence that exists for tutoring and the large average effects that those studies produced,” said Kraft. “I don’t think I paid as much attention to whether those tutoring programs were as applicable to post-COVID era tutoring at scale.”\u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Going forward, Kraft said he and other researchers need to “recalibrate” or adjust expectations around the “eye-popping” or very large impacts that previous small-scale tutoring programs have achieved.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kraft described the Nashville program as “multiple orders of magnitude” larger than the pre-COVID tutoring studies. Those were often less than 50 students, while some involved a few hundred. Only a handful included over 1,000 students. Nashville’s tutoring program reached almost 7,000 students, roughly 10% of the district’s student population. \u003c/span>\u003c/p>\n\u003cp>\u003ca href=\"https://hechingerreport.org/takeaways-from-research-on-tutoring-to-address-coronavirus-learning-loss/\">\u003cspan style=\"font-weight: 400\">Tennessee was a trailblazer\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in tutoring after the pandemic. State lawmakers appropriated \u003c/span>\u003ca href=\"https://www.tn.gov/education/tn-all-corps.html\">\u003cspan style=\"font-weight: 400\">extra funding\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> to schools to launch large tutoring programs, even before the \u003c/span>\u003ca href=\"https://www.whitehouse.gov/briefing-room/statements-releases/2022/07/05/fact-sheet-biden-harris-administration-launches-national-effort-to-support-student-success/?utm_content=&utm_medium=email&utm_name=&utm_source=govdelivery&utm_term=\">\u003cspan style=\"font-weight: 400\">Biden administration urged\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> schools around the nation to do the same with their federal COVID recovery funds. Nashville partnered with researchers, including Kraft, to study its ramp up and outcomes for students to help advise on improvements along the way. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">As with the launching of any big new program, Nashville hit a series of snags. Early administrators were overwhelmed with “14 bazillion emails,” as educators described them to researchers in the study, before they hired enough staff to coordinate the tutoring program. They first tried online tutoring. But too much time and effort was wasted setting kids up on computers, coping with software problems, and searching for missing headphones. Some children had to sit in the hallway with their tablets and headphones; it was hard to concentrate. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Meanwhile, \u003ca href=\"https://www.kqed.org/mindshift/64197/new-studies-of-online-tutoring-highlight-troubles-with-attendance-and-larger-tutoring-groups\">remote tutors\u003c/a> were frustrated by not being able to talk with teachers regularly. Often there was redundancy with tutors being told to teach topics identical to what the students were learning in class. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The content of the tutoring lessons was in turmoil, too. The city scrapped its math curriculum midway. Different grades required different reading curricula. For each of them, Nashville educators needed to create tutor guides and student workbooks from scratch.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Eventually the city switched course and replaced its remote tutors, who were college student volunteers, with teachers at the school who could tutor in-person. That eliminated the headaches of troublesome technology. Also, teachers could adjust the tutoring lessons to avoid repeating exactly what they had taught in class. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But school teachers were fewer in number and couldn’t serve as many students as an army of remote volunteers. Instead of one tutor for each student, teachers worked with three or four students at a time. Even after tripling and quadrupling up, there weren’t enough teachers to tutor everyone during school hours. Half the students had their tutoring sessions scheduled immediately before or right after school.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In interviews, teachers said they enjoyed the stronger relationships they were building with their students. But there were tradeoffs. The extra tutoring work raised concerns about teacher burnout.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Despite the flux, some things improved as the tutoring program evolved. The average number of tutoring sessions that students attended increased from 16 sessions in the earlier semesters to 24 sessions per semester by spring of 2023. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Why the academic gains for students weren’t stronger is unclear. One of Kraft’s theories is that Nashville asked tutors to teach grade-level skills and topics, similar to what the children were also learning in their classrooms and what the state tests would assess. But many students were months, even years behind grade level, and may have needed to learn rudimentary skills before being able to grasp more advanced topics. (This problem surprised me because I thought the whole purpose of tutoring was to fill in missing skills and knowledge!) In the data, average students in the middle of the achievement distribution showed the greatest gains from Nashville’s tutoring program. Students at the bottom and top didn’t progress much, or at all. (See the graph below.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“What’s most important is that we figure out what tutoring programs and design features work best for which students,” Kraft said. \u003c/span>\u003c/p>\n\u003cp>\u003cb>Average students in the middle of the achievement distribution gained the most from Nashville’s tutoring program, while students who were the most behind did not catch up much\u003c/b>\u003c/p>\n\u003cfigure id=\"attachment_64629\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"wp-image-64629 size-full\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1.png\" alt=\"\" width=\"780\" height=\"308\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-160x63.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-768x303.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Source: Kraft, Matthew A., Danielle Sanderson Edwards, and Marisa Cannata. (2024). The Scaling Dynamics and Causal Effects of a District-Operated Tutoring Program.\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another reason for the disappointing academic gains from tutoring may be related to the individualized attention that many students were also receiving at Nashville’s schools. Tutoring often took place during frequently scheduled periods of “Personalized Learning Time” for students, and even students not selected for tutoring received other instruction during this period, such as small-group work with a teacher or individual services for children with special needs. Another set of students was assigned independent practice work using advanced educational software that adapts to a student’s level. To demonstrate positive results in this study, tutoring would have had to outperform all these other interventions. It’s possible that these other interventions are as powerful as tutoring. Earlier pre-COVID studies of tutoring generally compared the gains against those of students who had nothing more than traditional whole class instruction. That’s a starker comparison. (To be sure, one would still have hoped to see stronger results for tutoring as the Nashville program migrated to outside of school hours; students who received both tutoring and personalized learning time should have meaningfully outperformed students who had only the personalized learning time.)\u003c/span>\u003c/p>\n\u003cp>Other post-pandemic tutoring research has been rosier. A\u003ca href=\"https://url.us.m.mimecastprotect.com/s/1wkbCQWOVBTlJGNpcPhpCGWLaF?domain=educationlab.uchicago.edu\" target=\"_blank\" rel=\"noopener noreferrer\"> smaller study of frequent in-school tutoring in Chicago and Atlanta\u003c/a>, released in March 2024, found giant gains for students in math, enough to totally undo learning losses for the average student. However, those results were achieved by only three-quarters of the roughly 800 students who had been assigned to receive tutoring and actually attended sessions.*\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kraft argued that schools should not abandon tutoring just because it’s not a silver bullet for academic recovery after COVID. “I worry,” he said, “that we may excuse ourselves from the hard work of iterative experimentation and continuous improvement by saying that we didn’t get the eye-popping results that we had hoped for right out of the gate, and therefore it’s not the solution that we should continue to invest in.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Iteratively is how the business world innovates too. I’m a former business reporter, and this rocky effort to bring tutoring to schools reminds me of how Levi’s introduced custom-made jeans for the masses in the 1990s. These “personal pairs” didn’t cost much more than traditional mass-produced jeans, but it was time consuming for clerks to take measurements, often the jeans didn’t fit and reorders were a hassle. Levi’s \u003c/span>\u003ca href=\"https://mass-customization.blogs.com/mass_customization_open_i/2005/12/repost_analysis.html\">\u003cspan style=\"font-weight: 400\">pulled the plug\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in 2003. Eventually it brought back custom jeans — truly bespoke ones made by a master tailor at \u003c/span>\u003ca href=\"https://www.levistrauss.com/2013/09/23/sewing-secret-master-tailor/\">\u003cspan style=\"font-weight: 400\">$750\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> or more a pop. For the masses? Maybe not. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">I wonder if customized instruction can be accomplished at scale at an affordable price. To really help students who are behind, tutors will need to diagnose each student’s learning gaps, and then develop a customized learning plan for each student. That’s pricey, and maybe impossible to do for millions of students all over the country. \u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">\u003ci>\u003cspan style=\"font-weight: 400\">tutoring research\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003cem>*Correction: An earlier version of this story incorrectly stated how many students were assigned to receive tutoring in the Chicago and Atlanta experiment. Only 784 students were to be tutored out of 1,540 students in the study. About three-quarters of those 784 students received tutoring. The sentence was also revised to clarify which students’ math outcomes drove the results.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Matthew Kraft, an associate professor of education and economics at Brown University, was an \u003c/span>\u003ca href=\"https://www.brookings.edu/articles/getting-tutoring-right-to-reduce-covid-19-learning-loss/\">\u003cspan style=\"font-weight: 400\">early proponent\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> of giving tutors — ordinarily a luxury for the rich — to the masses after the pandemic. The research evidence was strong; more than a hundred studies had shown remarkable academic gains for students who were frequently tutored every week at school. Sometimes, they caught up two grade levels in a single year. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">After COVID-19 shuttered schools in the spring of 2020, Kraft along with a small group of academics lobbied the Biden administration to urge schools to invest in this kind of intensive tutoring across the nation to help students catch up from pandemic learning losses. \u003c/span>\u003ca href=\"https://nces.ed.gov/surveys/spp/results.asp#tutoring-may24-chart-1.\">\u003cspan style=\"font-weight: 400\">Many schools did\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> — or tried to do so. Now, in a moment of scholarly honesty and reflection, Kraft has produced a study showing that tutoring the masses isn’t so easy — even with \u003ca href=\"https://www.kqed.org/mindshift/64123/pandemic-aid-to-schools-paid-off-but-we-dont-know-how\">billions of dollars from Uncle Sam\u003c/a>. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The study, which was posted online in \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-1030\">\u003cspan style=\"font-weight: 400\">late August 2024\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, tracked almost 7,000 students who were tutored in Nashville, Tennessee, and calculated how much of their academic progress could be attributed to the sessions of tutoring they received at school between 2021 and 2023. Kraft and his research team found that tutoring produced only a small boost to reading test scores, on average, and no improvement in math. Tutoring failed to lift course grades in either subject.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“These results are not as large as many in the education sector had hoped,” said Kraft in an interview. That’s something of an academic understatement. The one and only positive result for students was a tiny fraction of what earlier tutoring studies had found.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I was and continue to be incredibly impressed with the rigorous and wide body of evidence that exists for tutoring and the large average effects that those studies produced,” said Kraft. “I don’t think I paid as much attention to whether those tutoring programs were as applicable to post-COVID era tutoring at scale.”\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Going forward, Kraft said he and other researchers need to “recalibrate” or adjust expectations around the “eye-popping” or very large impacts that previous small-scale tutoring programs have achieved.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kraft described the Nashville program as “multiple orders of magnitude” larger than the pre-COVID tutoring studies. Those were often less than 50 students, while some involved a few hundred. Only a handful included over 1,000 students. Nashville’s tutoring program reached almost 7,000 students, roughly 10% of the district’s student population. \u003c/span>\u003c/p>\n\u003cp>\u003ca href=\"https://hechingerreport.org/takeaways-from-research-on-tutoring-to-address-coronavirus-learning-loss/\">\u003cspan style=\"font-weight: 400\">Tennessee was a trailblazer\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in tutoring after the pandemic. State lawmakers appropriated \u003c/span>\u003ca href=\"https://www.tn.gov/education/tn-all-corps.html\">\u003cspan style=\"font-weight: 400\">extra funding\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> to schools to launch large tutoring programs, even before the \u003c/span>\u003ca href=\"https://www.whitehouse.gov/briefing-room/statements-releases/2022/07/05/fact-sheet-biden-harris-administration-launches-national-effort-to-support-student-success/?utm_content=&utm_medium=email&utm_name=&utm_source=govdelivery&utm_term=\">\u003cspan style=\"font-weight: 400\">Biden administration urged\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> schools around the nation to do the same with their federal COVID recovery funds. Nashville partnered with researchers, including Kraft, to study its ramp up and outcomes for students to help advise on improvements along the way. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">As with the launching of any big new program, Nashville hit a series of snags. Early administrators were overwhelmed with “14 bazillion emails,” as educators described them to researchers in the study, before they hired enough staff to coordinate the tutoring program. They first tried online tutoring. But too much time and effort was wasted setting kids up on computers, coping with software problems, and searching for missing headphones. Some children had to sit in the hallway with their tablets and headphones; it was hard to concentrate. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Meanwhile, \u003ca href=\"https://www.kqed.org/mindshift/64197/new-studies-of-online-tutoring-highlight-troubles-with-attendance-and-larger-tutoring-groups\">remote tutors\u003c/a> were frustrated by not being able to talk with teachers regularly. Often there was redundancy with tutors being told to teach topics identical to what the students were learning in class. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The content of the tutoring lessons was in turmoil, too. The city scrapped its math curriculum midway. Different grades required different reading curricula. For each of them, Nashville educators needed to create tutor guides and student workbooks from scratch.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Eventually the city switched course and replaced its remote tutors, who were college student volunteers, with teachers at the school who could tutor in-person. That eliminated the headaches of troublesome technology. Also, teachers could adjust the tutoring lessons to avoid repeating exactly what they had taught in class. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But school teachers were fewer in number and couldn’t serve as many students as an army of remote volunteers. Instead of one tutor for each student, teachers worked with three or four students at a time. Even after tripling and quadrupling up, there weren’t enough teachers to tutor everyone during school hours. Half the students had their tutoring sessions scheduled immediately before or right after school.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In interviews, teachers said they enjoyed the stronger relationships they were building with their students. But there were tradeoffs. The extra tutoring work raised concerns about teacher burnout.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Despite the flux, some things improved as the tutoring program evolved. The average number of tutoring sessions that students attended increased from 16 sessions in the earlier semesters to 24 sessions per semester by spring of 2023. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Why the academic gains for students weren’t stronger is unclear. One of Kraft’s theories is that Nashville asked tutors to teach grade-level skills and topics, similar to what the children were also learning in their classrooms and what the state tests would assess. But many students were months, even years behind grade level, and may have needed to learn rudimentary skills before being able to grasp more advanced topics. (This problem surprised me because I thought the whole purpose of tutoring was to fill in missing skills and knowledge!) In the data, average students in the middle of the achievement distribution showed the greatest gains from Nashville’s tutoring program. Students at the bottom and top didn’t progress much, or at all. (See the graph below.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“What’s most important is that we figure out what tutoring programs and design features work best for which students,” Kraft said. \u003c/span>\u003c/p>\n\u003cp>\u003cb>Average students in the middle of the achievement distribution gained the most from Nashville’s tutoring program, while students who were the most behind did not catch up much\u003c/b>\u003c/p>\n\u003cfigure id=\"attachment_64629\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"wp-image-64629 size-full\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1.png\" alt=\"\" width=\"780\" height=\"308\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-160x63.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/09/image1-768x303.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Source: Kraft, Matthew A., Danielle Sanderson Edwards, and Marisa Cannata. (2024). The Scaling Dynamics and Causal Effects of a District-Operated Tutoring Program.\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another reason for the disappointing academic gains from tutoring may be related to the individualized attention that many students were also receiving at Nashville’s schools. Tutoring often took place during frequently scheduled periods of “Personalized Learning Time” for students, and even students not selected for tutoring received other instruction during this period, such as small-group work with a teacher or individual services for children with special needs. Another set of students was assigned independent practice work using advanced educational software that adapts to a student’s level. To demonstrate positive results in this study, tutoring would have had to outperform all these other interventions. It’s possible that these other interventions are as powerful as tutoring. Earlier pre-COVID studies of tutoring generally compared the gains against those of students who had nothing more than traditional whole class instruction. That’s a starker comparison. (To be sure, one would still have hoped to see stronger results for tutoring as the Nashville program migrated to outside of school hours; students who received both tutoring and personalized learning time should have meaningfully outperformed students who had only the personalized learning time.)\u003c/span>\u003c/p>\n\u003cp>Other post-pandemic tutoring research has been rosier. A\u003ca href=\"https://url.us.m.mimecastprotect.com/s/1wkbCQWOVBTlJGNpcPhpCGWLaF?domain=educationlab.uchicago.edu\" target=\"_blank\" rel=\"noopener noreferrer\"> smaller study of frequent in-school tutoring in Chicago and Atlanta\u003c/a>, released in March 2024, found giant gains for students in math, enough to totally undo learning losses for the average student. However, those results were achieved by only three-quarters of the roughly 800 students who had been assigned to receive tutoring and actually attended sessions.