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August 30, 2026Theory Into PracticeOpen Access

Augmenting, not outsourcing: Leveraging artificial intelligence to support students’ self-regulated learning

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Authors

JLJoni LämsäSJSanna Järvelä

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Overview

Case analysis reveals how AI-enhanced tools augment self-regulated learning in secondary classrooms, indicating that triggering regulation prevents cognitive outsourcing during academic tasks.

Key Points

  • This paper introduces the Trigger Regulation Framework to illustrate how artificial intelligence can be designed to augment students' self-regulated learning rather than offloading cognitive tasks.
  • Introduced the conceptual Trigger Regulation Framework centered on cognitive, emotional, and motivational obstacles during learning.
  • Evaluated two secondary classroom cases utilizing multimodal data streams and analytics to monitor both individual and collaborative regulation.
  • Demonstrated that targeted AI interventions triggered by student obstacles prompt active self-regulation instead of cognitive outsourcing.
  • Showed that multimodal analytics effectively trace individual and socially shared regulation of learning to inform teacher guidance in digital classrooms.

Cite This Study

Lämsä et al. (2026) studied this question.

synapsesocial.com/papers/6a93f00a6c1a8fb52e79c110https://doi.org/10.1080/00405841.2026.2721203
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