Metacognition Metacognition as the Regulatory Foundation of AI Competency Development in AI-Supported K–12 Learning: A Systematic Review and Thematic Synthesis
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Abstract
Artificial intelligence (AI) is increasingly integrated into K–12 education, creating new learning opportunities while increasing learners' cognitive and regulatory demands. Although metacognition is widely recognized as essential for self-regulated learning, its role in developing AI competency within AI-supported learning remains fragmented. This systematic review synthesized empirical evidence on the role of metacognition in developing AI competency within AI-supported K–12 learning. Following the PRISMA 2020 guidelines, a systematic search of the Scopus database identified 13 empirical studies published between 2024 and 2026. The studies were analyzed using thematic synthesis, including paper-level coding, code consolidation, descriptive theme development, and analytical theme generation. Three analytical themes emerged. First, metacognition enables learners to appropriate AI-supported scaffolding through monitoring, strategy regulation, reflection, and affective regulation. Second, metacognition extends beyond regulating learning toward the emerging regulation of human–AI interaction by supporting evaluation and strategic control of AI-generated information. Third, metacognition supports regulated knowledge construction, providing a foundation for AI competency-related development. However, direct evidence of AI-specific metacognitive regulation remains limited. This review proposes AI-specific metacognitive regulation and metacognitively regulated AI competency development as complementary conceptual propositions, arguing that metacognition is the regulatory foundation through which AI competency develops and is enacted in AI-supported K–12 learning.
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References
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