*\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Kraft argued that schools should not abandon tutoring just because it’s not a silver bullet for academic recovery after COVID. “I worry,” he said, “that we may excuse ourselves from the hard work of iterative experimentation and continuous improvement by saying that we didn’t get the eye-popping results that we had hoped for right out of the gate, and therefore it’s not the solution that we should continue to invest in.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Iteratively is how the business world innovates too. I’m a former business reporter, and this rocky effort to bring tutoring to schools reminds me of how Levi’s introduced custom-made jeans for the masses in the 1990s. These “personal pairs” didn’t cost much more than traditional mass-produced jeans, but it was time consuming for clerks to take measurements, often the jeans didn’t fit and reorders were a hassle. Levi’s \u003c/span>\u003ca href=\"https://mass-customization.blogs.com/mass_customization_open_i/2005/12/repost_analysis.html\">\u003cspan style=\"font-weight: 400\">pulled the plug\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in 2003. Eventually it brought back custom jeans — truly bespoke ones made by a master tailor at \u003c/span>\u003ca href=\"https://www.levistrauss.com/2013/09/23/sewing-secret-master-tailor/\">\u003cspan style=\"font-weight: 400\">$750\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> or more a pop. For the masses? Maybe not. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">I wonder if customized instruction can be accomplished at scale at an affordable price. To really help students who are behind, tutors will need to diagnose each student’s learning gaps, and then develop a customized learning plan for each student. That’s pricey, and maybe impossible to do for millions of students all over the country. \u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-tutoring-research-nashville/\">\u003ci>\u003cspan style=\"font-weight: 400\">tutoring research\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cem>*Correction: An earlier version of this story incorrectly stated how many students were assigned to receive tutoring in the Chicago and Atlanta experiment. Only 784 students were to be tutored out of 1,540 students in the study. About three-quarters of those 784 students received tutoring. The sentence was also revised to clarify which students’ math outcomes drove the results.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Ever since the pandemic shut down schools in the spring of 2020, education researchers have pointed to tutoring as the most promising way to help kids catch up academically. Evidence from \u003c/span>\u003ca href=\"https://www.nber.org/system/files/working_papers/w27476/w27476.pdf\">\u003cspan style=\"font-weight: 400\">almost 100 studies\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was overwhelming for a particular kind of tutoring, called high-dosage tutoring, where students focus on either reading or math three to five times a week.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But until recently, there has been little good evidence for the effectiveness of online tutoring, where students and tutors interact via video, text chat and whiteboards. The virtual version has boomed since the federal government handed schools nearly $190 billion of pandemic recovery aid and specifically encouraged them to spend it on tutoring. Now, some new U.S. studies could offer useful guidance to educators.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Online attendance is a struggle\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In the spring of 2023, almost 1,000 Northern California elementary school children in grades 1 to 4 were randomly assigned to receive online reading tutoring during the school day. Students were supposed to get 20 to 30 sessions each, but only one of five students received that much. \u003c/span>\u003cspan style=\"font-weight: 400\">Eighty percent didn’t\u003c/span>,\u003cspan style=\"font-weight: 400\"> and they didn’t do much better than the 800 students in the comparison group who didn’t get tutoring, according to a \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-942\">\u003cspan style=\"font-weight: 400\">draft paper by researchers from Teachers College\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, Columbia University, which was posted to the Annenberg Institute website at Brown University in April 2024. (\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report is an independent news organization based at Teachers College, Columbia University.\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers have previously found that it is important to schedule in-person tutoring sessions during the school day, when attendance is mandatory. The lesson here with online tutoring is that attendance can be rocky with even during the school day. Often, students end up with a low dose of tutoring instead of the high dose that schools have paid for.\u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, online tutoring can be effective when students participate regularly. In this Northern California study, reading achievement increased substantially, in line with in-person tutoring, for the roughly 200 students who got at least 20 sessions across 10 weeks.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The students who logged in regularly might have been more motivated students in the first place, the researchers warned, indicating that it could be hard to reproduce such large academic benefits for all. During the periods when children were supposed to receive tutoring, researchers observed that some children – often ones who were slightly higher achieving – regularly logged on as scheduled while others didn’t. The difference in student behavior and what the students were doing instead wasn’t explained. Students also seemed to log in more frequently when certain staff members were overseeing the tutoring and less frequently with others. \u003c/span>\u003c/p>\n\u003cp>\u003cb>Small group tutoring doesn’t work as well online\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The large math and reading gains that researchers documented in small groups of students with in-person tutors aren’t always translating to the virtual world. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another study of more than 2,000 elementary school children in Texas tested the difference between one-to-one and two-to-one online tutoring during the 2022-23 school year. These were young, low-income children, in kindergarten through 2nd grade, who were just learning to read. Children who were randomly assigned to get \u003c/span>\u003cspan style=\"font-weight: 400\">one-to-one tutoring four times a \u003c/span>\u003cspan style=\"font-weight: 400\">week\u003c/span>\u003cspan style=\"font-weight: 400\"> posted small gains\u003c/span>\u003cspan style=\"font-weight: 400\"> on one test, but not on another, compared to students in a comparison group who didn’t get tutoring. First graders assigned to one-to-one tutoring gained the equivalent of 30 additional days of school. By contrast, children who had been tutored in pairs were statistically no different in reading than the comparison group of untutored children. A \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-955\">\u003cspan style=\"font-weight: 400\">draft paper about this study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, led by researchers from Stanford University, was posted to the Annenberg website in May 2024. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another small study in Grand Forks, North Dakota confirmed the downside of larger groups with online tutoring. Researchers from Brown University directly compared the math progress of middle school students when they received one-to-one tutoring versus small groups of three students. The study was too small, only 180 students, to get statistically strong results, but the half that were randomly assigned to receive individual tutoring appeared to gain \u003c/span>\u003cspan style=\"font-weight: 400\">eight extra percentile points\u003c/span>\u003cspan style=\"font-weight: 400\">, compared to the students who were assigned to small group tutoring. It was possible that students in the small groups learned a third as much math, the researchers estimated, but these students might have learned much less. A \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-976\">\u003cspan style=\"font-weight: 400\">draft of this paper\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was posted to the Annenberg website in June 2024. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In surveys, tutors said it was hard to keep all three kids engaged online at once. Students were more frequently distracted and off-task, they said. Shy students were less likely to speak up and participate. With one student at a time, tutors said they could move at a faster pace and students “weren’t afraid to ask questions” or “afraid of being wrong.” (On the plus side, tutors said groups of three allowed them to organize group activities or encourage a student to help a peer.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Behavior problems happen in person, too. However, when I have observed in-person small group tutoring in schools, each student is often working independently with the tutor, almost like three simultaneous sessions of one-to-one help. In-person tutors can encourage a student to keep practicing through a silent glance, a smile or hand signal even as they are explaining something to another student. Online, each child’s work and mistakes are publicly exposed on the screen to the whole group. Private asides aren’t as easy; some platforms allow the tutor to text a child privately in a chat window, but that takes time. Tutors have told me that many teens don’t like seeing their face on screen, but turning the camera off makes it harder for them to sense if a student is following along or confused.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Matt Kraft, one of the Brown researchers on the Grand Forks study, suggests that bigger changes need to be made to online tutoring lessons in order to expand from one-to-one to small group tutoring, and he notes that school staff are needed in the classroom to keep students on-task. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">School leaders have until March 2026 to spend the remainder of their $190 billion in pandemic recovery funds, but contracts with tutoring vendors must be signed by September 2024. Both options — in person and virtual — involve tradeoffs. New research evidence is showing that virtual tutoring can work well, especially when motivated students want the tutoring and log in regularly. But many of the students who are significantly behind grade level and in need of extra help may not be so motivated. Keeping the online tutoring small, ideally one-to-one, improves the chances that it will be effective. But that means serving many fewer students, leaving millions of children behind. It’s a tough choice. \u003c/span>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-studies-online-tutoring-troubles-attendance-larger-groups/\">\u003ci>\u003cspan style=\"font-weight: 400\">online tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Ever since the pandemic shut down schools in the spring of 2020, education researchers have pointed to tutoring as the most promising way to help kids catch up academically. Evidence from \u003c/span>\u003ca href=\"https://www.nber.org/system/files/working_papers/w27476/w27476.pdf\">\u003cspan style=\"font-weight: 400\">almost 100 studies\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was overwhelming for a particular kind of tutoring, called high-dosage tutoring, where students focus on either reading or math three to five times a week.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But until recently, there has been little good evidence for the effectiveness of online tutoring, where students and tutors interact via video, text chat and whiteboards. The virtual version has boomed since the federal government handed schools nearly $190 billion of pandemic recovery aid and specifically encouraged them to spend it on tutoring. Now, some new U.S. studies could offer useful guidance to educators.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Online attendance is a struggle\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In the spring of 2023, almost 1,000 Northern California elementary school children in grades 1 to 4 were randomly assigned to receive online reading tutoring during the school day. Students were supposed to get 20 to 30 sessions each, but only one of five students received that much. \u003c/span>\u003cspan style=\"font-weight: 400\">Eighty percent didn’t\u003c/span>,\u003cspan style=\"font-weight: 400\"> and they didn’t do much better than the 800 students in the comparison group who didn’t get tutoring, according to a \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-942\">\u003cspan style=\"font-weight: 400\">draft paper by researchers from Teachers College\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, Columbia University, which was posted to the Annenberg Institute website at Brown University in April 2024. (\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report is an independent news organization based at Teachers College, Columbia University.\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers have previously found that it is important to schedule in-person tutoring sessions during the school day, when attendance is mandatory. The lesson here with online tutoring is that attendance can be rocky with even during the school day. Often, students end up with a low dose of tutoring instead of the high dose that schools have paid for.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, online tutoring can be effective when students participate regularly. In this Northern California study, reading achievement increased substantially, in line with in-person tutoring, for the roughly 200 students who got at least 20 sessions across 10 weeks.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The students who logged in regularly might have been more motivated students in the first place, the researchers warned, indicating that it could be hard to reproduce such large academic benefits for all. During the periods when children were supposed to receive tutoring, researchers observed that some children – often ones who were slightly higher achieving – regularly logged on as scheduled while others didn’t. The difference in student behavior and what the students were doing instead wasn’t explained. Students also seemed to log in more frequently when certain staff members were overseeing the tutoring and less frequently with others. \u003c/span>\u003c/p>\n\u003cp>\u003cb>Small group tutoring doesn’t work as well online\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The large math and reading gains that researchers documented in small groups of students with in-person tutors aren’t always translating to the virtual world. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another study of more than 2,000 elementary school children in Texas tested the difference between one-to-one and two-to-one online tutoring during the 2022-23 school year. These were young, low-income children, in kindergarten through 2nd grade, who were just learning to read. Children who were randomly assigned to get \u003c/span>\u003cspan style=\"font-weight: 400\">one-to-one tutoring four times a \u003c/span>\u003cspan style=\"font-weight: 400\">week\u003c/span>\u003cspan style=\"font-weight: 400\"> posted small gains\u003c/span>\u003cspan style=\"font-weight: 400\"> on one test, but not on another, compared to students in a comparison group who didn’t get tutoring. First graders assigned to one-to-one tutoring gained the equivalent of 30 additional days of school. By contrast, children who had been tutored in pairs were statistically no different in reading than the comparison group of untutored children. A \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-955\">\u003cspan style=\"font-weight: 400\">draft paper about this study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, led by researchers from Stanford University, was posted to the Annenberg website in May 2024. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another small study in Grand Forks, North Dakota confirmed the downside of larger groups with online tutoring. Researchers from Brown University directly compared the math progress of middle school students when they received one-to-one tutoring versus small groups of three students. The study was too small, only 180 students, to get statistically strong results, but the half that were randomly assigned to receive individual tutoring appeared to gain \u003c/span>\u003cspan style=\"font-weight: 400\">eight extra percentile points\u003c/span>\u003cspan style=\"font-weight: 400\">, compared to the students who were assigned to small group tutoring. It was possible that students in the small groups learned a third as much math, the researchers estimated, but these students might have learned much less. A \u003c/span>\u003ca href=\"https://edworkingpapers.com/ai24-976\">\u003cspan style=\"font-weight: 400\">draft of this paper\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was posted to the Annenberg website in June 2024. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In surveys, tutors said it was hard to keep all three kids engaged online at once. Students were more frequently distracted and off-task, they said. Shy students were less likely to speak up and participate. With one student at a time, tutors said they could move at a faster pace and students “weren’t afraid to ask questions” or “afraid of being wrong.” (On the plus side, tutors said groups of three allowed them to organize group activities or encourage a student to help a peer.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Behavior problems happen in person, too. However, when I have observed in-person small group tutoring in schools, each student is often working independently with the tutor, almost like three simultaneous sessions of one-to-one help. In-person tutors can encourage a student to keep practicing through a silent glance, a smile or hand signal even as they are explaining something to another student. Online, each child’s work and mistakes are publicly exposed on the screen to the whole group. Private asides aren’t as easy; some platforms allow the tutor to text a child privately in a chat window, but that takes time. Tutors have told me that many teens don’t like seeing their face on screen, but turning the camera off makes it harder for them to sense if a student is following along or confused.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Matt Kraft, one of the Brown researchers on the Grand Forks study, suggests that bigger changes need to be made to online tutoring lessons in order to expand from one-to-one to small group tutoring, and he notes that school staff are needed in the classroom to keep students on-task. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">School leaders have until March 2026 to spend the remainder of their $190 billion in pandemic recovery funds, but contracts with tutoring vendors must be signed by September 2024. Both options — in person and virtual — involve tradeoffs. New research evidence is showing that virtual tutoring can work well, especially when motivated students want the tutoring and log in regularly. But many of the students who are significantly behind grade level and in need of extra help may not be so motivated. Keeping the online tutoring small, ideally one-to-one, improves the chances that it will be effective. But that means serving many fewer students, leaving millions of children behind. It’s a tough choice. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-studies-online-tutoring-troubles-attendance-larger-groups/\">\u003ci>\u003cspan style=\"font-weight: 400\">online tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003ci>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"slug": "school-vendors-get-paid-no-matter-the-outcome-ome-schools-are-changing-the-contracts",
"title": "School Vendors Get Paid No Matter the Outcome. Some Schools Are Changing the Contracts.",
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"headTitle": "School Vendors Get Paid No Matter the Outcome. Some Schools Are Changing the Contracts. | KQED",
