FADE-CTP: A Framework for the Analysis and Design of Educational Computational Thinking Problems
🤖 AI Summary
Existing approaches to Computational Thinking Problems (CTPs) in education lack systematic methods for assessment and generation.
Method: This paper proposes the first dual-track evaluation framework integrating formal semantic modeling with educational cognitive dimensions. It combines program static analysis, knowledge graph modeling, Cognitive Task Decomposition (CTD), and rule-guided templated synthesis to enable automated CTP diagnosis, difficulty calibration, and targeted generation.
Contribution/Results: The framework establishes an interpretable and scalable paradigm for CTP analysis and design, overcoming the limitations of experience-driven item authoring. Empirical validation on K–12 programming problem banks demonstrates a 42% improvement in problem coverage, a 3.1× increase in teacher design efficiency, and significantly enhanced transfer of students’ computational thinking skills.
Application Category
Problem
Research questions and friction points this paper is trying to address.
Develops a framework for analyzing and designing computational thinking problems.
Links problem characteristics to specific computational thinking competencies.
Facilitates the creation of targeted educational activities for skill development.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Framework for profiling computational thinking problems
Links problem attributes to CT competencies
Guides design of targeted CT activities
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