Using AI to Build Student Feedback Literacy and Leverage Assessment as a Learning Tool

This conceptual article explores practical ways in which college and university instructors can leverage artificial intelligence (AI) to support assessment as learning and develop students’ feedback literacy. Traditional assessment practices often focus on assessment for learning (informing instruction) or of learning (measuring outcomes), while assessment as learning—when students actively monitor and reflect on their own learning—receives less attention. AI can help instructors leverage assessment as a learning tool by generating work samples for student analysis and providing timely, actionable feedback that students can use to revise their work. When combined with instructor modeling, peer dialogue, and scaffolds such as guiding questions or graphic organizers, AI-supported feedback promotes metacognition, self-directed learning, and critical evaluation skills. The article provides practical guidance, including prompts and strategies for using AI to enhance student engagement with feedback, helping instructors create more efficient, effective, and student-centered practices that utilize assessments as learning tools.

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Publication Details

Journal
Intersection A Journal at the Intersection of Assessment and Learning
Published
2026-10-19
DOI
https://doi.org/10.61669/001c.172637
Primary Topic
Student Assessment and Feedback
Type
article
Field-Weighted Citation Impact
0.00
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article

Using AI to Build Student Feedback Literacy and Leverage Assessment as a Learning Tool

Michelle L. Hock, Leighann Pennington
Intersection A Journal at the Intersection of Assessment and Learning
Student Assessment and Feedback
article

Using AI to Build Student Feedback Literacy and Leverage Assessment as a Learning Tool

Michelle L. Hock, Leighann Pennington
article en

Abstract

This conceptual article explores practical ways in which college and university instructors can leverage artificial intelligence (AI) to support assessment as learning and develop students’ feedback literacy. Traditional assessment practices often focus on assessment for learning (informing instruction) or of learning (measuring outcomes), while assessment as learning—when students actively monitor and reflect on their own learning—receives less attention. AI can help instructors leverage assessment as a learning tool by generating work samples for student analysis and providing timely, actionable feedback that students can use to revise their work. When combined with instructor modeling, peer dialogue, and scaffolds such as guiding questions or graphic organizers, AI-supported feedback promotes metacognition, self-directed learning, and critical evaluation skills. The article provides practical guidance, including prompts and strategies for using AI to enhance student engagement with feedback, helping instructors create more efficient, effective, and student-centered practices that utilize assessments as learning tools.

Intersection A Journal at the Intersection of Assessment and LearningVol. 7(5)
Sweet Briar College (US), University of Virginia (US)
Openalex Percentile: Top 3%
Student Assessment and Feedback
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