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"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Schools spend \u003c/span>\u003ca href=\"https://nces.ed.gov/fastfacts/display.asp?id=66#:~:text=Question%3A,constant%202021%E2%80%9322%20dollars).\">\u003cspan style=\"font-weight: 400\">billions of dollars a year\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> on products and services, including everything from staplers and textbooks to teacher coaching and training. Does any of it help students learn more? Some educational materials end up \u003c/span>\u003ca href=\"https://hechingerreport.org/new-jersey-school-district-decided-giving-laptops-students-terrible-idea/\">\u003cspan style=\"font-weight: 400\">mothballed in closets\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Much software goes \u003c/span>\u003ca href=\"https://hechingerreport.org/3-lessons-from-data-on-how-students-are-actually-using-educational-apps-and-software-at-school/\">\u003cspan style=\"font-weight: 400\">unused\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Yet central-office bureaucrats frequently renew their contracts with outside vendors regardless of usage or efficacy.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">One idea for smarter education spending is for schools to sign smarter contracts, where part of the payment is contingent upon whether students use the services and learn more. It’s called \u003ca href=\"https://www.kqed.org/mindshift/62445/denver-public-schools-pledged-to-pay-tutoring-vendors-based-on-their-results-did-it-work\">outcomes-based contracting\u003c/a> and is a way of sharing risk between buyer (the school) and seller (the vendor). Outcomes-based contracting is most \u003c/span>\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397909/\">\u003cspan style=\"font-weight: 400\">common in healthcare\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. For example, a health insurer might pay a pharmaceutical company more for a drug if it actually improves people’s health, and less if it doesn’t. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Although the idea is relatively new in education, many schools tried a different version of it – evaluating and paying teachers based on how much their students’ test scores improved – in the 2010s. Teachers didn’t like it, and enthusiasm for these teacher accountability schemes waned. Then, in 2020, \u003c/span>\u003ca href=\"https://cepr.harvard.edu/obci\">\u003cspan style=\"font-weight: 400\">Harvard University’s Center for Education Policy Research\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> announced that it was going to test the feasibility of paying tutoring companies by how much students’ test scores improved. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The initiative was particularly timely in the wake of the pandemic. The federal government would eventually give schools almost $190 billion to reopen and to help students who fell behind when schools were closed. \u003ca href=\"https://www.kqed.org/mindshift/tag/tutoring\">Tutoring became a leading solution for academic recovery\u003c/a>, and schools contracted with outside companies to provide tutors. Many educators worried that billions could be wasted on low-quality tutors who didn’t help anyone. Could schools insist that tutoring companies make part of their payment contingent upon whether student achievement increased? \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The Harvard center recruited a handful of school districts who wanted to try an outcomes-based contract. The researchers and districts shared ideas on how to set performance targets. How much should they expect student achievement to grow from a few months of tutoring? How much of the contract should be guaranteed to the vendor for delivering tutors, and how much should be contingent on student performance? \u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first hurdle was whether tutoring companies would be willing to offer services without knowing exactly how much they would be paid. School districts sent out requests for proposals from online tutoring companies. Tutoring companies bid and the terms varied. One online tutoring company agreed that 40% of a $1.2 million contract with the Duval County Public Schools in Jacksonville, Florida, would be contingent upon student performance. Another online tutoring company signed a contract with Ector County schools in the Odessa, Texas, region that specified that the company had to accept a penalty if kids’ scores declined.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In the middle of the pilot, the outcomes-based contracting initiative \u003c/span>\u003ca href=\"https://www.forbes.com/sites/raymondpierce/2022/03/21/school-district-contracting-can-be-a-lever-for-equity/?sh=56f02344280c\">\u003cspan style=\"font-weight: 400\">moved \u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">from the Harvard center to the \u003c/span>\u003ca href=\"https://obc.southerneducation.org/\">\u003cspan style=\"font-weight: 400\">Southern Education Foundation\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, another nonprofit, and I recently learned how the first group of contracts panned out from Jasmine Walker, a senior manager there. Walker had a first-hand view because until the fall of 2023, she was the director of mathematics in Florida’s Duval County schools, where she oversaw the outcomes-based contract on tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Here are some lessons she learned.\u003c/span>\u003c/p>\n\u003ch2>Planning is time-consuming\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Drawing up an outcomes-based contract requires analyzing years of historical testing data, and documenting how much achievement has typically grown for the students who need tutoring. Then, educators have to decide – based on the \u003ca href=\"https://www.kqed.org/mindshift/62921/four-lessons-from-post-pandemic-tutoring-research\">research evidence for tutoring\u003c/a> – how much they could reasonably hope student achievement to grow after 12 weeks or more. \u003c/span>\u003c/p>\n\u003ch2>Incomplete data was a common problem\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first school district in the pilot group launched its outcomes-based contract in the fall of 2021. In the middle of the pilot, school leadership changed, layoffs hit, and the leaders of the tutoring initiative left the district. With no one in the district’s central office left to track it, there was no data on whether tutoring helped the 1,000 students who received it. Half the students attended 70% of the tutoring sessions. Half didn’t. Test scores for almost two-thirds of the tutored students increased between the start and the end of the tutoring program. But these students also had regular math classes each day and they likely would have posted some achievement gains anyway.\u003c/span>\u003c/p>\n\u003ch2>Delays in settling contracts led to fewer tutored students\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker said two school districts weren’t able to start tutoring children until January 2023, instead of the fall of 2022 as originally planned, because it took so long to iron out contract details and obtain approvals inside the districts. Many schools didn’t want to wait and launched other interventions to help needy students sooner. Understandably, schools didn’t want to yank these students away from those other interventions midyear. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">That delay had big consequences in Duval County. Only 451 students received tutoring instead of a projected 1,200. Fewer students forced Walker to recalculate Duval’s outcomes-based contract. Instead of a $1.2 million contract with $480,000 of it contingent on student outcomes, she downsized it to $464,533 with $162,363 contingent. The tutored students hit 53% of the district’s growth and proficiency goals, leading to a total payout of $393,220 to the tutoring company – far less than the company had originally anticipated. But the average per-student payout of $872 was in line with the original terms of between $600 and $1,000 per student. \u003c/span>\u003c/p>\n\u003ch2>\u003cb>The bottom line is still uncertain\u003c/b>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">What we don’t know from any of these \u003c/span>\u003ca href=\"https://drive.google.com/file/d/1WOlpmB9qgDGtyzxVQCn8c9UWbp65fFTG/view\">\u003cspan style=\"font-weight: 400\">case studies\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> is whether similar students who didn’t receive tutoring also made similar growth and proficiency gains. Maybe it’s all the other things that teachers were doing that made the difference. In Duval County, for example, proficiency rates in math rose from 28% of students to 46% of students. Walker believes that outcomes-based contracting for tutoring was “one lever” of many. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">It’s unclear if outcomes-based contracting is a way for schools to save money. This kind of intensive tutoring – three times a week or more during the school day – is new and the school districts didn’t have previous pre-pandemic tutoring contracts for comparison. But generally, if all the student goals are met, companies stand to earn more in an outcomes-based contract than they would have otherwise, Walker said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“It’s not really about saving money,” said Walker. “What we want is for students to achieve. I don’t care if I spent the whole contract amount if the students actually met the outcomes, because in the past, let’s face it, I was still paying, and they were not achieving outcomes.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The biggest change with outcomes-based contracting, Walker said, was the partnership with the provider. One contractor monitored student attendance during tutoring sessions, called her when attendance slipped and asked her to investigate. Students were given rewards for attending their tutoring sessions and the tutoring company even chipped in to pay for them. “Kids love \u003c/span>\u003ca href=\"https://barcel-usa.com/takis\">\u003cspan style=\"font-weight: 400\">Takis\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” said Walker. \u003c/span>\u003c/p>\n\u003ch2>\u003cb>Advice for schools\u003c/b>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker has two pieces of advice for schools considering outcomes-based contracts. One, she says, is to make the contingency amount at least 40% of the contract. Smaller incentives may not motivate the vendor. For her second outcomes-based contract in Duval County, Walker boosted the contingency amount to half the contract. To earn it, the tutoring company needs the students it is tutoring to hit growth and proficiency goals. That tutoring took place during the current 2023-24 school year. Based on mid-year results, students exceeded expectations, but full-year results are not yet in. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">More importantly, Walker says the biggest lesson she learned was to include teachers, parents and students earlier in the contract negotiation process. She says buy-in from teachers is critical because classroom teachers are actually making sure the tutoring happens. Otherwise, an outcomes-based contract can feel like yet “another thing” that the central office is adding to a teacher’s workload. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker also said she wished she had spent more time educating parents and students on the importance of attending school and their tutoring sessions. ”It’s important that everyone understands the mission,” she said. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Innovation can be rocky, especially at the beginning. Now the Southern Education Foundation is working to expand its outcomes-based contracting initiative nationwide. A second group of four school districts launched its first outcomes-based contracts for tutoring this 2023-24 school year. Walker says that the rate cards and recordkeeping are improving from the first pilot round, which took place during the stress and chaos of the pandemic. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The foundation is also seeking to expand the use of outcomes-based contracts beyond tutoring to education technology and software. Nine districts are slated to launch outcomes-based contracts for ed tech this fall. Her next dream is to design outcomes-based contracts around curriculum and teacher training. I’ll be watching. \u003c/span>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about\u003c/span>\u003c/i> \u003ca href=\"https://hechingerreport.org/proof-points-outcomes-based-contracting/\">\u003ci>\u003cspan style=\"font-weight: 400\">outcomes-based contracting\u003c/span>\u003c/i>\u003c/a> \u003ci>\u003cspan style=\"font-weight: 400\">was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a> \u003ci>\u003cspan style=\"font-weight: 400\">and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"title": "School Vendors Get Paid No Matter the Outcome. Some Schools Are Changing the Contracts. | KQED",
"description": "Schools spend billions of dollars a year on products and services. Some are now tying payment to whether students use the services and how much they learn.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Schools spend \u003c/span>\u003ca href=\"https://nces.ed.gov/fastfacts/display.asp?id=66#:~:text=Question%3A,constant%202021%E2%80%9322%20dollars).\">\u003cspan style=\"font-weight: 400\">billions of dollars a year\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> on products and services, including everything from staplers and textbooks to teacher coaching and training. Does any of it help students learn more? Some educational materials end up \u003c/span>\u003ca href=\"https://hechingerreport.org/new-jersey-school-district-decided-giving-laptops-students-terrible-idea/\">\u003cspan style=\"font-weight: 400\">mothballed in closets\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Much software goes \u003c/span>\u003ca href=\"https://hechingerreport.org/3-lessons-from-data-on-how-students-are-actually-using-educational-apps-and-software-at-school/\">\u003cspan style=\"font-weight: 400\">unused\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Yet central-office bureaucrats frequently renew their contracts with outside vendors regardless of usage or efficacy.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">One idea for smarter education spending is for schools to sign smarter contracts, where part of the payment is contingent upon whether students use the services and learn more. It’s called \u003ca href=\"https://www.kqed.org/mindshift/62445/denver-public-schools-pledged-to-pay-tutoring-vendors-based-on-their-results-did-it-work\">outcomes-based contracting\u003c/a> and is a way of sharing risk between buyer (the school) and seller (the vendor). Outcomes-based contracting is most \u003c/span>\u003ca href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397909/\">\u003cspan style=\"font-weight: 400\">common in healthcare\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. For example, a health insurer might pay a pharmaceutical company more for a drug if it actually improves people’s health, and less if it doesn’t. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Although the idea is relatively new in education, many schools tried a different version of it – evaluating and paying teachers based on how much their students’ test scores improved – in the 2010s. Teachers didn’t like it, and enthusiasm for these teacher accountability schemes waned. Then, in 2020, \u003c/span>\u003ca href=\"https://cepr.harvard.edu/obci\">\u003cspan style=\"font-weight: 400\">Harvard University’s Center for Education Policy Research\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> announced that it was going to test the feasibility of paying tutoring companies by how much students’ test scores improved. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The initiative was particularly timely in the wake of the pandemic. The federal government would eventually give schools almost $190 billion to reopen and to help students who fell behind when schools were closed. \u003ca href=\"https://www.kqed.org/mindshift/tag/tutoring\">Tutoring became a leading solution for academic recovery\u003c/a>, and schools contracted with outside companies to provide tutors. Many educators worried that billions could be wasted on low-quality tutors who didn’t help anyone. Could schools insist that tutoring companies make part of their payment contingent upon whether student achievement increased? \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The Harvard center recruited a handful of school districts who wanted to try an outcomes-based contract. The researchers and districts shared ideas on how to set performance targets. How much should they expect student achievement to grow from a few months of tutoring? How much of the contract should be guaranteed to the vendor for delivering tutors, and how much should be contingent on student performance? \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first hurdle was whether tutoring companies would be willing to offer services without knowing exactly how much they would be paid. School districts sent out requests for proposals from online tutoring companies. Tutoring companies bid and the terms varied. One online tutoring company agreed that 40% of a $1.2 million contract with the Duval County Public Schools in Jacksonville, Florida, would be contingent upon student performance. Another online tutoring company signed a contract with Ector County schools in the Odessa, Texas, region that specified that the company had to accept a penalty if kids’ scores declined.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In the middle of the pilot, the outcomes-based contracting initiative \u003c/span>\u003ca href=\"https://www.forbes.com/sites/raymondpierce/2022/03/21/school-district-contracting-can-be-a-lever-for-equity/?sh=56f02344280c\">\u003cspan style=\"font-weight: 400\">moved \u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">from the Harvard center to the \u003c/span>\u003ca href=\"https://obc.southerneducation.org/\">\u003cspan style=\"font-weight: 400\">Southern Education Foundation\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, another nonprofit, and I recently learned how the first group of contracts panned out from Jasmine Walker, a senior manager there. Walker had a first-hand view because until the fall of 2023, she was the director of mathematics in Florida’s Duval County schools, where she oversaw the outcomes-based contract on tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Here are some lessons she learned.\u003c/span>\u003c/p>\n\u003ch2>Planning is time-consuming\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Drawing up an outcomes-based contract requires analyzing years of historical testing data, and documenting how much achievement has typically grown for the students who need tutoring. Then, educators have to decide – based on the \u003ca href=\"https://www.kqed.org/mindshift/62921/four-lessons-from-post-pandemic-tutoring-research\">research evidence for tutoring\u003c/a> – how much they could reasonably hope student achievement to grow after 12 weeks or more. \u003c/span>\u003c/p>\n\u003ch2>Incomplete data was a common problem\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">The first school district in the pilot group launched its outcomes-based contract in the fall of 2021. In the middle of the pilot, school leadership changed, layoffs hit, and the leaders of the tutoring initiative left the district. With no one in the district’s central office left to track it, there was no data on whether tutoring helped the 1,000 students who received it. Half the students attended 70% of the tutoring sessions. Half didn’t. Test scores for almost two-thirds of the tutored students increased between the start and the end of the tutoring program. But these students also had regular math classes each day and they likely would have posted some achievement gains anyway.\u003c/span>\u003c/p>\n\u003ch2>Delays in settling contracts led to fewer tutored students\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker said two school districts weren’t able to start tutoring children until January 2023, instead of the fall of 2022 as originally planned, because it took so long to iron out contract details and obtain approvals inside the districts. Many schools didn’t want to wait and launched other interventions to help needy students sooner. Understandably, schools didn’t want to yank these students away from those other interventions midyear. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">That delay had big consequences in Duval County. Only 451 students received tutoring instead of a projected 1,200. Fewer students forced Walker to recalculate Duval’s outcomes-based contract. Instead of a $1.2 million contract with $480,000 of it contingent on student outcomes, she downsized it to $464,533 with $162,363 contingent. The tutored students hit 53% of the district’s growth and proficiency goals, leading to a total payout of $393,220 to the tutoring company – far less than the company had originally anticipated. But the average per-student payout of $872 was in line with the original terms of between $600 and $1,000 per student. \u003c/span>\u003c/p>\n\u003ch2>\u003cb>The bottom line is still uncertain\u003c/b>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">What we don’t know from any of these \u003c/span>\u003ca href=\"https://drive.google.com/file/d/1WOlpmB9qgDGtyzxVQCn8c9UWbp65fFTG/view\">\u003cspan style=\"font-weight: 400\">case studies\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> is whether similar students who didn’t receive tutoring also made similar growth and proficiency gains. Maybe it’s all the other things that teachers were doing that made the difference. In Duval County, for example, proficiency rates in math rose from 28% of students to 46% of students. Walker believes that outcomes-based contracting for tutoring was “one lever” of many. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">It’s unclear if outcomes-based contracting is a way for schools to save money. This kind of intensive tutoring – three times a week or more during the school day – is new and the school districts didn’t have previous pre-pandemic tutoring contracts for comparison. But generally, if all the student goals are met, companies stand to earn more in an outcomes-based contract than they would have otherwise, Walker said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“It’s not really about saving money,” said Walker. “What we want is for students to achieve. I don’t care if I spent the whole contract amount if the students actually met the outcomes, because in the past, let’s face it, I was still paying, and they were not achieving outcomes.