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<p>This study examines the integration of self-regulated learning strategies with practical activities via information and communication technology (ICT) tools for data collection in high school physics curricula. It explores the interpretation of behavioral data to understand students’ learning strategies. The study engaged educators from six schools, resulting in 40 samples, to implement ICT-enabled experimental kits designed for practical learning activities. Using experimental kits aligned with curriculum outcomes, this research pioneers data collection and analysis to reveal student learning tactics, laying the groundwork for learner profile development. The methodology employs ICT-enabled experimental kits for data gathering, facilitating students’ behavior analysis during learning activities. Clustering techniques, including K-means and principal component analysis, were applied to interpret data, uncovering patterns in goal-setting, self-monitoring, and reflective learning behaviors. These findings highlight the method’s potential to create comprehensive learner profiles, enabling educators to tailor educational experiences to individual learners’ needs more effectively. This initiative aims to enrich the learning experience by seamlessly integrating traditional educational methods with technological innovations, focusing on tailoring them to individual student profiles.</p>

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Self-Regulated Learning in Action: Empowering Physics Curriculum with ICT and Practical Approaches

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月9日

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  • Buchaputara Pansri,
  • Vivat Thongchotchat,
  • Kentarou Kurashige,
  • Shinya Watanabe,
  • Kazuhiko Sato

摘要

This study examines the integration of self-regulated learning strategies with practical activities via information and communication technology (ICT) tools for data collection in high school physics curricula. It explores the interpretation of behavioral data to understand students’ learning strategies. The study engaged educators from six schools, resulting in 40 samples, to implement ICT-enabled experimental kits designed for practical learning activities. Using experimental kits aligned with curriculum outcomes, this research pioneers data collection and analysis to reveal student learning tactics, laying the groundwork for learner profile development. The methodology employs ICT-enabled experimental kits for data gathering, facilitating students’ behavior analysis during learning activities. Clustering techniques, including K-means and principal component analysis, were applied to interpret data, uncovering patterns in goal-setting, self-monitoring, and reflective learning behaviors. These findings highlight the method’s potential to create comprehensive learner profiles, enabling educators to tailor educational experiences to individual learners’ needs more effectively. This initiative aims to enrich the learning experience by seamlessly integrating traditional educational methods with technological innovations, focusing on tailoring them to individual student profiles.