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Daiki Matsumoto; Atsushi Shimada; Yuta Taniguchi – International Association for Development of the Information Society, 2025
Predicting learner actions and intentions is crucial for providing personalized real-time support and early intervention in programming education. This approach enables proactive, context-aware assistance that is difficult for human instructors to deliver by foreseeing signs of potential struggles and misconceptions, or by inferring a learner's…
Descriptors: Prediction, Programming, Coding, Models
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation

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