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The biggest change with outcomes-based contracting, Walker said, was the partnership with the provider. One contractor monitored student attendance during tutoring sessions, called her when attendance slipped and asked her to investigate. Students were given rewards for attending their tutoring sessions and the tutoring company even chipped in to pay for them. “Kids love \u003c/span>\u003ca href=\"https://barcel-usa.com/takis\">\u003cspan style=\"font-weight: 400\">Takis\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” said Walker. \u003c/span>\u003c/p>\n\u003ch2>\u003cb>Advice for schools\u003c/b>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker has two pieces of advice for schools considering outcomes-based contracts. One, she says, is to make the contingency amount at least 40% of the contract. Smaller incentives may not motivate the vendor. For her second outcomes-based contract in Duval County, Walker boosted the contingency amount to half the contract. To earn it, the tutoring company needs the students it is tutoring to hit growth and proficiency goals. That tutoring took place during the current 2023-24 school year. Based on mid-year results, students exceeded expectations, but full-year results are not yet in. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">More importantly, Walker says the biggest lesson she learned was to include teachers, parents and students earlier in the contract negotiation process. She says buy-in from teachers is critical because classroom teachers are actually making sure the tutoring happens. Otherwise, an outcomes-based contract can feel like yet “another thing” that the central office is adding to a teacher’s workload. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walker also said she wished she had spent more time educating parents and students on the importance of attending school and their tutoring sessions. ”It’s important that everyone understands the mission,” she said. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Innovation can be rocky, especially at the beginning. Now the Southern Education Foundation is working to expand its outcomes-based contracting initiative nationwide. A second group of four school districts launched its first outcomes-based contracts for tutoring this 2023-24 school year. Walker says that the rate cards and recordkeeping are improving from the first pilot round, which took place during the stress and chaos of the pandemic. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The foundation is also seeking to expand the use of outcomes-based contracts beyond tutoring to education technology and software. Nine districts are slated to launch outcomes-based contracts for ed tech this fall. Her next dream is to design outcomes-based contracts around curriculum and teacher training. I’ll be watching. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about\u003c/span>\u003c/i> \u003ca href=\"https://hechingerreport.org/proof-points-outcomes-based-contracting/\">\u003ci>\u003cspan style=\"font-weight: 400\">outcomes-based contracting\u003c/span>\u003c/i>\u003c/a> \u003ci>\u003cspan style=\"font-weight: 400\">was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a> \u003ci>\u003cspan style=\"font-weight: 400\">and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"title": "How an AI Talk meter Can Prompt Teachers to Talk Less and Students to Talk More",
"headTitle": "How an AI Talk meter Can Prompt Teachers to Talk Less and Students to Talk More | KQED",
"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Silence may be golden, but when it comes to learning with a tutor, talking is pure gold. It’s audible proof that a student is paying attention and not drifting off, research suggests. More importantly, the more a student articulates his or her reasoning, the easier it is for a tutor to correct misunderstandings or praise a breakthrough. Those are the moments when learning happens.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">One India-based tutoring company, Cuemath, trains its tutors to encourage students to talk more. Its tutors are in India, but many of its clients are American families with elementary school children. The tutoring takes place at home via online video, like a Zoom meeting with a whiteboard, where both tutor and student can work on math problems together. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The company wanted to see if it could boost student participation so it collaborated with researchers at Stanford University to develop a “talk meter,” sort of a Fitbit for the voice, for its tutoring site. Thanks to advances in artificial intelligence, the researchers could separate the audio of the tutors from that of the students and calculate the ratio of tutor-to-student speech.\u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62976\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62976\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1.png\" alt=\"\" width=\"780\" height=\"751\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1-160x154.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1-768x739.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Example of the talk meter shown to Cuemath tutors at the end of the tutoring session. \u003ccite>(Source: Figure 2 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">In initial pilot tests, the talk meter was posted on the tutor’s video screen for the entire one-hour tutoring session, but tutors found that too distracting. The study was revised so that the meter pops up every 20 minutes or three times during the session. When the student is talking less than 25% of the time, the meter goes red, indicating that improvement is needed. When the student is talking more than half the time, the meter turns green. In between, it’s yellow. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">More than 700 tutors and 1,200 of their students were randomly assigned to one of three groups: one where the tutors were shown the talk meter, another where both tutors and students were shown the talk meter, and a third control group which wasn’t shown the talk meter at all for comparison.\u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When just the tutors saw the talk meter, they tended to curtail their explanations and talk much less. But despite their efforts to prod their tutees to talk more, students increased their talking only by 7%. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When students were also shown the talk meter, the dynamic changed. Students increased their talking by 18%. Introverts especially started speaking up, according to interviews with the tutors. \u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62974\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62974\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3.png\" alt=\"\" width=\"780\" height=\"824\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3-160x169.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3-768x811.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Example of the talk meter shown to tutors every 20 minutes during the tutoring session. \u003ccite>(Source: Figure 2 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">The results show how teaching and learning is a two-way street. It’s not just about coaching teachers to be better at their craft. We also need to coach students to be better learners. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“It’s not all the teacher’s responsibility to change student behavior,” said Dorottya Demszky, an assistant professor in education data science at Stanford University and lead author of the study. “I think it’s genuinely, super transformative to think of the student as part of it as well.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The study hasn’t yet been published in a peer-reviewed journal and is currently a draft paper, “\u003c/span>\u003ca href=\"https://www.solaresearch.org/events/lak/lak24/\">\u003cspan style=\"font-weight: 400\">Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” so it may still be revised. It is slated to be presented at the March 2024 annual conference of the \u003c/span>\u003ca href=\"https://www.solaresearch.org/events/lak/lak24/\">\u003cspan style=\"font-weight: 400\">Society of Learning Analytics\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in Kyoto, Japan. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In analyzing the sound files, Demszky noticed that students tended to work on their practice problems with the tutor more silently in both the control and tutor-only talk meter groups. But students started to verbalize their steps aloud once they saw the talk meter. Students were filling more of the silences.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In interviews with the researchers, students said the meter made the tutoring session feel like a game. One student said, “It’s like a competition. So if you talk more, it’s like, I think you’re better at it.” Another noted: “When I see that it’s red, I get a little bit sad and then I keep on talking, then I see it yellow, and then I keep on talking more. Then I see it green and then I’m super happy.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Some students found the meter distracting. “It can get annoying because sometimes when I’m trying to look at a question, it just appears, and then sometimes I can’t get rid of it,” one said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Tutors had mixed reactions, too. For many, the talk meter was a helpful reminder not to be long-winded in their explanations and to ask more probing, open-ended questions. Some tutors said they felt pressured to reach a 50-50 ratio and that they were unnaturally holding back from speaking. One tutor pointed out that it’s not always desirable for a student to talk so much. When you’re introducing a new concept or the student is really lost and struggling, it may be better for the teacher to speak more. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Surprisingly, kids didn’t just fill the air with silly talk to move the gauge. Demszky’s team analyzed the transcripts in a subset of the tutoring sessions and found that students were genuinely talking about their math work and expressing their reasoning. The use of math terms increased by 42%.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Unfortunately, there are several drawbacks to the study design. We don’t know if students’ math achievement improved from the talk meter. The problem was that students of different ages were learning different things in different grades and different countries and there was no single, standardized test to give them all. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another confounding factor is that students who saw the talk meter were also given extra information sessions and worksheets about the benefits of talking more. So we can’t tell from this experiment if the talk meter made the difference or if the information on the value of talking aloud would have been enough to get them to talk more.\u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62975\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62975\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2.png\" alt=\"\" width=\"780\" height=\"194\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2-160x40.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2-768x191.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Excerpts from transcribed tutoring sessions in which students are talking about the talk meter. \u003ccite>(Source: Table 4 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">Demszky is working on developing a talk meter app that can be used in traditional classrooms to encourage more student participation. She hopes teachers will share talk meter results with their students. “I think you could involve the students a little more: ‘It seems like some of you weren’t participating. Or it seems like my questions were very closed ended? How can we work on this together?’”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But she said she’s treading carefully because she is aware that there can be unintended consequences with measurement apps. She wants to give feedback not only on how much students are talking but also on the quality of what they are talking about. And natural language processing still has trouble with English in foreign accents and background noise. Beyond the technological hurdles, there are psychological ones too.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\"> “Not everyone wants a Fitbit or a tool that gives them metrics and feedback,” Demszky acknowledges.\u003c/span>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-how-to-get-teachers-to-talk-less-and-students-more/\">\u003ci>\u003cspan style=\"font-weight: 400\">student participation\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points newsletter\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Silence may be golden, but when it comes to learning with a tutor, talking is pure gold. It’s audible proof that a student is paying attention and not drifting off, research suggests. More importantly, the more a student articulates his or her reasoning, the easier it is for a tutor to correct misunderstandings or praise a breakthrough. Those are the moments when learning happens.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">One India-based tutoring company, Cuemath, trains its tutors to encourage students to talk more. Its tutors are in India, but many of its clients are American families with elementary school children. The tutoring takes place at home via online video, like a Zoom meeting with a whiteboard, where both tutor and student can work on math problems together. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The company wanted to see if it could boost student participation so it collaborated with researchers at Stanford University to develop a “talk meter,” sort of a Fitbit for the voice, for its tutoring site. Thanks to advances in artificial intelligence, the researchers could separate the audio of the tutors from that of the students and calculate the ratio of tutor-to-student speech.\u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62976\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62976\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1.png\" alt=\"\" width=\"780\" height=\"751\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1-160x154.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image1-768x739.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Example of the talk meter shown to Cuemath tutors at the end of the tutoring session. \u003ccite>(Source: Figure 2 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">In initial pilot tests, the talk meter was posted on the tutor’s video screen for the entire one-hour tutoring session, but tutors found that too distracting. The study was revised so that the meter pops up every 20 minutes or three times during the session. When the student is talking less than 25% of the time, the meter goes red, indicating that improvement is needed. When the student is talking more than half the time, the meter turns green. In between, it’s yellow. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">More than 700 tutors and 1,200 of their students were randomly assigned to one of three groups: one where the tutors were shown the talk meter, another where both tutors and students were shown the talk meter, and a third control group which wasn’t shown the talk meter at all for comparison.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When just the tutors saw the talk meter, they tended to curtail their explanations and talk much less. But despite their efforts to prod their tutees to talk more, students increased their talking only by 7%. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When students were also shown the talk meter, the dynamic changed. Students increased their talking by 18%. Introverts especially started speaking up, according to interviews with the tutors. \u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62974\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62974\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3.png\" alt=\"\" width=\"780\" height=\"824\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3-160x169.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image3-768x811.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Example of the talk meter shown to tutors every 20 minutes during the tutoring session. \u003ccite>(Source: Figure 2 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">The results show how teaching and learning is a two-way street. It’s not just about coaching teachers to be better at their craft. We also need to coach students to be better learners. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“It’s not all the teacher’s responsibility to change student behavior,” said Dorottya Demszky, an assistant professor in education data science at Stanford University and lead author of the study. “I think it’s genuinely, super transformative to think of the student as part of it as well.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The study hasn’t yet been published in a peer-reviewed journal and is currently a draft paper, “\u003c/span>\u003ca href=\"https://www.solaresearch.org/events/lak/lak24/\">\u003cspan style=\"font-weight: 400\">Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">,” so it may still be revised. It is slated to be presented at the March 2024 annual conference of the \u003c/span>\u003ca href=\"https://www.solaresearch.org/events/lak/lak24/\">\u003cspan style=\"font-weight: 400\">Society of Learning Analytics\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in Kyoto, Japan. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In analyzing the sound files, Demszky noticed that students tended to work on their practice problems with the tutor more silently in both the control and tutor-only talk meter groups. But students started to verbalize their steps aloud once they saw the talk meter. Students were filling more of the silences.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In interviews with the researchers, students said the meter made the tutoring session feel like a game. One student said, “It’s like a competition. So if you talk more, it’s like, I think you’re better at it.” Another noted: “When I see that it’s red, I get a little bit sad and then I keep on talking, then I see it yellow, and then I keep on talking more. Then I see it green and then I’m super happy.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Some students found the meter distracting. “It can get annoying because sometimes when I’m trying to look at a question, it just appears, and then sometimes I can’t get rid of it,” one said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Tutors had mixed reactions, too. For many, the talk meter was a helpful reminder not to be long-winded in their explanations and to ask more probing, open-ended questions. Some tutors said they felt pressured to reach a 50-50 ratio and that they were unnaturally holding back from speaking. One tutor pointed out that it’s not always desirable for a student to talk so much. When you’re introducing a new concept or the student is really lost and struggling, it may be better for the teacher to speak more. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Surprisingly, kids didn’t just fill the air with silly talk to move the gauge. Demszky’s team analyzed the transcripts in a subset of the tutoring sessions and found that students were genuinely talking about their math work and expressing their reasoning. The use of math terms increased by 42%.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Unfortunately, there are several drawbacks to the study design. We don’t know if students’ math achievement improved from the talk meter. The problem was that students of different ages were learning different things in different grades and different countries and there was no single, standardized test to give them all. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Another confounding factor is that students who saw the talk meter were also given extra information sessions and worksheets about the benefits of talking more. So we can’t tell from this experiment if the talk meter made the difference or if the information on the value of talking aloud would have been enough to get them to talk more.\u003c/span>\u003c/p>\n\u003cfigure id=\"attachment_62975\" class=\"wp-caption aligncenter\" style=\"max-width: 780px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-62975\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2.png\" alt=\"\" width=\"780\" height=\"194\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2.png 780w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2-160x40.png 160w, https://cdn.kqed.org/wp-content/uploads/sites/23/2024/01/image2-768x191.png 768w\" sizes=\"(max-width: 780px) 100vw, 780px\">\u003cfigcaption class=\"wp-caption-text\">Excerpts from transcribed tutoring sessions in which students are talking about the talk meter. \u003ccite>(Source: Table 4 of Demszky et. al. “Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform.”)