The emergence of agentic artificial intelligence (AI) marks a shift from reactive educational technologies towards systems capable of autonomous multi-step planning, tool orchestration, and adaptive decision-making. As these systems contribute to structuring study pathways, generating feedback, and monitoring learner progression, elements of cognitive and metacognitive regulation become distributed between learners and AI agents. However, existing evaluation approaches in educational technology