Adaptive Practicing Design to Facilitate Self-Regulated Learning

Online higher education provides exceptional flexibility in learning but demands high self-regulated learning skills. The deficiency of self-regulated learning skills in many students highlights the need for support. This study introduces a confidence-based adaptive practicing system as an intellig...

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Main Authors: Hongxin Yan, Fuhua Lin, Kinshuk
Format: Article
Language:English
Published: The Canadian Network for Innovation in Education (CNIE) 2025-04-01
Series:Canadian Journal of Learning and Technology
Subjects:
Online Access:https://cjlt.ca/index.php/cjlt/article/view/28768
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author Hongxin Yan
Fuhua Lin
Kinshuk
author_facet Hongxin Yan
Fuhua Lin
Kinshuk
author_sort Hongxin Yan
collection DOAJ
description Online higher education provides exceptional flexibility in learning but demands high self-regulated learning skills. The deficiency of self-regulated learning skills in many students highlights the need for support. This study introduces a confidence-based adaptive practicing system as an intelligent assessment and tutoring solution to enhance self-regulated learning in STEM disciplines. Unlike conventional intelligent tutoring systems that depend entirely on machine control, confidence-based adaptive practicing integrates learner confidence and control options into the AI-based adaptive mechanism to improve learning autonomy and model efficiency, establishing an AI-learner shared control approach. Based on Vygotsky’s zone of proximal development (ZPD) concept, an innovative knowledge-tracing framework and model called ZPD-KT was designed and implemented in the confidence-based adaptive practicing system. To evaluate the effectiveness of the ZPD-KT model, a simulation of confidence-based adaptive practicing was conducted. Findings showed that ZPD-KT significantly improves the accuracy of knowledge tracing compared to the traditional Bayesian knowledge-tracing model. Also, interviews with experts in the field underlined the potential of the confidence-based adaptive practicing system in facilitating self-regulated learning and the interpretability of the ZPD-KT model. This study also sheds light on a new way of keeping humans apprised of adaptive learning implementation.
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publisher The Canadian Network for Innovation in Education (CNIE)
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spelling doaj-art-aff36e23da0a408da5f604c3a56e75f22025-08-20T03:07:46ZengThe Canadian Network for Innovation in Education (CNIE)Canadian Journal of Learning and Technology1499-66771499-66852025-04-0150310.21432/cjlt28768Adaptive Practicing Design to Facilitate Self-Regulated LearningHongxin Yan0Fuhua Lin1Kinshuk2University of Eastern FinlandAthabasca UniversityUniversity of North Texas Online higher education provides exceptional flexibility in learning but demands high self-regulated learning skills. The deficiency of self-regulated learning skills in many students highlights the need for support. This study introduces a confidence-based adaptive practicing system as an intelligent assessment and tutoring solution to enhance self-regulated learning in STEM disciplines. Unlike conventional intelligent tutoring systems that depend entirely on machine control, confidence-based adaptive practicing integrates learner confidence and control options into the AI-based adaptive mechanism to improve learning autonomy and model efficiency, establishing an AI-learner shared control approach. Based on Vygotsky’s zone of proximal development (ZPD) concept, an innovative knowledge-tracing framework and model called ZPD-KT was designed and implemented in the confidence-based adaptive practicing system. To evaluate the effectiveness of the ZPD-KT model, a simulation of confidence-based adaptive practicing was conducted. Findings showed that ZPD-KT significantly improves the accuracy of knowledge tracing compared to the traditional Bayesian knowledge-tracing model. Also, interviews with experts in the field underlined the potential of the confidence-based adaptive practicing system in facilitating self-regulated learning and the interpretability of the ZPD-KT model. This study also sheds light on a new way of keeping humans apprised of adaptive learning implementation. https://cjlt.ca/index.php/cjlt/article/view/28768adaptive practicingconfidence-based assessmentknowledge tracingquestion sequencingself-regulated learningwheel-spinning
spellingShingle Hongxin Yan
Fuhua Lin
Kinshuk
Adaptive Practicing Design to Facilitate Self-Regulated Learning
Canadian Journal of Learning and Technology
adaptive practicing
confidence-based assessment
knowledge tracing
question sequencing
self-regulated learning
wheel-spinning
title Adaptive Practicing Design to Facilitate Self-Regulated Learning
title_full Adaptive Practicing Design to Facilitate Self-Regulated Learning
title_fullStr Adaptive Practicing Design to Facilitate Self-Regulated Learning
title_full_unstemmed Adaptive Practicing Design to Facilitate Self-Regulated Learning
title_short Adaptive Practicing Design to Facilitate Self-Regulated Learning
title_sort adaptive practicing design to facilitate self regulated learning
topic adaptive practicing
confidence-based assessment
knowledge tracing
question sequencing
self-regulated learning
wheel-spinning
url https://cjlt.ca/index.php/cjlt/article/view/28768
work_keys_str_mv AT hongxinyan adaptivepracticingdesigntofacilitateselfregulatedlearning
AT fuhualin adaptivepracticingdesigntofacilitateselfregulatedlearning
AT kinshuk adaptivepracticingdesigntofacilitateselfregulatedlearning