Think–Pair–Chatbot–Share: AI-Facilitated Peer Learning in Chemistry

This study introduces and evaluates the Think–Pair–Chatbot–Share (TPCS) model, an adaptation of the traditional Think–Pair–Share (TPS) framework where a generative AI (Gen-AI) chatbot is integrated to scaffold learning and provide feedback. We compared first-year chemistry students learning ionization energy and atomic structure using traditional TPS versus the Gen-AI-facilitated TPCS model. Student responses from both think and share stages were analyzed for accuracy and common errors, while engagement was examined via participation rates. Results indicate that for students who completed all stages, the Gen-AI-facilitated TPCS group recorded a higher proportion of correct share stage responses in three of the four tasks. However, the Gen-AI-facilitated TPCS intervention was associated with lower overall participation, suggesting potential challenges related to sustained engagement with the Gen-AI-facilitated, multitask activity. These findings offer the first classroom-level evidence of AI-mediated TPS in action within tertiary chemistry education and underscore both its instructional potential and the challenges in maintaining engagement.

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Publication Details

Journal
Journal of Chemical Education
Published
2025-08-11
DOI
https://doi.org/10.1021/acs.jchemed.5c00438
Citations
3
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
5.08
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article

Think–Pair–Chatbot–Share: AI-Facilitated Peer Learning in Chemistry

Pierre J. P. Naeyaert, Reyne Pullen, Thomas E. Murphy, Liam R. J. Scarratt
3 citations
Journal of Chemical Education
Online Learning and Analytics
5.08
article

Think–Pair–Chatbot–Share: AI-Facilitated Peer Learning in Chemistry

Pierre J. P. Naeyaert, Reyne Pullen, Thomas E. Murphy, Liam R. J. Scarratt
article en
3 citations

Abstract

This study introduces and evaluates the Think–Pair–Chatbot–Share (TPCS) model, an adaptation of the traditional Think–Pair–Share (TPS) framework where a generative AI (Gen-AI) chatbot is integrated to scaffold learning and provide feedback. We compared first-year chemistry students learning ionization energy and atomic structure using traditional TPS versus the Gen-AI-facilitated TPCS model. Student responses from both think and share stages were analyzed for accuracy and common errors, while engagement was examined via participation rates. Results indicate that for students who completed all stages, the Gen-AI-facilitated TPCS group recorded a higher proportion of correct share stage responses in three of the four tasks. However, the Gen-AI-facilitated TPCS intervention was associated with lower overall participation, suggesting potential challenges related to sustained engagement with the Gen-AI-facilitated, multitask activity. These findings offer the first classroom-level evidence of AI-mediated TPS in action within tertiary chemistry education and underscore both its instructional potential and the challenges in maintaining engagement.

Journal of Chemical EducationVol. 102(9)
The University of Sydney (AU), UNSW Sydney (AU)
Openalex Percentile: Top 4%
Online Learning and Analytics
5.08
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