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Stereotype Modeling for Problem-Solving Performance Predictions in MOOCs and Traditional Courses, , , и . Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, стр. 76--84. New York, NY, USA, ACM, (2017)Subgoal Labeled Worked Examples in K-3 Education., и . SIGCSE, стр. 616-621. ACM, (2018)Computing Education Research in Finland., , , , , , , , , и 3 other автор(ы). Past, Present and Future of Computing Education Research, Springer, (2023)Automatically Generating CS Learning Materials with Large Language Models., , , , , , , и . CoRR, (2022)Computing Education in the Era of Generative AI., , , , , , , , , и . CoRR, (2023)Learning programming, syntax errors and institution-specific factors., , , и . ACE, стр. 90-96. ACM, (2018)Methodological Considerations for Predicting At-risk Students., , , , и . ACE, стр. 105-113. ACM, (2022)Evaluating Distance Measures for Program Repair., , , , и . ICER (1), стр. 495-507. ACM, (2023)Time-on-Task Metrics for Predicting Performance., , и . SIGCSE (1), стр. 871-877. ACM, (2022)Synthesizing research on programmers' mental models of programs, tasks and concepts - A systematic literature review., , , и . Inf. Softw. Technol., (декабря 2023)