Development and validation of the AI-enhanced Self-Regulated Learning (AI-SRL) scale

Abstract

The integration of Artificial Intelligence (AI) into educational settings offers new opportunities for enhancing self-regulated learning (SRL) among students. However, current tools lack precision in measuring how AI influences learners' self-regulatory capabilities. This study introduces the AI-Enhanced Self-Regulated Learning (AI-SRL) Scale, designed to assess SRL in AI-supported educational environments. Through a rigorous scale development process involving a literature review, expert consultation, and systematic validation, we developed a comprehensive measurement instrument. The development employed a two-phase validation approach with separate samples for exploratory and confirmatory factor analyses. The final validated scale comprises 22 items organized into five dimensions: AI Competence, Learning Awareness, Learning Strategies, Engagement and Efficiency, and Ethical Collaboration. These factors capture the multifaceted nature of how students regulate their learning when using AI tools, from technical proficiency to ethical considerations. The scale demonstrated strong psychometric properties, with excellent internal consistency and robust construct validity. This validated instrument has practical applications for educators aiming to optimize AI integration in their classrooms, researchers investigating the intersection of AI and SRL, and institutions developing AI-enhanced curricula. The AI-SRL Scale provides a reliable framework for assessing how effectively students leverage AI tools while maintaining their self-regulatory capabilities, thereby contributing to more effective and responsible AI implementation.

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