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Adaptive Immediate Feedback Can Improve Novice Programming Engagement and Intention to Persist in Computer Science.

, , , , и . ICER, стр. 194-203. ACM, (2020)

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Evaluation of a Data-driven Feedback Algorithm for Open-ended Programming., , и . EDM, International Educational Data Mining Society (IEDMS), (2017)Hint Generation Under Uncertainty: The Effect of Hint Quality on Help-Seeking Behavior., , и . AIED, том 10331 из Lecture Notes in Computer Science, стр. 311-322. Springer, (2017)Gender, Self-Assessment, and Persistence in Computing: How gender differences in self-assessed ability reduce women's persistence in computer science., , , , , , , и . ICER (1), стр. 73-83. ACM, (2022)Engaging Students with Instructor Solutions in Online Programming Homework., , , и . CHI, стр. 1-7. ACM, (2020)Sharing and Using Programming Log Data (Abstract Only)., , , и . SIGCSE, стр. 729. ACM, (2017)Experience Helps, but It Isn't Everything: Exploring Causes of Affective State in Novice Programmers., , , , , и . SIGCSE (2), стр. 1792-1793. ACM, (2024)An Experience Report on Introducing Explicit Strategies into Testing Checklists for Advanced Beginners., , , , и . ITiCSE (1), стр. 194-200. ACM, (2023)Execution Trace Based Feature Engineering To Enable Formative Feedback on Visual, Interactive Programs., , , , и . EDM, International Educational Data Mining Society, (2021)Investigate Effectiveness of Code Features in Knowledge Tracing Task on Novice Programming Course. (Work in Progress)., , и . EDM (Workshops), том 3051 из CEUR Workshop Proceedings, CEUR-WS.org, (2021)Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models., , , , , , и . SIGCSE (1), стр. 526-532. ACM, (2024)