Source record

Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2609.22993.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

Within-subjects study with 131 learners tested CoMeT, an AI coding tutor built on 'preserved metacognitive demand,' which holds learner decision-making constant while varying support. CoMeT escalated help on failure and faded on uptake, matched a question-only tutor's demand, produced twice the artifacts of an unrestricted assistant, and frustrated learners less.

Distinguishes cognitive load from metacognitive demand as a design axis for AI tutors. Controlled comparison, specific escalation/fading rules, and quantified surrender rates make it directly applicable.

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