Proposes a six-move framework (Prime, Probe, Point, Attach, Strengthen, Test) for learning with AI, using an 'effortless' diagnostic to avoid illusion of mastery, backed by cited evidence of design-dependent outcomes including 17% harm from unguarded AI and doubled gains from engineered tutors.
Enhancing teaching through constructive alignment
4 Pith papers cite this work. Polarity classification is still indexing.
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The authors report that an AI-assisted harness enabled weekly closed-book tests to replace lectures in one small upper-level course while preserving student accountability, based on survey data from 18 students and project git history.
A framework mapping nine prompt patterns to productive struggle and evaluative judgement for AI-supported secure coding education.
A methodology for undergraduate mathematics education relocates evidential trust from polished written work to live human explanation and cumulative observation to address AI assistance.
citing papers explorer
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The Effortless Trap: Productive Struggle, AI, and the Illusion of Learning
Proposes a six-move framework (Prime, Probe, Point, Attach, Strengthen, Test) for learning with AI, using an 'effortless' diagnostic to avoid illusion of mastery, backed by cited evidence of design-dependent outcomes including 17% harm from unguarded AI and doubled gains from engineered tutors.
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Test-Driven, AI-Assisted Learning: Replacing Lectures with Weekly Closed-Book Tests
The authors report that an AI-assisted harness enabled weekly closed-book tests to replace lectures in one small upper-level course while preserving student accountability, based on survey data from 18 students and project git history.