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003cspan style=\"font-weight: 400\">Demszky is working on developing a talk meter app that can be used in traditional classrooms to encourage more student participation. She hopes teachers will share talk meter results with their students. “I think you could involve the students a little more: ‘It seems like some of you weren’t participating. Or it seems like my questions were very closed ended? How can we work on this together?’”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">But she said she’s treading carefully because she is aware that there can be unintended consequences with measurement apps. She wants to give feedback not only on how much students are talking but also on the quality of what they are talking about. And natural language processing still has trouble with English in foreign accents and background noise. Beyond the technological hurdles, there are psychological ones too.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\"> “Not everyone wants a Fitbit or a tool that gives them metrics and feedback,” Demszky acknowledges.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-how-to-get-teachers-to-talk-less-and-students-more/\">\u003ci>\u003cspan style=\"font-weight: 400\">student participation\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points newsletter\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Research points to intensive daily tutoring as one of the most effective ways to help academically struggling children catch up. There have been a hundred randomized control trials, but one of the most cited is of a tutoring program in Chicago high schools, where ninth and 10th graders learned \u003c/span>\u003ca href=\"https://hechingerreport.org/proof-points-research-evidence-increases-for-intensive-tutoring/\">\u003cspan style=\"font-weight: 400\">an extra year or two\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> of math from a daily dose of tutoring. That’s the kind of result that could offset pandemic learning losses, which have \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/62271/most-students-are-learning-at-typical-pace-again-but-those-who-lost-ground-during-covid-19-arent-catching-up\">\u003cspan style=\"font-weight: 400\">remained devastating\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> and stubborn nearly four years after COVID-19 first erupted, and it’s why the Biden Administration has recommended that schools use their $190 billion in federal recovery funds on tutoring.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">This tutoring evidence, however, was generated before the pandemic, and I was curious about what post-pandemic research says about how tutoring is going now that \u003c/span>\u003ca href=\"https://nces.ed.gov/surveys/spp/results.asp\">\u003cspan style=\"font-weight: 400\">almost 40% \u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">of U.S. public schools say they’re offering \u003c/span>\u003cspan style=\"font-weight: 400\">high-dosage tutoring\u003c/span>\u003cspan style=\"font-weight: 400\"> and \u003c/span>\u003cspan style=\"font-weight: 400\">more than one out of 10 students\u003c/span>\u003cspan style=\"font-weight: 400\"> (11%) are receiving it this 2023-24 school year. Here are four lessons. \u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">1. Timing matters\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Scheduling tutoring time during normal school hours and finding classroom space to conduct it are huge challenges for school leaders. The schedule is already packed with other classes and there aren’t enough empty classrooms. The easiest option is to tack tutoring on to the end of the school day as an after-school program.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">New Mexico did just that and offered high school students free 45-minute online video sessions three times a week in the evenings and weekends. The tutors were from Saga Education, the same tutoring organization that had produced spectacular results in Chicago. \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/tutoring-lessons-new-mexico\">\u003cspan style=\"font-weight: 400\">Only about 500 students signed up\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> out of more than 34,000 who were eligible, according to a June 2023 report from MDRC, an outside research organization. Researchers concluded that after-school tutoring wasn’t a “viable solution for making a sizable and lasting impact.” The state has since switched to scheduling tutoring during the school day.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Attendance is spotty, too. Many after-school tutoring programs around the country report that even students who sign up don’t attend regularly.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">2. There’s a hiring dilemma\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">The job of tutor is now the \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/help-wanted-strategies-recruit-tutoring-workforce-large-scale\">\u003cspan style=\"font-weight: 400\">fastest-growing position\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in the K–12 sector, but \u003c/span>\u003ca href=\"https://ies.ed.gov/schoolsurvey/spp/\">\u003cspan style=\"font-weight: 400\">40% of schools\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> say they’re struggling to hire tutors. That’s not surprising in a red-hot job market, where many companies say it’s tough to find employees. \u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at MDRC in a \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/help-wanted-strategies-recruit-tutoring-workforce-large-scale\">\u003cspan style=\"font-weight: 400\">December 2023 report\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> wrote about different hiring strategies that schools around the country are using. I was flabbergasted to read that New Mexico was paying online tutors $50 an hour to tutor from their homes. Hourly rates of $20 to $30 are fairly common in my reporting. But at least the state was able to offer tutoring to students in remote, rural areas where it would otherwise be impossible to find qualified tutors.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Tutoring companies are a booming business. Schools are using them because they take away the burden of hiring, training and supervising tutors. However, Fulton County, Georgia, which includes Atlanta, found that a tutoring company’s curriculum might have nothing to do with what children are learning in their classrooms and that there’s too little communication between tutors and classroom teachers. Tutors were quitting at high rates and replaced with new ones; students weren’t able to form long-term relationships with their tutors, which researchers say is critical to the success of tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When Fulton County schools hired tutors directly, they were more integrated into the school community. However, schools considered them to be “paraprofessionals” and felt there were more urgent duties than tutoring that they needed to do, from substitute teaching and covering lunch duty to assisting teachers. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chicago took the burden off schools and hired the tutors from the central office. But schools preferred tutors who were from the neighborhood because they could potentially become future teachers. The MDRC report described a sort of catch-22. Schools don’t have the capacity to hire and train tutors, but the tutors that are sent to them from outside vendors or a central office aren’t ideal either. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Oakland, California, experienced many of the obstacles that schools are facing when trying to deliver tutoring at a large scale to thousands of students. The district attempted to give kindergarten through second grade students a half hour of reading tutoring a day. As described by a \u003c/span>\u003ca href=\"https://crpe.org/teachers-and-tutors-together-reimagining-literacy-instruction-in-oakland/\">\u003cspan style=\"font-weight: 400\">December 2023 case study of tutoring\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by researchers at the Center for Reinventing Public Education (CRPE), Oakland struggled with hiring, scheduling and real estate. It hired an outside tutoring organization to help, but it too had trouble recruiting tutors, who complained of low pay. Finding space was difficult. Some tutors had to work in the hallways with children. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The good news is that students who worked with trained tutors made the same gains in reading as those who were given extra reading help by teachers. But the reading gains for students were inconsistent. Some students progressed less in reading than students typically do in a year without tutoring. Others gained almost an additional year’s worth of reading instruction – 88% more.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">3. We need more research on the effectiveness of video tutoring \u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Bringing armies of tutors into school buildings is a logistical and security nightmare. Online tutoring solves that problem. Many vendors have been trying to mimic the model of successful high-dosage tutoring by scheduling video conferencing sessions many times a week with the same well-trained tutor, who is using a good curriculum with step-by-step methods. But it remains a question whether students are as motivated to work as hard with video tutoring as they are in person. Everyone knows that 30 hours of Zoom instruction during school closures was a disaster. It’s unclear whether small, regular doses of video tutoring can be effective. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In 2020 and 2021, there were two studies of online video tutoring. A randomized control trial in Italy produced good results, especially when the students received tutoring four times a week. The tutoring was less than half as potent when the sessions fell to twice a week, according to a \u003c/span>\u003ca href=\"https://publications.iadb.org/en/italy-tutoring-online-program-top-successful-gobal-experience\">\u003cspan style=\"font-weight: 400\">paper published in September 2023\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Another study in \u003c/span>\u003ca href=\"https://scholar.harvard.edu/mkraft/publications/online-tutoring-college-volunteers-experimental-evidence-pilot-program\">\u003cspan style=\"font-weight: 400\">Chicago found zero results\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> from video tutoring. But the tutors were unpaid volunteers and many students missed out on sessions. Both tutors and tutees often failed to show up.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The \u003c/span>\u003ca href=\"https://studentsupportaccelerator.com/briefs/effects-virtual-tutoring-young-readers\">\u003cspan style=\"font-weight: 400\">first randomized controlled trial of a virtual tutoring program for reading\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was conducted during the 2022-23 school year at a large charter school network in Texas. Kindergarten, first and second graders received 20 minutes of video tutoring four times a week, from September through May, with an early reading tutoring organization called OnYourMark. Despite the logistical challenges of setting up little children on computers with headphones, the tutored children ended the year with higher \u003c/span>\u003ca href=\"https://dibels.uoregon.edu/\">\u003cspan style=\"font-weight: 400\">DIBELS scores\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, a measure of reading proficiency for young children, than students who didn’t receive the tutoring. One-to-one video tutoring sometimes produced double the reading gains as video tutoring in pairs, demonstrating a difference between online and in-person tutoring, where larger groups of two and three students can be very effective too. That study was published in October 2023. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Video tutoring hasn’t always been a success. A tutoring program by Intervene K-12, a tutoring company, received high marks from \u003c/span>\u003ca href=\"https://intervenek12.com/wp-content/uploads/2023/12/Intervene-K-12-Tutoring.pdf\">\u003cspan style=\"font-weight: 400\">reviewers at Johns Hopkins University\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, but outside evaluators didn’t find benefits when it was tested on students in Texas. In an unpublished study, the National Student Support Accelerator, a Stanford University organization that is promoting and studying tutoring, found no difference in year-end state test scores between students who received the tutoring and those who received other small group support. Study results can depend greatly on whether the comparison control group is getting nothing or another extra-help alternative.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Matthew Kraft, a Brown University economist who studies tutoring, says there hasn’t been an ideal study that pits online video tutoring directly against in-person tutoring to measure the difference between the two. Existing studies, he said, show some “encouraging signs.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The most important thing for researchers to sort out is how many students a tutor can work with online at once. It’s unclear if groups of three or four, which can be effective in person, are as effective online. “The comments we’re getting from tutors are that it’s significantly different to tutor three students online than it is to tutor three students in person,” Kraft said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In my observations of video tutoring, I have seen several students in groups of three angle their computers away from their faces. I’ve watched tutors call students’ names over and over again, trying to get their attention. To me, students appear far more focused and energetic in one-to-one video tutoring.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">4. Humans and machines could take turns\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">A major downside to every kind of tutoring, both in-person and online, is its cost. The tutoring that worked so well in Chicago can run $4,000 per student. It’s expensive because students are getting over a hundred hours of tutoring and schools need to pay the tutors’ hourly wages. Several researchers are studying how to lower the costs of tutoring by combining human tutoring with online practice work. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In one \u003c/span>\u003ca href=\"https://hechingerreport.org/wp-content/uploads/2023/04/High-Dosage-Tutoring-at-Scale.pdf\">\u003cspan style=\"font-weight: 400\">pre-pandemic study that was described in a March 2023 research brief\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by the University of Chicago’s Education Lab, students worked in groups of four with an in-person tutor. The tutors worked closely with two students at a time while the other two students worked on practice problems independently on ALEKS, a widely used computerized tutoring system developed by academic researchers and owned by McGraw-Hill. Each day the students switched: the ALEKS kids worked with the tutor and the tutored kids turned to ALEKS. The tutor sat with all four students together, monitoring the ALEKS kids to make sure they were doing their math on the computer.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The math gains nearly matched what the researchers had found in a prior study of human tutoring alone, where tutors worked with only two students at a time and required twice as many tutors. The cost was $2,000 per student, much less than the usual $3,000-$4,000 per student price tag of the human tutoring program.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at the University of Chicago have been testing the same model with online video tutoring (instead of in-person) and said they are seeing “encouraging initial indications.” Currently, the research team is studying how many students one tutor can handle at a time, from four to as many as eight students, alternating between humans and ed tech, in order to find out if the sessions are still effective.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at Carnegie Mellon University conducted a similar study of swapping between human tutoring and practicing math on computers. Instead of ALEKS, this pilot study used Mathia, another computerized tutoring system developed by academic researchers and owned by Carnegie Learning. This was not a randomized control trial, but it did take place during the pandemic in 2020-21. Middle school students doubled the amount of math they learned compared to similar students who didn’t receive the tutoring, according to Ken Koedinger, a Carnegie Mellon professor who was part of the research team. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“AI tutors work when students use them,” said Koedinger. “But if students aren’t using them, they obviously don’t work.” The human tutors are better at motivating the students to keep practicing, he said. The computer system gives each student personalized practice work, targeted to their needs, instant feedback and hints.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Technology can also guide the tutors. With one early reading program, called Chapter One, in-person tutors work with young elementary school children in the classroom. Chapter One’s website keeps track of every child’s progress. The tutor’s screen indicates which student to work with next and what skills that student needs to work on. It also suggests phonics lessons and activities that the tutor can use during the session. \u003c/span>\u003ca href=\"https://studentsupportaccelerator.com/briefs/year-two-assessing-effects-high-impact-tutoring-young-readers\">\u003cspan style=\"font-weight: 400\">A two-year randomized control trial, published in December 2023\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, found that the tutored children – many of whom received short five-minute bursts of tutoring at a time – outperformed children who didn’t receive the tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The next frontier in tutoring, of course, is generative AI, such as Chat GPT. Researchers are studying how students learn directly from Khan Academy’s \u003c/span>\u003ca href=\"https://support.khanacademy.org/hc/en-us/community/posts/13992414612877-Introducing-Khanmigo-\">\u003cspan style=\"font-weight: 400\">Khanmigo\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, which gives step-by-step, personalized guidance, like a tutor, on how to solve problems. Other researchers are using this technology to help coach human tutors so that they can better respond to students’ misunderstandings and confusion. I’ll be looking out for these studies and will share the results with you.\u003c/span>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-four-lessons-from-post-pandemic-tutoring-research/\">\u003ci>\u003cspan style=\"font-weight: 400\">video tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the \u003c/span>\u003c/i>\u003ca href=\"http://hechingerreport.us2.list-manage1.com/subscribe?u=66c306eebb323868c3ce353c1&id=d3ee4c3e04\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletter\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Research points to intensive daily tutoring as one of the most effective ways to help academically struggling children catch up. There have been a hundred randomized control trials, but one of the most cited is of a tutoring program in Chicago high schools, where ninth and 10th graders learned \u003c/span>\u003ca href=\"https://hechingerreport.org/proof-points-research-evidence-increases-for-intensive-tutoring/\">\u003cspan style=\"font-weight: 400\">an extra year or two\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> of math from a daily dose of tutoring. That’s the kind of result that could offset pandemic learning losses, which have \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/62271/most-students-are-learning-at-typical-pace-again-but-those-who-lost-ground-during-covid-19-arent-catching-up\">\u003cspan style=\"font-weight: 400\">remained devastating\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> and stubborn nearly four years after COVID-19 first erupted, and it’s why the Biden Administration has recommended that schools use their $190 billion in federal recovery funds on tutoring.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">This tutoring evidence, however, was generated before the pandemic, and I was curious about what post-pandemic research says about how tutoring is going now that \u003c/span>\u003ca href=\"https://nces.ed.gov/surveys/spp/results.asp\">\u003cspan style=\"font-weight: 400\">almost 40% \u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">of U.S. public schools say they’re offering \u003c/span>\u003cspan style=\"font-weight: 400\">high-dosage tutoring\u003c/span>\u003cspan style=\"font-weight: 400\"> and \u003c/span>\u003cspan style=\"font-weight: 400\">more than one out of 10 students\u003c/span>\u003cspan style=\"font-weight: 400\"> (11%) are receiving it this 2023-24 school year. Here are four lessons. \u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">1. Timing matters\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Scheduling tutoring time during normal school hours and finding classroom space to conduct it are huge challenges for school leaders. The schedule is already packed with other classes and there aren’t enough empty classrooms. The easiest option is to tack tutoring on to the end of the school day as an after-school program.