Explorable theorems ground written proofs in Lean formalizations to enable step-by-step execution, custom example testing, and dependency tracing, with a user study showing improved comprehension.
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Schemex is an interactive three-stage AI workflow for schema induction that user studies show produces more actionable schemas than a frontier baseline without loss of generalizability.
Critical Inker scaffolds critical reflection during AI-assisted writing via Socratic questioning and visual logical-error feedback, reporting 91.2% argument overlap with ground truth and 87% validity accuracy in a pilot evaluation.
CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
LLM-driven personalization of CS1 RegEx worksheets based on learner profiles raises completion to over 99% and boosts correctness by 18.2% for at-risk students while preserving perceived difficulty.
citing papers explorer
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Explorable Theorems: Making Written Theorems Explorable by Grounding Them in Formal Representations
Explorable theorems ground written proofs in Lean formalizations to enable step-by-step execution, custom example testing, and dependency tracing, with a user study showing improved comprehension.
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Schemex: Discovering Structural Abstractions from Examples
Schemex is an interactive three-stage AI workflow for schema induction that user studies show produces more actionable schemas than a frontier baseline without loss of generalizability.
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Critical Inker: Scaffolding Critical Thinking in AI-Assisted Writing Through Socratic Questioning
Critical Inker scaffolds critical reflection during AI-assisted writing via Socratic questioning and visual logical-error feedback, reporting 91.2% argument overlap with ground truth and 87% validity accuracy in a pilot evaluation.
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Improving Code Comprehension through Cognitive-Load Aware Automated Refactoring for Novice Programmers
CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
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Beyond One-Size-Fits-All Exercises: Personalizing Computer Science Worksheets with Large Language Models
LLM-driven personalization of CS1 RegEx worksheets based on learner profiles raises completion to over 99% and boosts correctness by 18.2% for at-risk students while preserving perceived difficulty.