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Writing Researcher Finds AI Feedback ‘Better Than I Thought’

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This week I challenged my editor to face off against a machine. Barbara Kantrowitz gamely accepted, under one condition: “You have to file early.” Ever since ChatGPT arrived in 2022, many journalists have made a public stunt out of asking the new generation of artificial intelligence to write their stories. Those AI stories were often bland and sprinkled with errors. I wanted to understand how well ChatGPT handled a different aspect of writing: giving feedback.

My curiosity was piqued by a new study, published in the June 2024 issue of the peer-reviewed journal Learning and Instruction, that evaluated the quality of ChatGPT’s feedback on students’ writing. A team of researchers compared AI with human feedback on 200 history essays written by students in grades 6 through 12 and they determined that human feedback was generally a bit better. Humans had a particular advantage in advising students on something to work on that would be appropriate for where they are in their development as a writer. 

But ChatGPT came close. On a five-point scale that the researchers used to rate feedback quality, with a 5 being the highest quality feedback, ChatGPT averaged a 3.6 compared with a 4.0 average from a team of 16 expert human evaluators. It was a tough challenge. Most of these humans had taught writing for more than 15 years or they had considerable experience in writing instruction. All received three hours of training for this exercise plus extra pay for providing the feedback.

ChatGPT even beat these experts in one aspect; it was slightly better at giving feedback on students’ reasoning, argumentation and use of evidence from source materials – the features that the researchers had wanted the writing evaluators to focus on.

“It was better than I thought it was going to be because I didn’t have a lot of hope that it was going to be that good,” said Steve Graham, a well-regarded expert on writing instruction at Arizona State University, and a member of the study’s research team. “It wasn’t always accurate. But sometimes it was right on the money. And I think we’ll learn how to make it better.”

Average ratings for the quality of ChatGPT and human feedback on 200 student essays

Researchers rated the quality of the feedback on a five-point scale across five different categories. Criteria-based refers to whether the feedback addressed the main goals of the writing assignment, in this case, to produce a well-reasoned argument about history using evidence from the reading source materials that the students were given. Clear directions mean whether the feedback included specific examples of something the student did well and clear directions for improvement. Accuracy means whether the feedback advice was correct without errors. Essential Features refer to whether the suggestion on what the student should work on next is appropriate for where the student is in his writing development and is an important element of this genre of writing. Supportive Tone refers to whether the feedback is delivered with language that is affirming, respectful and supportive, as opposed to condescending, impolite or authoritarian. (Source: Fig. 1 of Steiss et al, “Comparing the quality of human and ChatGPT feedback of students’ writing,” Learning and Instruction, June 2024.)

Exactly how ChatGPT is able to give good feedback is something of a black box even to the writing researchers who conducted this study. Artificial intelligence doesn’t comprehend things in the same way that humans do. But somehow, through the neural networks that ChatGPT’s programmers built, it is picking up on patterns from all the writing it has previously digested, and it is able to apply those patterns to a new text. 


The surprising “relatively high quality” of ChatGPT’s feedback is important because it means that the new artificial intelligence of large language models, also known as generative AI, could potentially help students improve their writing. One of the biggest problems in writing instruction in U.S. schools is that teachers assign too little writing, Graham said, often because teachers feel that they don’t have the time to give personalized feedback to each student. That leaves students without sufficient practice to become good writers. In theory, teachers might be willing to assign more writing or insist on revisions for each paper if students (or teachers) could use ChatGPT to provide feedback between drafts. 

Despite the potential, Graham isn’t an enthusiastic cheerleader for AI. “My biggest fear is that it becomes the writer,” he said. He worries that students will not limit their use of ChatGPT to helpful feedback, but ask it to do their thinking, analyzing and writing for them. That’s not good for learning. The research team also worries that writing instruction will suffer if teachers delegate too much feedback to ChatGPT. Seeing students’ incremental progress and common mistakes remain important for deciding what to teach next, the researchers said. For example, seeing loads of run-on sentences in your students’ papers might prompt a lesson on how to break them up. But if you don’t see them, you might not think to teach it. Another common concern among writing instructors is that AI feedback will steer everyone to write in the same homogenized way. A young writer’s unique voice could be flattened out before it even has the chance to develop.

There’s also the risk that students may not be interested in heeding AI feedback. Students often ignore the painstaking feedback that their teachers already give on their essays. Why should we think students will pay attention to feedback if they start getting more of it from a machine? 

Still, Graham and his research colleagues at the University of California, Irvine, are continuing to study how AI could be used effectively and whether it ultimately improves students’ writing. “You can’t ignore it,” said Graham. “We either learn to live with it in useful ways, or we’re going to be very unhappy with it.”