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">New Mexico did just that and offered high school students free 45-minute online video sessions three times a week in the evenings and weekends. The tutors were from Saga Education, the same tutoring organization that had produced spectacular results in Chicago. \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/tutoring-lessons-new-mexico\">\u003cspan style=\"font-weight: 400\">Only about 500 students signed up\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> out of more than 34,000 who were eligible, according to a June 2023 report from MDRC, an outside research organization. Researchers concluded that after-school tutoring wasn’t a “viable solution for making a sizable and lasting impact.” The state has since switched to scheduling tutoring during the school day.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Attendance is spotty, too. Many after-school tutoring programs around the country report that even students who sign up don’t attend regularly.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">2. There’s a hiring dilemma\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">The job of tutor is now the \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/help-wanted-strategies-recruit-tutoring-workforce-large-scale\">\u003cspan style=\"font-weight: 400\">fastest-growing position\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> in the K–12 sector, but \u003c/span>\u003ca href=\"https://ies.ed.gov/schoolsurvey/spp/\">\u003cspan style=\"font-weight: 400\">40% of schools\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> say they’re struggling to hire tutors. That’s not surprising in a red-hot job market, where many companies say it’s tough to find employees. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at MDRC in a \u003c/span>\u003ca href=\"https://www.mdrc.org/work/publications/help-wanted-strategies-recruit-tutoring-workforce-large-scale\">\u003cspan style=\"font-weight: 400\">December 2023 report\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> wrote about different hiring strategies that schools around the country are using. I was flabbergasted to read that New Mexico was paying online tutors $50 an hour to tutor from their homes. Hourly rates of $20 to $30 are fairly common in my reporting. But at least the state was able to offer tutoring to students in remote, rural areas where it would otherwise be impossible to find qualified tutors.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Tutoring companies are a booming business. Schools are using them because they take away the burden of hiring, training and supervising tutors. However, Fulton County, Georgia, which includes Atlanta, found that a tutoring company’s curriculum might have nothing to do with what children are learning in their classrooms and that there’s too little communication between tutors and classroom teachers. Tutors were quitting at high rates and replaced with new ones; students weren’t able to form long-term relationships with their tutors, which researchers say is critical to the success of tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When Fulton County schools hired tutors directly, they were more integrated into the school community. However, schools considered them to be “paraprofessionals” and felt there were more urgent duties than tutoring that they needed to do, from substitute teaching and covering lunch duty to assisting teachers. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chicago took the burden off schools and hired the tutors from the central office. But schools preferred tutors who were from the neighborhood because they could potentially become future teachers. The MDRC report described a sort of catch-22. Schools don’t have the capacity to hire and train tutors, but the tutors that are sent to them from outside vendors or a central office aren’t ideal either. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Oakland, California, experienced many of the obstacles that schools are facing when trying to deliver tutoring at a large scale to thousands of students. The district attempted to give kindergarten through second grade students a half hour of reading tutoring a day. As described by a \u003c/span>\u003ca href=\"https://crpe.org/teachers-and-tutors-together-reimagining-literacy-instruction-in-oakland/\">\u003cspan style=\"font-weight: 400\">December 2023 case study of tutoring\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by researchers at the Center for Reinventing Public Education (CRPE), Oakland struggled with hiring, scheduling and real estate. It hired an outside tutoring organization to help, but it too had trouble recruiting tutors, who complained of low pay. Finding space was difficult. Some tutors had to work in the hallways with children. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The good news is that students who worked with trained tutors made the same gains in reading as those who were given extra reading help by teachers. But the reading gains for students were inconsistent. Some students progressed less in reading than students typically do in a year without tutoring. Others gained almost an additional year’s worth of reading instruction – 88% more.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">3. We need more research on the effectiveness of video tutoring \u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">Bringing armies of tutors into school buildings is a logistical and security nightmare. Online tutoring solves that problem. Many vendors have been trying to mimic the model of successful high-dosage tutoring by scheduling video conferencing sessions many times a week with the same well-trained tutor, who is using a good curriculum with step-by-step methods. But it remains a question whether students are as motivated to work as hard with video tutoring as they are in person. Everyone knows that 30 hours of Zoom instruction during school closures was a disaster. It’s unclear whether small, regular doses of video tutoring can be effective. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In 2020 and 2021, there were two studies of online video tutoring. A randomized control trial in Italy produced good results, especially when the students received tutoring four times a week. The tutoring was less than half as potent when the sessions fell to twice a week, according to a \u003c/span>\u003ca href=\"https://publications.iadb.org/en/italy-tutoring-online-program-top-successful-gobal-experience\">\u003cspan style=\"font-weight: 400\">paper published in September 2023\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. Another study in \u003c/span>\u003ca href=\"https://scholar.harvard.edu/mkraft/publications/online-tutoring-college-volunteers-experimental-evidence-pilot-program\">\u003cspan style=\"font-weight: 400\">Chicago found zero results\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> from video tutoring. But the tutors were unpaid volunteers and many students missed out on sessions. Both tutors and tutees often failed to show up.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The \u003c/span>\u003ca href=\"https://studentsupportaccelerator.com/briefs/effects-virtual-tutoring-young-readers\">\u003cspan style=\"font-weight: 400\">first randomized controlled trial of a virtual tutoring program for reading\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> was conducted during the 2022-23 school year at a large charter school network in Texas. Kindergarten, first and second graders received 20 minutes of video tutoring four times a week, from September through May, with an early reading tutoring organization called OnYourMark. Despite the logistical challenges of setting up little children on computers with headphones, the tutored children ended the year with higher \u003c/span>\u003ca href=\"https://dibels.uoregon.edu/\">\u003cspan style=\"font-weight: 400\">DIBELS scores\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, a measure of reading proficiency for young children, than students who didn’t receive the tutoring. One-to-one video tutoring sometimes produced double the reading gains as video tutoring in pairs, demonstrating a difference between online and in-person tutoring, where larger groups of two and three students can be very effective too. That study was published in October 2023. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Video tutoring hasn’t always been a success. A tutoring program by Intervene K-12, a tutoring company, received high marks from \u003c/span>\u003ca href=\"https://intervenek12.com/wp-content/uploads/2023/12/Intervene-K-12-Tutoring.pdf\">\u003cspan style=\"font-weight: 400\">reviewers at Johns Hopkins University\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, but outside evaluators didn’t find benefits when it was tested on students in Texas. In an unpublished study, the National Student Support Accelerator, a Stanford University organization that is promoting and studying tutoring, found no difference in year-end state test scores between students who received the tutoring and those who received other small group support. Study results can depend greatly on whether the comparison control group is getting nothing or another extra-help alternative.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Matthew Kraft, a Brown University economist who studies tutoring, says there hasn’t been an ideal study that pits online video tutoring directly against in-person tutoring to measure the difference between the two. Existing studies, he said, show some “encouraging signs.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The most important thing for researchers to sort out is how many students a tutor can work with online at once. It’s unclear if groups of three or four, which can be effective in person, are as effective online. “The comments we’re getting from tutors are that it’s significantly different to tutor three students online than it is to tutor three students in person,” Kraft said.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In my observations of video tutoring, I have seen several students in groups of three angle their computers away from their faces. I’ve watched tutors call students’ names over and over again, trying to get their attention. To me, students appear far more focused and energetic in one-to-one video tutoring.\u003c/span>\u003c/p>\n\u003ch2>\u003cspan style=\"font-weight: 400\">4. Humans and machines could take turns\u003c/span>\u003c/h2>\n\u003cp>\u003cspan style=\"font-weight: 400\">A major downside to every kind of tutoring, both in-person and online, is its cost. The tutoring that worked so well in Chicago can run $4,000 per student. It’s expensive because students are getting over a hundred hours of tutoring and schools need to pay the tutors’ hourly wages. Several researchers are studying how to lower the costs of tutoring by combining human tutoring with online practice work. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In one \u003c/span>\u003ca href=\"https://hechingerreport.org/wp-content/uploads/2023/04/High-Dosage-Tutoring-at-Scale.pdf\">\u003cspan style=\"font-weight: 400\">pre-pandemic study that was described in a March 2023 research brief\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by the University of Chicago’s Education Lab, students worked in groups of four with an in-person tutor. The tutors worked closely with two students at a time while the other two students worked on practice problems independently on ALEKS, a widely used computerized tutoring system developed by academic researchers and owned by McGraw-Hill. Each day the students switched: the ALEKS kids worked with the tutor and the tutored kids turned to ALEKS. The tutor sat with all four students together, monitoring the ALEKS kids to make sure they were doing their math on the computer.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The math gains nearly matched what the researchers had found in a prior study of human tutoring alone, where tutors worked with only two students at a time and required twice as many tutors. The cost was $2,000 per student, much less than the usual $3,000-$4,000 per student price tag of the human tutoring program.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at the University of Chicago have been testing the same model with online video tutoring (instead of in-person) and said they are seeing “encouraging initial indications.” Currently, the research team is studying how many students one tutor can handle at a time, from four to as many as eight students, alternating between humans and ed tech, in order to find out if the sessions are still effective.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers at Carnegie Mellon University conducted a similar study of swapping between human tutoring and practicing math on computers. Instead of ALEKS, this pilot study used Mathia, another computerized tutoring system developed by academic researchers and owned by Carnegie Learning. This was not a randomized control trial, but it did take place during the pandemic in 2020-21. Middle school students doubled the amount of math they learned compared to similar students who didn’t receive the tutoring, according to Ken Koedinger, a Carnegie Mellon professor who was part of the research team. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“AI tutors work when students use them,” said Koedinger. “But if students aren’t using them, they obviously don’t work.” The human tutors are better at motivating the students to keep practicing, he said. The computer system gives each student personalized practice work, targeted to their needs, instant feedback and hints.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Technology can also guide the tutors. With one early reading program, called Chapter One, in-person tutors work with young elementary school children in the classroom. Chapter One’s website keeps track of every child’s progress. The tutor’s screen indicates which student to work with next and what skills that student needs to work on. It also suggests phonics lessons and activities that the tutor can use during the session. \u003c/span>\u003ca href=\"https://studentsupportaccelerator.com/briefs/year-two-assessing-effects-high-impact-tutoring-young-readers\">\u003cspan style=\"font-weight: 400\">A two-year randomized control trial, published in December 2023\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, found that the tutored children – many of whom received short five-minute bursts of tutoring at a time – outperformed children who didn’t receive the tutoring. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The next frontier in tutoring, of course, is generative AI, such as Chat GPT. Researchers are studying how students learn directly from Khan Academy’s \u003c/span>\u003ca href=\"https://support.khanacademy.org/hc/en-us/community/posts/13992414612877-Introducing-Khanmigo-\">\u003cspan style=\"font-weight: 400\">Khanmigo\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, which gives step-by-step, personalized guidance, like a tutor, on how to solve problems. Other researchers are using this technology to help coach human tutors so that they can better respond to students’ misunderstandings and confusion. I’ll be looking out for these studies and will share the results with you.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-four-lessons-from-post-pandemic-tutoring-research/\">\u003ci>\u003cspan style=\"font-weight: 400\">video tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the \u003c/span>\u003c/i>\u003ca href=\"http://hechingerreport.us2.list-manage1.com/subscribe?u=66c306eebb323868c3ce353c1&id=d3ee4c3e04\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletter\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"title": "Schools keep buying online drop-in tutoring. Research doesn’t support it.",
"headTitle": "Schools keep buying online drop-in tutoring. Research doesn’t support it. | KQED",
"content": "\u003cp>\u003cspan style=\"font-weight: 400\">Ever since schools reopened and resumed in-person instruction, districts have been trying to help students catch up from pandemic learning losses. The Biden Administration has urged schools to use tutoring. Many schools have purchased an online version that gives students 24/7 access to tutors. Typically, communication is through text chat, similar to communicating with customer service on a website. Students never see their tutors or hear their voices. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers estimate that \u003c/span>\u003ca href=\"https://www.edworkingpapers.com/sites/default/files/ai22-654.pdf\">\u003cspan style=\"font-weight: 400\">billions\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> have been spent on these online tutoring services, but so far, there’s no good evidence that they are helping many students catch up. And many students need extra help. According to the most recent test scores from spring 2023, \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/62271/most-students-are-learning-at-typical-pace-again-but-those-who-lost-ground-during-covid-19-arent-catching-up\">\u003cspan style=\"font-weight: 400\">50% more students are below grade level than before the pandemic\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">; even higher achieving students remain months behind where they should be.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Low uptake\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The main problem is that on-demand tutoring relies on students to seek extra help. Very few do. Some school systems have reported \u003c/span>\u003ca href=\"https://wtop.com/fairfax-county/2022/11/most-fairfax-co-students-didnt-use-free-tutoring-service-la\">\u003cspan style=\"font-weight: 400\">usage rates below 2%.\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> A 2022 \u003c/span>\u003ca href=\"https://www.edworkingpapers.com/ai22-654\">\u003cspan style=\"font-weight: 400\">study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by researchers at Brown University of an effort to boost usage among 7,000 students at a California charter school network found that students who needed the most help were the least likely to try online tutoring and only a very small percentage of students used it regularly. Opt-in tutoring could “exacerbate inequalities rather than reduce them,” warned a \u003c/span>\u003ca href=\"https://www.edresearchforaction.org/research-briefs/accelerating-student-academic-recovery/\">\u003cspan style=\"font-weight: 400\">September 2023 research brief\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by Brown University’s Annenberg Center, Results for America, a nonprofit that promotes evidence-backed policies, the American Institutes for Research and NWEA, an assessment firm.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In January 2023, an independent research firm Mathematica released a \u003c/span>\u003ca href=\"https://www.mathematica.org/publications/impacts-of-upchieve-on-demand-tutoring-on-students-math-knowledge-and-perceptions\">\u003cspan style=\"font-weight: 400\">more positive report on students’ math gains with an online tutoring service called UPchieve\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, which uses volunteers as tutors. It seemed to suggest that high school students could make extraordinary math progress from online homework help. \u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve is a foundation-funded nonprofit with a slightly different model. Instead of schools buying the tutoring service from a commercial vendor, UPchieve makes its tutors freely available to any student in grades eight to 12 living in a low-income zip code or attending a low-income high school. Behind the scenes, foundations cover the cost to deliver the tutoring, about $5 per student served. (\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">Those foundations include the Bill & Melinda Gates and the Overdeck Family foundations, which are also among the many funders of The Hechinger Report.\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve posted findings from the study in large font on its website: “\u003c/span>\u003ca href=\"https://upchieve.org/impact\">\u003cspan style=\"font-weight: 400\">Using UPchieve 9 times caused student test scores to meaningfully increase” by “9 percentile rank points\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">.” If true, that would be equivalent to doubling the amount of math that a typical high school student learns. That would mean that students learned an extra 14 weeks worth of math from just a few extra hours of instruction. Not even the most highly regarded and expensive tutoring programs using professional tutors who are following clear lesson plans achieve this.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The \u003c/span>\u003cspan style=\"font-weight: 400\">study\u003c/span>\u003cspan style=\"font-weight: 400\"> garnered a lot of attention on social media and flattering media coverage “\u003c/span>\u003ca href=\"https://www.the74million.org/article/how-a-free-24-7-tutoring-model-is-disrupting-learning-loss-for-low-income-kids/\">\u003cspan style=\"font-weight: 400\">for disrupting learning loss in low-income kids\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">.” But how real was this progress? \u003c/span>\u003c/p>\n\u003cp>\u003cb>Gift card incentives\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">After I read the study, which was also commissioned by the Gates foundation, I immediately saw that UPchieve’s excerpts were taken out of context. This was not a straightforward randomized controlled trial, comparing what happens to students who were offered this tutoring with students who were not. Instead, it was a trial of the power of cash incentives and email reminders. