Analysis of 1,425 students' logs shows they coast through 60% of class time on math seatwork, mostly by stopping early, with extra practice effort correlating to higher standardized test performance.
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5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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LearnMate^2, an LLM-driven personalized learning support system, improves learning outcomes and user experience over existing online platforms combined with generic LLM assistance in small-scale user studies.
RelianceScope is a new analytical framework that maps AI reliance into nine engagement patterns across help-seeking and response-use, situated in students' prior knowledge and instructional context, validated on programming course logs.
AI-assisted code review in student projects increased iterative activity and supported code quality discussions while preserving engagement levels across two cohorts.
A self-regulated GenAI contract changed thinking for 58% of 217 students but did not produce sustained behavior change because maintaining personal guidelines required ongoing self-control that many could not sustain under pressure.
citing papers explorer
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Coasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork
Analysis of 1,425 students' logs shows they coast through 60% of class time on math seatwork, mostly by stopping early, with extra practice effort correlating to higher standardized test performance.
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LearnMate^2: Design and Evaluation of an LLM-powered Personalized and Adaptive Support System for Online Learning
LearnMate^2, an LLM-driven personalized learning support system, improves learning outcomes and user experience over existing online platforms combined with generic LLM assistance in small-scale user studies.
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RelianceScope: An Analytical Framework for Examining Students' Reliance on Generative AI Chatbots in Problem Solving
RelianceScope is a new analytical framework that maps AI reliance into nine engagement patterns across help-seeking and response-use, situated in students' prior knowledge and instructional context, validated on programming course logs.
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AI-Assisted Code Review as a Scaffold for Code Quality and Self-Regulated Learning: An Experience Report
AI-assisted code review in student projects increased iterative activity and supported code quality discussions while preserving engagement levels across two cohorts.
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Self-Regulated Personal Contracts as a Harm Reduction Approach to Generative AI in Undergraduate Programming Education
A self-regulated GenAI contract changed thinking for 58% of 217 students but did not produce sustained behavior change because maintaining personal guidelines required ongoing self-control that many could not sustain under pressure.