Among 919 intro CS students solving Prompt Problems, typed prompts beat unedited voice on first-attempt success for two of three tasks; edited voice matched text, and most preferred text.
2011.Cognitive Load Theory
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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.
Fully aligned instructional videos for physical tasks yield 11.1% better completion quality and 15.5% faster times, with four decomposable visual attributes whose isolated misalignments degrade performance without users noticing.
DREAMS is a new modeling prototype that cuts time for creating and revising DRM Reference and Impact Models compared to manual methods, shown in a small study with four users.
LLM2Manim pipeline generates pedagogy-aware Manim animations for STEM, producing slightly better student post-test scores (83% vs 78%), learning gains (d=0.67), and engagement than PowerPoint in a controlled study.
citing papers explorer
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Say What? Examining Text and Voice Input Modalities for Prompt-Based Programming in Computing Education
Among 919 intro CS students solving Prompt Problems, typed prompts beat unedited voice on first-attempt success for two of three tasks; edited voice matched text, and most preferred text.
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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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Substantial, Decomposable, and Invisible: Visual Context Misalignment in Instructional Videos for Physical Tasks
Fully aligned instructional videos for physical tasks yield 11.1% better completion quality and 15.5% faster times, with four decomposable visual attributes whose isolated misalignments degrade performance without users noticing.
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DREAMS: Modelling Support for Research into Engineering and Artistic Design
DREAMS is a new modeling prototype that cuts time for creating and revising DRM Reference and Impact Models compared to manual methods, shown in a small study with four users.
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LLM2Manim: Pedagogy-Aware AI Generation of STEM Animations
LLM2Manim pipeline generates pedagogy-aware Manim animations for STEM, producing slightly better student post-test scores (83% vs 78%), learning gains (d=0.67), and engagement than PowerPoint in a controlled study.