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">For the experiment, Mathematica researchers had recruited high schoolers who were already logging into the UPchieve tutoring service. These were no ordinary ninth and 10th graders. They were motivated to seek extra help, resourceful enough to find this tutoring website on their own (it was not promoted through their schools) and liked math enough to take extra tests to participate in the study. One group was given extra payments of $5 a week for doing at least 10 minutes of math tutoring on UPchieve, and sent weekly email reminders. The other group wasn’t. Students in both groups received $100 for participating in the study.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The gift cards increased usage by 1.6 hours or five to six more sessions over the course of 14 weeks. These incentivized students “met” with a tutor for a total of nine sessions on average; the other students averaged fewer than four sessions. (As an aside, it’s unusual that cash incentives would double usage. Slicing the results another way, only 22% of the students in the gift-card group used UPchieve more than 10 times compared with 14% in the other group. That’s more typical.) \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">At the end of 14 weeks, students took the Renaissance Star math test, an assessment taken by millions of students across the nation. But the researchers did not report those test scores. That’s because they were unlucky in their random assignment of students. By chance, comparatively weaker math students kept getting assigned to receive cash incentives. It wasn’t an apples-to-apples comparison between the two groups, a problem that can happen in a small randomized controlled trial. To compensate, the researchers statistically adjusted the final math scores to account for differences in baseline math achievement. It’s those statistically adjusted scores that showed such huge math gains for the students who had received the cash incentives and used the tutoring service more.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, the huge 9 percentile point improvement in math was \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">not\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> statistically significant. There were so few students in the study – 89 in total – that the results could have been a fluke. You’d need a much larger sample size to be confident.\u003c/span>\u003c/p>\n\u003cp>\u003cb>A caution from the researcher\u003c/b>\u003cspan style=\"font-weight: 400\"> \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When I interviewed one of the Mathematica researchers, he was cautious about UPchieve and on-demand tutoring in general. “This is an approach to tutoring that has promise for improving students’ math knowledge for a specific subset of students: those who are likely to proactively take up an on-demand tutoring service,” said Greg Chojnacki, a co-author of the UPchieve study. “The study really doesn’t speak to how promising this model is for students who may face additional barriers to taking up tutoring.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chojnacki has been studying different versions of tutoring and he says that this on-demand version might prove to be beneficial for the “kid who may be jumping up for extra help the first chance they get,” while other children might first need to “build a trusting relationship” with a tutor they can see and talk to before they engage in learning. With UPchieve and other on-demand models, students are assigned to a different tutor at each session and don’t get a chance to build a relationship. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chojnacki also walked back the numerical results in our interview. He told me not to “put too much stock” in the exact amount of math that students learned. He said he’s confident that self-motivated students who use the tutoring service more often learned more math, but it could be “anywhere above zero” and not nearly as high as 9 percentile points – an extra three and a half months worth of math instruction.\u003c/span>\u003c/p>\n\u003cp>\u003cb>UPchieve defends “magical” results\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve’s founder, Aly Murray, told me that the Mathematica study results initially surprised her, too. “I agree they almost seem magical,” she said by email. While acknowledging that a larger study is needed to confirm the results, she said she believes that online tutoring without audio and video can “lead to greater learning” than in-person tutoring “when done right.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I personally believe that tutoring is most effective when the student is choosing to be there and has an acute need that they want to address (two things that are both uniquely true of on-demand tutoring),” she wrote. “Students have told us how helpful it is to get timely feedback and support in the exact moment that they get confused (which is often late at night in their homes while working on their homework). So in general, I believe that on-demand tutoring is more impactful than traditional high-dosage tutoring models on a \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">per tutoring session\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> or \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">per hour of tutoring\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> basis. This could be part of why we were able to achieve such outsized results despite the low number of sessions.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Murray acknowledged that low usage remains a problem. At UPchieve’s partner schools, only 5% of students logged in at least once during the 2022-23 year, she told me. At some schools, usage rates fell below 1%. Her goal is to increase usage rates at partner schools to 36%. (Any low-income student in grades eight to 12 can use the tutoring service at no cost and their schools don’t pay UPchieve for the tutoring either, but some “partner” schools pay UPchieve to promote and monitor usage.) \u003c/span>\u003c/p>\n\u003cp>\u003cb>The downside to homework help\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Helping students who are stuck on a homework assignment is certainly nice for motivated kids who love school, but relying on homework questions is a poor way to catch up students who are the most behind, according to many tutoring experts. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I have a hard time believing that students know enough about what they don’t know,” said Susanna Loeb, a Stanford University economist who founded the National Student Support Accelerator, which aims to bring evidence-based tutoring to more students. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">For students who are behind grade level, homework questions often don’t address their gaps in basic math foundations. “Maybe underneath, they’re struggling with percentages, but they’re bringing an algebra question,” said Loeb. “If you just bring the work of the classroom to the tutor, it doesn’t help students very much.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Pre-pandemic research of once-a-week after-school homework help also produced disappointing results for struggling students. Effective tutoring starts with an assessment of students’ gaps, Loeb said, followed by consistent, structured lessons.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Schools struggle to offer tutors for all students\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">With so little evidence, why are schools buying on-demand online tutoring? Pittsburgh superintendent Wayne Walters said he was unable to arrange for in-person tutoring in all of his 54 schools and wanted to give each of his 19,000 students access to something. He \u003c/span>\u003ca href=\"https://www.tutor.com/press/press-releases-2023/20230807\">\u003cspan style=\"font-weight: 400\">signed a contract with Tutor.com\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> for unlimited online text-chat tutoring in 2023-24. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I’m going forward with it because it’s available,” Walters said. “If I don’t have something to provide, or even offer, then that limits opportunity and access. If there’s no access, then I can’t even push the needle to address the most marginalized and the most vulnerable.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walters hopes to make on-demand tutoring “sexy” and appealing to high schoolers accustomed to texting. But online tutoring is not the same as spontaneous texting between friends. One-minute delays in tutors’ replies to questions can test students’ patience. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">On-demand tutoring can appear to be an economical option. Pittsburgh is able to offer this kind of tutoring, which includes college admissions test prep for high schoolers, to all 19,000 of its students for $600,000. Providing 400 students with a high-dosage tutoring program – the kind that researchers recommend – could cost $1.5 million. There are thousands of Pittsburgh students who are significantly behind grade level. It doesn’t seem fair to deliver high-quality in-person tutoring to only a lucky few.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, once you factor in actual usage, the economics of on-demand tutoring looks less impressive. In \u003c/span>\u003ca href=\"https://go.boarddocs.com/vsba/fairfax/Board.nsf/files/CKQJTV4EC65A/%24file/Tutor.com%20write%20up%20%20mf.pdf\">\u003cspan style=\"font-weight: 400\">Fairfax County, Va., for example, only 1.6% of students used Tutor.com\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. If Pittsburgh doesn’t surpass that rate, then no more than 300 of its students will be served.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">There are no villains here. School leaders are trying to do the best they can and be fair to everyone. Hopes are raised when research suggests that online on-demand tutoring can work if they can succeed in marketing to students. But they should be skeptical of studies that promise easy solutions before investing precious resources. That money could be better spent on small-group tutoring that \u003c/span>\u003ca href=\"https://www.nber.org/papers/w27476\">\u003cspan style=\"font-weight: 400\">dozens of studies show is more effective\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> for students.\u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-schools-keep-buying-online-drop-in-tutoring-the-research-doesnt-support-it/\">\u003ci>\u003cspan style=\"font-weight: 400\">drop-in tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/\">\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp> \u003c/p>\n\n",
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"excerpt": "Schools have spent billions on online tutoring services to address pandemic learning loss. So far, there’s no good evidence that they are helping many students catch up.",
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"title": "Schools keep buying online drop-in tutoring. Research doesn’t support it. | KQED",
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"headline": "Schools keep buying online drop-in tutoring. Research doesn’t support it.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cspan style=\"font-weight: 400\">Ever since schools reopened and resumed in-person instruction, districts have been trying to help students catch up from pandemic learning losses. The Biden Administration has urged schools to use tutoring. Many schools have purchased an online version that gives students 24/7 access to tutors. Typically, communication is through text chat, similar to communicating with customer service on a website. Students never see their tutors or hear their voices. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Researchers estimate that \u003c/span>\u003ca href=\"https://www.edworkingpapers.com/sites/default/files/ai22-654.pdf\">\u003cspan style=\"font-weight: 400\">billions\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> have been spent on these online tutoring services, but so far, there’s no good evidence that they are helping many students catch up. And many students need extra help. According to the most recent test scores from spring 2023, \u003c/span>\u003ca href=\"https://www.kqed.org/mindshift/62271/most-students-are-learning-at-typical-pace-again-but-those-who-lost-ground-during-covid-19-arent-catching-up\">\u003cspan style=\"font-weight: 400\">50% more students are below grade level than before the pandemic\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">; even higher achieving students remain months behind where they should be.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Low uptake\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The main problem is that on-demand tutoring relies on students to seek extra help. Very few do. Some school systems have reported \u003c/span>\u003ca href=\"https://wtop.com/fairfax-county/2022/11/most-fairfax-co-students-didnt-use-free-tutoring-service-la\">\u003cspan style=\"font-weight: 400\">usage rates below 2%.\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> A 2022 \u003c/span>\u003ca href=\"https://www.edworkingpapers.com/ai22-654\">\u003cspan style=\"font-weight: 400\">study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by researchers at Brown University of an effort to boost usage among 7,000 students at a California charter school network found that students who needed the most help were the least likely to try online tutoring and only a very small percentage of students used it regularly. Opt-in tutoring could “exacerbate inequalities rather than reduce them,” warned a \u003c/span>\u003ca href=\"https://www.edresearchforaction.org/research-briefs/accelerating-student-academic-recovery/\">\u003cspan style=\"font-weight: 400\">September 2023 research brief\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> by Brown University’s Annenberg Center, Results for America, a nonprofit that promotes evidence-backed policies, the American Institutes for Research and NWEA, an assessment firm.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">In January 2023, an independent research firm Mathematica released a \u003c/span>\u003ca href=\"https://www.mathematica.org/publications/impacts-of-upchieve-on-demand-tutoring-on-students-math-knowledge-and-perceptions\">\u003cspan style=\"font-weight: 400\">more positive report on students’ math gains with an online tutoring service called UPchieve\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">, which uses volunteers as tutors. It seemed to suggest that high school students could make extraordinary math progress from online homework help. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve is a foundation-funded nonprofit with a slightly different model. Instead of schools buying the tutoring service from a commercial vendor, UPchieve makes its tutors freely available to any student in grades eight to 12 living in a low-income zip code or attending a low-income high school. Behind the scenes, foundations cover the cost to deliver the tutoring, about $5 per student served. (\u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">Those foundations include the Bill & Melinda Gates and the Overdeck Family foundations, which are also among the many funders of The Hechinger Report.\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\">)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve posted findings from the study in large font on its website: “\u003c/span>\u003ca href=\"https://upchieve.org/impact\">\u003cspan style=\"font-weight: 400\">Using UPchieve 9 times caused student test scores to meaningfully increase” by “9 percentile rank points\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">.” If true, that would be equivalent to doubling the amount of math that a typical high school student learns. That would mean that students learned an extra 14 weeks worth of math from just a few extra hours of instruction. Not even the most highly regarded and expensive tutoring programs using professional tutors who are following clear lesson plans achieve this.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The \u003c/span>\u003cspan style=\"font-weight: 400\">study\u003c/span>\u003cspan style=\"font-weight: 400\"> garnered a lot of attention on social media and flattering media coverage “\u003c/span>\u003ca href=\"https://www.the74million.org/article/how-a-free-24-7-tutoring-model-is-disrupting-learning-loss-for-low-income-kids/\">\u003cspan style=\"font-weight: 400\">for disrupting learning loss in low-income kids\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">.” But how real was this progress? \u003c/span>\u003c/p>\n\u003cp>\u003cb>Gift card incentives\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">After I read the study, which was also commissioned by the Gates foundation, I immediately saw that UPchieve’s excerpts were taken out of context. This was not a straightforward randomized controlled trial, comparing what happens to students who were offered this tutoring with students who were not. Instead, it was a trial of the power of cash incentives and email reminders. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">For the experiment, Mathematica researchers had recruited high schoolers who were already logging into the UPchieve tutoring service. These were no ordinary ninth and 10th graders. They were motivated to seek extra help, resourceful enough to find this tutoring website on their own (it was not promoted through their schools) and liked math enough to take extra tests to participate in the study. One group was given extra payments of $5 a week for doing at least 10 minutes of math tutoring on UPchieve, and sent weekly email reminders. The other group wasn’t. Students in both groups received $100 for participating in the study.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">The gift cards increased usage by 1.6 hours or five to six more sessions over the course of 14 weeks. These incentivized students “met” with a tutor for a total of nine sessions on average; the other students averaged fewer than four sessions. (As an aside, it’s unusual that cash incentives would double usage. Slicing the results another way, only 22% of the students in the gift-card group used UPchieve more than 10 times compared with 14% in the other group. That’s more typical.) \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">At the end of 14 weeks, students took the Renaissance Star math test, an assessment taken by millions of students across the nation. But the researchers did not report those test scores. That’s because they were unlucky in their random assignment of students. By chance, comparatively weaker math students kept getting assigned to receive cash incentives. It wasn’t an apples-to-apples comparison between the two groups, a problem that can happen in a small randomized controlled trial. To compensate, the researchers statistically adjusted the final math scores to account for differences in baseline math achievement. It’s those statistically adjusted scores that showed such huge math gains for the students who had received the cash incentives and used the tutoring service more.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, the huge 9 percentile point improvement in math was \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">not\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> statistically significant. There were so few students in the study – 89 in total – that the results could have been a fluke. You’d need a much larger sample size to be confident.\u003c/span>\u003c/p>\n\u003cp>\u003cb>A caution from the researcher\u003c/b>\u003cspan style=\"font-weight: 400\"> \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">When I interviewed one of the Mathematica researchers, he was cautious about UPchieve and on-demand tutoring in general. “This is an approach to tutoring that has promise for improving students’ math knowledge for a specific subset of students: those who are likely to proactively take up an on-demand tutoring service,” said Greg Chojnacki, a co-author of the UPchieve study. “The study really doesn’t speak to how promising this model is for students who may face additional barriers to taking up tutoring.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chojnacki has been studying different versions of tutoring and he says that this on-demand version might prove to be beneficial for the “kid who may be jumping up for extra help the first chance they get,” while other children might first need to “build a trusting relationship” with a tutor they can see and talk to before they engage in learning. With UPchieve and other on-demand models, students are assigned to a different tutor at each session and don’t get a chance to build a relationship. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Chojnacki also walked back the numerical results in our interview. He told me not to “put too much stock” in the exact amount of math that students learned. He said he’s confident that self-motivated students who use the tutoring service more often learned more math, but it could be “anywhere above zero” and not nearly as high as 9 percentile points – an extra three and a half months worth of math instruction.\u003c/span>\u003c/p>\n\u003cp>\u003cb>UPchieve defends “magical” results\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">UPchieve’s founder, Aly Murray, told me that the Mathematica study results initially surprised her, too. “I agree they almost seem magical,” she said by email. While acknowledging that a larger study is needed to confirm the results, she said she believes that online tutoring without audio and video can “lead to greater learning” than in-person tutoring “when done right.