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Autores principales: Gao, Jie, Li, Shasha, Zhang, Jianhua, Li, Shan, Wang, Tingting
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2601.17000
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author Gao, Jie
Li, Shasha
Zhang, Jianhua
Li, Shan
Wang, Tingting
author_facet Gao, Jie
Li, Shasha
Zhang, Jianhua
Li, Shan
Wang, Tingting
contents There has been a growing trend in employing generative artificial intelligence (GenAI) techniques to support learning. Moreover, scholars have reached a consensus on the critical role of self-regulated learning (SRL) in ensuring learning effectiveness within GenAI-assisted learning environments, making it essential to capture students' dynamic SRL patterns. In this study, we extracted students' interaction patterns with GenAI from trace data as they completed a problem-solving task within a GenAI-assisted intelligent tutoring system. Students' purpose of using GenAI was also analyzed from the perspective of information processing, i.e., information acquisition and information transformation. Using sequential and clustering analysis, this study classified participants into two groups based on their SRL sequences. These two groups differed in the frequency and temporal characteristics of GenAI use. In addition, most students used GenAI for information acquisition rather than information transformation, while the correlation between the purpose of using GenAI and learning performance was not statistically significant. Our findings inform both pedagogical design and the development of GenAI-assisted learning environments.
format Preprint
id arxiv_https___arxiv_org_abs_2601_17000
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publishDate 2026
record_format arxiv
spellingShingle Investigating Self-regulated Learning Sequences within a Generative AI-based Intelligent Tutoring System
Gao, Jie
Li, Shasha
Zhang, Jianhua
Li, Shan
Wang, Tingting
Computers and Society
Artificial Intelligence
There has been a growing trend in employing generative artificial intelligence (GenAI) techniques to support learning. Moreover, scholars have reached a consensus on the critical role of self-regulated learning (SRL) in ensuring learning effectiveness within GenAI-assisted learning environments, making it essential to capture students' dynamic SRL patterns. In this study, we extracted students' interaction patterns with GenAI from trace data as they completed a problem-solving task within a GenAI-assisted intelligent tutoring system. Students' purpose of using GenAI was also analyzed from the perspective of information processing, i.e., information acquisition and information transformation. Using sequential and clustering analysis, this study classified participants into two groups based on their SRL sequences. These two groups differed in the frequency and temporal characteristics of GenAI use. In addition, most students used GenAI for information acquisition rather than information transformation, while the correlation between the purpose of using GenAI and learning performance was not statistically significant. Our findings inform both pedagogical design and the development of GenAI-assisted learning environments.
title Investigating Self-regulated Learning Sequences within a Generative AI-based Intelligent Tutoring System
topic Computers and Society
Artificial Intelligence
url https://arxiv.org/abs/2601.17000