<![CDATA[This study examined how artificial intelligence supports students’ self-regulated learning during early classroom implementation, addressing the need to understand how emerging educational technologies influence learners’ planning, monitoring, and reflection processes. Using a convergent mixed methods design, quantitative survey data from 98 students were combined with qualitative reflections from 112 participants. The survey measured planning, monitoring, and reflection, while the qualitative strand captured students’ descriptions of how they engaged with AI-generated guidance. Results showed strong effects of AI on planning and reflection, with moderate and more variable patterns in monitoring. Integrated findings revealed convergence across strands for planning and reflection but divergence in monitoring, where students described difficulties interpreting feedback. These results suggest that AI can serve as a meaningful metacognitive scaffold when supported by developmentally appropriate guidance. The study contributes evidence on how AI influences learner regulation in authentic settings and highlights implications for instructional design and future research.]]>
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