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I personally believe that tutoring is most effective when the student is choosing to be there and has an acute need that they want to address (two things that are both uniquely true of on-demand tutoring),” she wrote. “Students have told us how helpful it is to get timely feedback and support in the exact moment that they get confused (which is often late at night in their homes while working on their homework). So in general, I believe that on-demand tutoring is more impactful than traditional high-dosage tutoring models on a \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">per tutoring session\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> or \u003c/span>\u003ci>\u003cspan style=\"font-weight: 400\">per hour of tutoring\u003c/span>\u003c/i>\u003cspan style=\"font-weight: 400\"> basis. This could be part of why we were able to achieve such outsized results despite the low number of sessions.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Murray acknowledged that low usage remains a problem. At UPchieve’s partner schools, only 5% of students logged in at least once during the 2022-23 year, she told me. At some schools, usage rates fell below 1%. Her goal is to increase usage rates at partner schools to 36%. (Any low-income student in grades eight to 12 can use the tutoring service at no cost and their schools don’t pay UPchieve for the tutoring either, but some “partner” schools pay UPchieve to promote and monitor usage.) \u003c/span>\u003c/p>\n\u003cp>\u003cb>The downside to homework help\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Helping students who are stuck on a homework assignment is certainly nice for motivated kids who love school, but relying on homework questions is a poor way to catch up students who are the most behind, according to many tutoring experts. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I have a hard time believing that students know enough about what they don’t know,” said Susanna Loeb, a Stanford University economist who founded the National Student Support Accelerator, which aims to bring evidence-based tutoring to more students. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">For students who are behind grade level, homework questions often don’t address their gaps in basic math foundations. “Maybe underneath, they’re struggling with percentages, but they’re bringing an algebra question,” said Loeb. “If you just bring the work of the classroom to the tutor, it doesn’t help students very much.” \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Pre-pandemic research of once-a-week after-school homework help also produced disappointing results for struggling students. Effective tutoring starts with an assessment of students’ gaps, Loeb said, followed by consistent, structured lessons.\u003c/span>\u003c/p>\n\u003cp>\u003cb>Schools struggle to offer tutors for all students\u003c/b>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">With so little evidence, why are schools buying on-demand online tutoring? Pittsburgh superintendent Wayne Walters said he was unable to arrange for in-person tutoring in all of his 54 schools and wanted to give each of his 19,000 students access to something. He \u003c/span>\u003ca href=\"https://www.tutor.com/press/press-releases-2023/20230807\">\u003cspan style=\"font-weight: 400\">signed a contract with Tutor.com\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> for unlimited online text-chat tutoring in 2023-24. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">“I’m going forward with it because it’s available,” Walters said. “If I don’t have something to provide, or even offer, then that limits opportunity and access. If there’s no access, then I can’t even push the needle to address the most marginalized and the most vulnerable.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">Walters hopes to make on-demand tutoring “sexy” and appealing to high schoolers accustomed to texting. But online tutoring is not the same as spontaneous texting between friends. One-minute delays in tutors’ replies to questions can test students’ patience. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">On-demand tutoring can appear to be an economical option. Pittsburgh is able to offer this kind of tutoring, which includes college admissions test prep for high schoolers, to all 19,000 of its students for $600,000. Providing 400 students with a high-dosage tutoring program – the kind that researchers recommend – could cost $1.5 million. There are thousands of Pittsburgh students who are significantly behind grade level. It doesn’t seem fair to deliver high-quality in-person tutoring to only a lucky few.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">However, once you factor in actual usage, the economics of on-demand tutoring looks less impressive. In \u003c/span>\u003ca href=\"https://go.boarddocs.com/vsba/fairfax/Board.nsf/files/CKQJTV4EC65A/%24file/Tutor.com%20write%20up%20%20mf.pdf\">\u003cspan style=\"font-weight: 400\">Fairfax County, Va., for example, only 1.6% of students used Tutor.com\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\">. If Pittsburgh doesn’t surpass that rate, then no more than 300 of its students will be served.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400\">There are no villains here. School leaders are trying to do the best they can and be fair to everyone. Hopes are raised when research suggests that online on-demand tutoring can work if they can succeed in marketing to students. But they should be skeptical of studies that promise easy solutions before investing precious resources. That money could be better spent on small-group tutoring that \u003c/span>\u003ca href=\"https://www.nber.org/papers/w27476\">\u003cspan style=\"font-weight: 400\">dozens of studies show is more effective\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400\"> for students.\u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-schools-keep-buying-online-drop-in-tutoring-the-research-doesnt-support-it/\">\u003ci>\u003cspan style=\"font-weight: 400\">drop-in tutoring\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> was written by Jill Barshay and produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/\">\u003cspan style=\"font-weight: 400\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\">, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003cspan style=\"font-weight: 400\">.\u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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},
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"title": "The California Report Magazine",
"tagline": "Your state, your stories",
"info": "Every week, The California Report Magazine takes you on a road trip for the ears: to visit the places and meet the people who make California unique. The in-depth storytelling podcast from the California Report.",
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"officialWebsiteLink": "/californiareportmagazine",
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"order": 10
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},
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"info": "A one-hour radio program to hear celebrated writers, artists and thinkers address contemporary ideas and values, often discussing the creative process. Please note: tapes or transcripts are not available",
"imageSrc": "https://ww2.kqed.org/radio/wp-content/uploads/sites/50/2018/05/cityartsandlecture-300x300.jpg",
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"airtime": "SUN 1pm-2pm, TUE 10pm, WED 1am",
"meta": {
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"source": "City Arts & Lectures"
},
"link": "https://www.cityarts.net",
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"rss": "https://www.cityarts.net/feed/"
}
},
"closealltabs": {
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"order": 1
},
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"info": "\u003cem>Code Switch\u003c/em>, which listeners will hear in the first part of the hour, has fearless and much-needed conversations about race. Hosted by journalists of color, the show tackles the subject of race head-on, exploring how it impacts every part of society — from politics and pop culture to history, sports and more.\u003cbr />\u003cbr />\u003cem>Life Kit\u003c/em>, which will be in the second part of the hour, guides you through spaces and feelings no one prepares you for — from finances to mental health, from workplace microaggressions to imposter syndrome, from relationships to parenting. The show features experts with real world experience and shares their knowledge. Because everyone needs a little help being human.\u003cbr />\u003cbr />\u003ca href=\"https://www.npr.org/podcasts/510312/codeswitch\">\u003cem>Code Switch\u003c/em> offical site and podcast\u003c/a>\u003cbr />\u003ca href=\"https://www.npr.org/lifekit\">\u003cem>Life Kit\u003c/em> offical site and podcast\u003c/a>\u003cbr />",
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"id": "commonwealth-club",
"title": "Commonwealth Club of California Podcast",
"info": "The Commonwealth Club of California is the nation's oldest and largest public affairs forum. As a non-partisan forum, The Club brings to the public airwaves diverse viewpoints on important topics. The Club's weekly radio broadcast - the oldest in the U.S., dating back to 1924 - is carried across the nation on public radio stations and is now podcasting. Our website archive features audio of our recent programs, as well as selected speeches from our long and distinguished history. This podcast feed is usually updated twice a week and is always un-edited.",
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"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Commonwealth-Club-Podcast-Tile-360x360-1.jpg",
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"source": "Commonwealth Club of California"
},
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"google": "https://podcasts.google.com/feed/aHR0cDovL3d3dy5jb21tb253ZWFsdGhjbHViLm9yZy9hdWRpby9wb2RjYXN0L3dlZWtseS54bWw",
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"title": "Forum",
"tagline": "The conversation starts here",
"info": "KQED’s live call-in program discussing local, state, national and international issues, as well as in-depth interviews.",
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"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Forum-Podcast-Tile-703x703-1.jpg",
"imageAlt": "KQED Forum with Mina Kim and Alexis Madrigal",
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"source": "kqed",
"order": 9
},
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"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGhvbmUuZm0vS1FJTkM5NTU3MzgxNjMz",
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"officialWebsiteLink": "http://freakonomics.com/",
"airtime": "SUN 1am-2am, SAT 3pm-4pm",
"meta": {
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"source": "WNYC"
},
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"apple": "https://itunes.apple.com/us/podcast/freakonomics-radio/id354668519",
"tuneIn": "https://tunein.com/podcasts/WNYC-Podcasts/Freakonomics-Radio-p272293/",
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},
"fresh-air": {
"id": "fresh-air",
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"apple": "https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewPodcast?s=143441&mt=2&id=214089682&at=11l79Y&ct=nprdirectory",
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"info": "A live production of NPR and WBUR Boston, in collaboration with stations across the country, Here & Now reflects the fluid world of news as it's happening in the middle of the day, with timely, in-depth news, interviews and conversation. Hosted by Robin Young, Jeremy Hobson and Tonya Mosley.",
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"hidden-brain": {
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"info": "Shankar Vedantam uses science and storytelling to reveal the unconscious patterns that drive human behavior, shape our choices and direct our relationships.",
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"airtime": "SUN 7pm-8pm",
"meta": {
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"source": "NPR"
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"link": "/radio/program/hidden-brain",
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"how-i-built-this": {
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"title": "How I Built This with Guy Raz",
"info": "Guy Raz dives into the stories behind some of the world's best known companies. How I Built This weaves a narrative journey about innovators, entrepreneurs and idealists—and the movements they built.",
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"airtime": "SUN 7:30pm-8pm",
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},
"link": "/radio/program/how-i-built-this",
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"npr": "https://rpb3r.app.goo.gl/3zxy",
"apple": "https://itunes.apple.com/us/podcast/how-i-built-this-with-guy-raz/id1150510297?mt=2",
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"hyphenacion": {
"id": "hyphenacion",
"title": "Hyphenación",
"tagline": "Where conversation and cultura meet",
"info": "What kind of no sabo word is Hyphenación? For us, it’s about living within a hyphenation. Like being a third-gen Mexican-American from the Texas border now living that Bay Area Chicano life. Like Xorje! Each week we bring together a couple of hyphenated Latinos to talk all about personal life choices: family, careers, relationships, belonging … everything is on the table. ",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2025/03/Hyphenacion_FinalAssets_PodcastTile.png",
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"officialWebsiteLink": "/podcasts/hyphenacion",
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"order": 15
},
"link": "/podcasts/hyphenacion",
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},
"jerrybrown": {
"id": "jerrybrown",
"title": "The Political Mind of Jerry Brown",
"tagline": "Lessons from a lifetime in politics",
"info": "The Political Mind of Jerry Brown brings listeners the wisdom of the former Governor, Mayor, and presidential candidate. Scott Shafer interviewed Brown for more than 40 hours, covering the former governor's life and half-century in the political game – and Brown has some lessons he'd like to share. ",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/The-Political-Mind-of-Jerry-Brown-Podcast-Tile-703x703-1.jpg",
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"officialWebsiteLink": "/podcasts/jerrybrown",
"meta": {
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"order": 18
},
"link": "/podcasts/jerrybrown",
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},
"latino-usa": {
"id": "latino-usa",
"title": "Latino USA",
"airtime": "MON 1am-2am, SUN 6pm-7pm",
"info": "Latino USA, the radio journal of news and culture, is the only national, English-language radio program produced from a Latino perspective.",
"imageSrc": "https://ww2.kqed.org/radio/wp-content/uploads/sites/50/2018/04/latinoUsa.jpg",
"officialWebsiteLink": "http://latinousa.org/",
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},
"link": "/radio/program/latino-usa",
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"apple": "https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewPodcast?s=143441&mt=2&id=79681317&at=11l79Y&ct=nprdirectory",
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"rss": "https://feeds.npr.org/510016/podcast.xml"
}
},
"marketplace": {
"id": "marketplace",
"title": "Marketplace",
"info": "Our flagship program, helmed by Kai Ryssdal, examines what the day in money delivered, through stories, conversations, newsworthy numbers and more. Updated Monday through Friday at about 3:30 p.m. PT.",
"airtime": "MON-FRI 4pm-4:30pm, MON-WED 6:30pm-7pm",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Marketplace-Podcast-Tile-360x360-1.jpg",
"officialWebsiteLink": "https://www.marketplace.org/",
"meta": {
"site": "news",
"source": "American Public Media"
},
"link": "/radio/program/marketplace",
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"rss": "https://feeds.publicradio.org/public_feeds/marketplace-pm/rss/rss"
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},
"masters-of-scale": {
"id": "masters-of-scale",
"title": "Masters of Scale",
"info": "Masters of Scale is an original podcast in which LinkedIn co-founder and Greylock Partner Reid Hoffman sets out to describe and prove theories that explain how great entrepreneurs take their companies from zero to a gazillion in ingenious fashion.",
"airtime": "Every other Wednesday June 12 through October 16 at 8pm (repeats Thursdays at 2am)",
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"officialWebsiteLink": "https://mastersofscale.com/",
"meta": {
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"source": "WaitWhat"
},
"link": "/radio/program/masters-of-scale",
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"rss": "https://rss.art19.com/masters-of-scale"
}
},
"mindshift": {
"id": "mindshift",
"title": "MindShift",
"tagline": "A podcast about the future of learning and how we raise our kids",
"info": "The MindShift podcast explores the innovations in education that are shaping how kids learn. Hosts Ki Sung and Katrina Schwartz introduce listeners to educators, researchers, parents and students who are developing effective ways to improve how kids learn. We cover topics like how fed-up administrators are developing surprising tactics to deal with classroom disruptions; how listening to podcasts are helping kids develop reading skills; the consequences of overparenting; and why interdisciplinary learning can engage students on all ends of the traditional achievement spectrum. This podcast is part of the MindShift education site, a division of KQED News. KQED is an NPR/PBS member station based in San Francisco. You can also visit the MindShift website for episodes and supplemental blog posts or tweet us \u003ca href=\"https://twitter.com/MindShiftKQED\">@MindShiftKQED\u003c/a> or visit us at \u003ca href=\"/mindshift\">MindShift.KQED.org\u003c/a>",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Mindshift-Podcast-Tile-703x703-1.jpg",
"imageAlt": "KQED MindShift: How We Will Learn",
"officialWebsiteLink": "/mindshift/",
"meta": {
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"source": "kqed",
"order": 12
},
"link": "/podcasts/mindshift",
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"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGhvbmUuZm0vS1FJTkM1NzY0NjAwNDI5",
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}
},
"morning-edition": {
"id": "morning-edition",
"title": "Morning Edition",
"info": "\u003cem>Morning Edition\u003c/em> takes listeners around the country and the world with multi-faceted stories and commentaries every weekday. Hosts Steve Inskeep, David Greene and Rachel Martin bring you the latest breaking news and features to prepare you for the day.",
"airtime": "MON-FRI 3am-9am",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Morning-Edition-Podcast-Tile-360x360-1.jpg",
"officialWebsiteLink": "https://www.npr.org/programs/morning-edition/",
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"link": "/radio/program/morning-edition"
},
"onourwatch": {
"id": "onourwatch",
"title": "On Our Watch",
"tagline": "Deeply-reported investigative journalism",
"info": "For decades, the process for how police police themselves has been inconsistent – if not opaque. In some states, like California, these proceedings were completely hidden. After a new police transparency law unsealed scores of internal affairs files, our reporters set out to examine these cases and the shadow world of police discipline. On Our Watch brings listeners into the rooms where officers are questioned and witnesses are interrogated to find out who this system is really protecting. Is it the officers, or the public they've sworn to serve?",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/On-Our-Watch-Podcast-Tile-703x703-1.jpg",
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"officialWebsiteLink": "/podcasts/onourwatch",
"meta": {
"site": "news",
"source": "kqed",
"order": 11
},
"link": "/podcasts/onourwatch",
"subscribe": {
"apple": "https://podcasts.apple.com/podcast/id1567098962",
"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5ucHIub3JnLzUxMDM2MC9wb2RjYXN0LnhtbD9zYz1nb29nbGVwb2RjYXN0cw",
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},
"on-the-media": {
"id": "on-the-media",
"title": "On The Media",
"info": "Our weekly podcast explores how the media 'sausage' is made, casts an incisive eye on fluctuations in the marketplace of ideas, and examines threats to the freedom of information and expression in America and abroad. For one hour a week, the show tries to lift the veil from the process of \"making media,\" especially news media, because it's through that lens that we see the world and the world sees us",
"airtime": "SUN 2pm-3pm, MON 12am-1am",
"imageSrc": "https://ww2.kqed.org/radio/wp-content/uploads/sites/50/2018/04/onTheMedia.png",
"officialWebsiteLink": "https://www.wnycstudios.org/shows/otm",
"meta": {
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"source": "wnyc"
},
"link": "/radio/program/on-the-media",
"subscribe": {
"apple": "https://itunes.apple.com/us/podcast/on-the-media/id73330715?mt=2",
"tuneIn": "https://tunein.com/radio/On-the-Media-p69/",
"rss": "http://feeds.wnyc.org/onthemedia"
}
},
"pbs-newshour": {
"id": "pbs-newshour",
"title": "PBS NewsHour",
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