Enhancing self‐regulated learning and learning experience in generative <scp>AI</scp> environments: The critical role of metacognitive support

The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self‐regulated learning to adapt to this change. However, it is difficult for students to persist in self‐regulation without guidance. Metacognitive support has a significant advantage in enhancing self‐regulated learning, but fewer studies have explored the effects of its role in GenAI environments. The purpose of this study was to investigate the impacts of metacognitive support on college students' self‐regulated learning and learning experiences in a GenAI environment. A quasi‐experiment was designed in which 68 college students were divided into two groups. The experimental group ( N = 35) received explicit metacognitive support, while the control group ( N = 33) did not receive any metacognitive prompts. The experiment lasted 4 weeks. The study measured students' academic performance, self‐regulated learning ability and learning experiences (including cognitive load and technology acceptance). The results indicate that in the GenAI environment, metacognitive support, while not producing significant between‐group differences in achievement, enhances students' self‐regulated learning abilities particularly in terms of task strategy and self‐evaluation, as well as optimizing their learning experience. The study also found that students were at risk of decreasing their level of self‐regulated learning if they lacked metacognitive support in the GenAI environment. The conclusion points out that GenAI supports learners to accomplish learning tasks while potentially reducing self‐regulated learning effectiveness, and that metacognitive support is key to supporting effective regulation in learners' GenAI environments. This study provides an important theoretical and practical basis for how to better support learners' learning in GenAI environments. Practitioner notes What is already known about this topic SRL is vital for effective learning in digital environments. Generative AI tools, like ChatGPT, can enhance learning but require support. Learners often struggle to apply SRL strategies without guidance. What this paper adds Metacognitive support improves SRL in Generative AI environments. It reduces cognitive load and increases the perceived usefulness of AI tools. Structured support leads to better academic outcomes. Implications for practice and/or policy Teachers should integrate metacognitive support when using AI tools. Teacher training should focus on SRL strategies in tech‐rich settings. Policies should promote ethical and effective AI use in education.

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Publication Details

Journal
British Journal of Educational Technology
Published
2025-05-05
DOI
https://doi.org/10.1111/bjet.13599
Citations
42
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
144.69

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article

Enhancing self‐regulated learning and learning experience in generative AI environments: The critical role of metacognitive support

Hongxia Liu, Xiaoqing Xu, Wei Zhao, Nuo Cheng et al.
42 citations
British Journal of Educational Technology
Innovative Teaching and Learning Methods
144.69
article

Enhancing self‐regulated learning and learning experience in generative AI environments: The critical role of metacognitive support

Hongxia Liu, Xiaoqing Xu, Wei Zhao, Nuo Cheng, Lifang Qiao
article en
42 citations

Abstract

The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self‐regulated learning to adapt to this change. However, it is difficult for students to persist in self‐regulation without guidance. Metacognitive support has a significant advantage in enhancing self‐regulated learning, but fewer studies have explored the effects of its role in GenAI environments. The purpose of this study was to investigate the impacts of metacognitive support on college students' self‐regulated learning and learning experiences in a GenAI environment. A quasi‐experiment was designed in which 68 college students were divided into two groups. The experimental group ( N = 35) received explicit metacognitive support, while the control group ( N = 33) did not receive any metacognitive prompts. The experiment lasted 4 weeks. The study measured students' academic performance, self‐regulated learning ability and learning experiences (including cognitive load and technology acceptance). The results indicate that in the GenAI environment, metacognitive support, while not producing significant between‐group differences in achievement, enhances students' self‐regulated learning abilities particularly in terms of task strategy and self‐evaluation, as well as optimizing their learning experience. The study also found that students were at risk of decreasing their level of self‐regulated learning if they lacked metacognitive support in the GenAI environment. The conclusion points out that GenAI supports learners to accomplish learning tasks while potentially reducing self‐regulated learning effectiveness, and that metacognitive support is key to supporting effective regulation in learners' GenAI environments. This study provides an important theoretical and practical basis for how to better support learners' learning in GenAI environments. Practitioner notes What is already known about this topic SRL is vital for effective learning in digital environments. Generative AI tools, like ChatGPT, can enhance learning but require support. Learners often struggle to apply SRL strategies without guidance. What this paper adds Metacognitive support improves SRL in Generative AI environments. It reduces cognitive load and increases the perceived usefulness of AI tools. Structured support leads to better academic outcomes. Implications for practice and/or policy Teachers should integrate metacognitive support when using AI tools. Teacher training should focus on SRL strategies in tech‐rich settings. Policies should promote ethical and effective AI use in education.

British Journal of Educational TechnologyVol. 56(5)
Northeast Normal University (CN), Hebei Normal University (CN)
Humanities and Social Science Fund of Ministry of Education of China
Openalex Percentile: Top 0%
Innovative Teaching and Learning Methods
144.69
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