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Direct linkMarwan, Samiha; Akram, Bita; Barnes, Tiffany; Price, Thomas W. – IEEE Transactions on Learning Technologies, 2022
Theories on learning show that formative feedback that is immediate, specific, corrective, and positive is essential to improve novice students' motivation and learning. However, most prior work on programming feedback focuses on highlighting student's mistakes, or detecting failed test cases after they submit a solution. In this article, we…
Descriptors: Feedback (Response), Formative Evaluation, Programming, Coding
Download full textMao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics
