AI RESEARCH
SLOW: Strategic Logical-inference Open Workspace for Cognitive Adaptation in AI Tutoring
arXiv CS.AI
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ArXi:2603.28062v1 Announce Type: new While Large Language Models (LLMs) have nstrated remarkable fluency in educational dialogues, most generative tutors primarily operate through intuitive, single-pass generation. This reliance on fast thinking precludes a dedicated reasoning workspace, forcing multiple diagnostic and strategic signals to be processed in a conflated manner. As a result, learner cognitive diagnosis, affective perception, and pedagogical decision-making become tightly entangled, which limits the tutoring system's capacity for deliberate instructional adaptation.