Right now, the researchers are studying how students might converse back-and-forth with ChatGPT like a writing coach in order to understand the feedback and decide which suggestions to use.

Example of feedback from a human and ChatGPT on the same essay

Source: Steiss et al, “Comparing the quality of human and ChatGPT feedback of students’ writing,” Learning and Instruction, June 2024.

In the current study, the researchers didn’t track whether students understood or employed the feedback, but only sought to measure its quality. Judging the quality of feedback is a rather subjective exercise, just as feedback itself is a bundle of subjective judgment calls. Smart people can disagree on what good writing looks like and how to revise bad writing. 

In this case, the research team came up with its own criteria for what constitutes good feedback on a history essay. They instructed the humans to focus on the student’s reasoning and argumentation, rather than, say, grammar and punctuation. They also told the human raters to adopt a “glow and grow strategy” for delivering the feedback by first finding something to praise, then identifying a particular area for improvement. 

The human raters provided this kind of feedback on hundreds of history essays from 2021 to 2023, as part of an unrelated study of an initiative to boost writing at school. The researchers randomly grabbed 200 of these essays and fed the raw student writing – without the human feedback – to version 3.5 of ChatGPT and asked it to give feedback, too.

At first, the AI feedback was terrible, but as the researchers tinkered with the instructions, or the “prompt,” they typed into ChatGPT, the feedback improved. The researchers eventually settled upon this wording: “Pretend you are a secondary school teacher. Provide 2-3 pieces of specific, actionable feedback on each of the following essays. … Use a friendly and encouraging tone.” The researchers also fed the assignment that the students were given, for example, “Why did the Montgomery Bus Boycott succeed?” along with the reading source material that the students were provided. (More details about how the researchers prompted ChatGPT are explained in Appendix C of the study.)

The humans took about 20 to 25 minutes per essay. ChatGPT’s feedback came back instantly. The humans sometimes marked up sentences by, for example, showing a place where the student could have cited a source to buttress an argument. ChatGPT didn’t write any in-line comments and only wrote a note to the student. 

Researchers then read through both sets of feedback – human and machine – for each essay, comparing and rating them. (It was supposed to be a blind comparison test and the feedback raters were not told who authored each one. However, the language and tone of ChatGPT were distinct giveaways, and the in-line comments were a tell of human feedback.)

Humans appeared to have a clear edge with the very strongest and the very weakest writers, the researchers found. They were better at pushing a strong writer a little bit further, for example, by suggesting that the student consider and address a counterargument. ChatGPT struggled to come up with ideas for a student who was already meeting the objectives of a well-argued essay with evidence from the reading source materials. ChatGPT also struggled with the weakest writers. The researchers had to drop two of the essays from the study because they were so short that ChatGPT didn’t have any feedback for the student. The human rater was able to parse out some meaning from a brief, incomplete sentence and offer a suggestion. 

In one student essay about the Montgomery Bus Boycott, reprinted above, the human feedback seemed too generic to me: “Next time, I would love to see some evidence from the sources to help back up your claim.” ChatGPT, by contrast, specifically suggested that the student could have mentioned how much revenue the bus company lost during the boycott – an idea that was mentioned in the student’s essay. ChatGPT also suggested that the student could have mentioned specific actions that the NAACP and other organizations took. But the student had actually mentioned a few of these specific actions in his essay. That part of ChatGPT’s feedback was plainly inaccurate. 

In another student writing example, also reprinted below, the human straightforwardly pointed out that the student had gotten an historical fact wrong. ChatGPT appeared to affirm that the student’s mistaken version of events was correct.

Another example of feedback from a human and ChatGPT on the same essay

Source: Steiss et al, “Comparing the quality of human and ChatGPT feedback of students’ writing,” Learning and Instruction, June 2024.

So how did ChatGPT’s review of my first draft stack up against my editor’s? One of the researchers on the study team suggested a prompt that I could paste into ChatGPT. After a few back and forth questions with the chatbot about my grade level and intended audience, it initially spit out some generic advice that had little connection to the ideas and words of my story. It seemed more interested in format and presentation, suggesting a summary at the top and subheads to organize the body. One suggestion would have made my piece too long-winded. Its advice to add examples of how AI feedback might be beneficial was something that I had already done. I then asked for specific things to change in my draft, and ChatGPT came back with some great subhead ideas. I plan to use them in my newsletter, which you can see if you sign up for it here. (And if you want to see my prompt and dialogue with ChatGPT, here is the link.) 

My human editor, Barbara, was the clear winner in this round. She tightened up my writing, fixed style errors and helped me brainstorm this ending. Barbara’s job is safe – for now. 


This story about AI feedback was written by Jill Barshay and produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Proof Points and other Hechinger newsletters.

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