This presentation examines the nexus of critical thinking, self-regulated learning (SRL), and generative AI (GenAI) in supporting learner autonomy. Although GenAI has emerged as a potential collaborative tool for learners, its integration often risks oversimplifying learning processes and may encourage over-reliance, undermining the development of critical thinking and independent problem-solving abilities. To address these challenges, a self-assessment rubric was developed, drawing on Zimmerman’s SRL framework and insights from existing AI literacy studies. This rubric guides learners in evaluating their cognitive, behavioral, and attitudinal competencies. It emphasizes planning, monitoring, and reflection phases to improve metacognition, critical evaluation of AI outputs, and ethical awareness.

Drawing on theoretical models and documented case studies, this presentation will explain how the rubric aligns with SRL phases to guide learners in setting goals, analyzing AI outputs critically, and reflecting on outcomes. Specific examples from the rubric will illustrate how learners can use AI tools to identify biases, refine understanding, and make ethical decisions. These conceptual applications highlight the rubric’s potential role in supporting intentional, reflective interaction with AI, promoting autonomy while addressing risks such as cognitive passivity and ethical lapses. This approach offers a practical, evidence-based method for integrating GenAI into education responsibly.