Siqi Shen

Poster Presentation: 11:00am-12:15pm | Wyatt Center Lobby Steps

Poster Title: The Effects of AI Feedback in an Intelligent Textbook on College Students’ Reading and Writing Performance

Poster Abstract: This study investigates how AI feedback in an intelligent textbook influences college students’ reading and writing performance aligned to the Interactive Constructive Active and Passive (ICAP) framework. Using a within-subject design, students completed two read-to-write tasks – constructed response items (CRIs) and summaries – under two conditions: (1) Strategic Thinking And Interactive Reading Support (STAIRS), which provided AI feedback to support interactive engagement, and (2) Random Reread, a control condition without AI feedback to support constructive engagement. STAIRS offered automated scoring of read-to-write tasks, targeted rereading, and a chatbot that engaged students in interactive dialogues to support revision. Results showed that STAIRS significantly improved students’ summary revisions and subsequent summary performance, suggesting that AI feedback functions not only as guidance for improving current summaries but also as feed-forward support to enhance future performance. However, students in the STAIRS condition did not show greater learning gains in CRIs or summative quiz scores. CRI scores may have been limited by ceiling effects, while the lack of quiz benefits may reflect a misalignment between feedback and assessment. Despite mixed outcomes, the observed gains from summaries suggest that AI feedback can play a meaningful role in supporting interactive learning.

Poster: Siqi Shen Poster

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