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Direct linkShan Li; Xiaoshan Huang; Tingting Wang; Juan Zheng; Susanne P. Lajoie – Journal of Computing in Higher Education, 2025
Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…
Descriptors: Information Retrieval, Artificial Intelligence, Prediction, Abstract Reasoning
Karen Woo; Garry Falloon – Computer Science Education, 2025
Background and context: Coding and computational thinking are often taught through integrated curricula, despite a paucity of classroom-based research on their effectiveness. Objective: To investigate evidence of learning resulting from cross-curricular coding tasks in middle-school classrooms, and the school environment factors that impact upon…
Descriptors: Coding, Computer Science Education, Curriculum Development, Thinking Skills
