How might educators use AI to support students’ interpretation and uptake of feedback? This week's episode focuses on a recent mixed-methods study about student perceptions of AI's potential to support learners' reflection on and engagement with feedback they receive in higher education.
View our full episode notes at https://www.centerforengagedlearning.org/ai-supported-feedback-uptake/.
How might educators use AI to support students’ interpretation and uptake of feedback?
In this episode, Jessie shares a recent mixed-methods study about student perceptions of AI's potential to support learners' reflection on and engagement with feedback they receive in higher education:
Abbas, Noorhan. 2026. “Investigating Student Perceptions of an AI-Powered Chatbot to Support Feedback Interpretation and Uptake in Higher Education.” Assessment & Evaluation in Higher Education. https://doi.org/10.1080/02602938.2026.2706016
This episode was hosted, edited, and produced by Jessie L. Moore, Director of the Center for Engaged Learning and Professor of Professional Writing & Rhetoric.
60-Second SoTL is produced by the Center for Engaged Learning at Elon University.
Music: “Cryptic” by AudioCoffee.
Image in show art by redgreystock on Magnific
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Jessie L. Moore:
How might educators use AI to support students’ interpretation and uptake of feedback? That’s the focus of this week’s 60-second SoTL from Elon University’s Center for Engaged Learning. I’m Jessie Moore.
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In “Investigating Student Perceptions of an AI-Powered Chatbot to Support Feedback Interpretation and Uptake in Higher Education,” Noorhan Abbas explores how AI might be used—not to give feedback—but rather to help students process and apply that feedback. Their open-access article appears in Assessment & Evaluation in Higher Education.
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In April 2026, Abbas conducted four semi-structured focus groups and a survey with students enrolled in an online, postgraduate masters of science in computing program at a research-intensive university in the United Kingdom. Abbas did not test an existing tool; instead, they focused on students’ perceptions of the trustworthiness and accuracy of a potential AI tool for supporting their understanding of and ability to act on feedback, as well as students’ concerns about AI-supported feedback engagement.
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Abbas reports five themes from thematic analysis of the focus groups:
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Survey findings generally reinforced these themes from the focus groups, and collectively, Abbas’s research suggests that an AI tool that offered a low-stakes, dialogic space for reflecting and acting on feedback could support feedback engagement, particularly if it were contextually grounded with human oversight and explicitly embraced as an allowed learning support within university policy.
To learn more about this study, including Abbas’s survey findings, visit our show notes for a link to the open access article.
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Jessie L. Moore:
Join us for our next episode of 60-second SoTL from Elon University’s Center for Engaged Learning for another snapshot of recent scholarship of teaching and learning. Learn more about the Center at www.CenterForEngagedLearning.org.
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