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Related Concept Videos

Self-Regulation01:25

Self-Regulation

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Self-regulation, also known as self-control, encompasses a range of cognitive and behavioral processes that allow individuals to adjust their internal states and outward actions to align with socially acceptable norms and long-term goals. It plays a fundamental role in adaptive functioning, from resisting impulsive behaviors to persisting through challenging tasks. While its benefits are widely recognized, self-regulation is not limitless. Muraven and Baumeister's theory posits that...
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Self-Efficacy01:29

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Self-efficacy is the belief in one's capacity to organize and execute actions necessary to manage prospective situations. This belief significantly influences how individuals approach goals, tasks, and challenges across different domains of life.Psychological and Educational ImpactsIndividuals with strong self-efficacy are more resilient in the face of difficulties. They are more likely to adopt effective problem-solving strategies, persist through obstacles, and regulate emotions such as...
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Metacognition is a conscious process where individuals are aware of their cognitive and executive processes, such as planning before solving a problem or self-monitoring during reading. For instance, a writer may need help with composing a piece. The situation involves a writer who is working on a piece of writing, but while doing so, they realize that something is missing. They notice that their characters lack depth or details. This realization occurs because the writer is reflecting on their...
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Self-Discrepancy Theory02:45

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One influential perspective on what motivates people's behavior is detailed in Tory Higgin's self-discrepancy theory (Higgins, 1987). He proposed that people hold disagreeing internal representations of themselves that lead to different emotional states.  
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Self-Determination Theory (SDT), formulated by Richard Ryan and Edward Deci, explains that human motivation is driven by three fundamental psychological needs: autonomy, competence, and relatedness. When these needs are met, individuals experience personal growth, intrinsic motivation, and overall well-being.
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Self-awareness is a psychological state in which the individual becomes the focal point of their attention. This inward focus transforms the self into an object of contemplation and assessment, influencing how individuals perceive their actions and their alignment with personal and societal standards.Triggers and Contexts for Self-AwarenessSelf-awareness can be activated by external stimuli that make individuals visually or audibly aware of themselves, such as mirrors, cameras, or recordings.
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Related Experiment Video

Updated: Oct 11, 2025

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Explainable AI for Data-Driven Feedback and Intelligent Action Recommendations to Support Students Self-Regulation.

Muhammad Afzaal1, Jalal Nouri1, Aayesha Zia1

  • 1Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden.

Frontiers in Artificial Intelligence
|December 6, 2021
PubMed
Summary

This study introduces an AI-powered dashboard that uses learning analytics and explainable machine learning to provide students with automated feedback and recommendations, improving self-regulation and course performance.

Keywords:
AIautomatic data-driven feedbackdashboardexplainable machine learning-based approachlearning analyticsrecommender systemself-regulated learning

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Area of Science:

  • Educational Technology
  • Artificial Intelligence in Education
  • Learning Analytics

Background:

  • Formative feedback is crucial for student learning but challenging to implement due to time constraints.
  • Existing learning analytics often predict performance without explaining the reasons, limiting actionable insights.

Purpose of the Study:

  • To develop and evaluate an AI-driven approach for automatic, intelligent formative feedback and action recommendations.
  • To enhance student self-regulation and academic performance through data-driven insights.

Main Methods:

  • Utilized learning analytics techniques and explainable machine learning (XAI).
  • Developed a dashboard integrating XAI to provide root cause explanations for predictions and actionable recommendations.
  • Tested and evaluated the dashboard using data from a university Learning Management System (LMS).

Main Results:

  • The developed dashboard significantly improved students' learning outcomes.
  • Students demonstrated enhanced self-regulation abilities with the aid of the dashboard.
  • A positive impact on student motivation was observed.

Conclusions:

  • Explainable machine learning combined with learning analytics offers a viable solution for scalable, intelligent formative feedback.
  • The dashboard effectively supports student self-regulation, motivation, and academic success.
  • The approach addresses limitations of prior predictive models by providing transparent, actionable recommendations.