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Hoq, Muntasir; Brusilovsky, Peter; Akram, Bita – International Educational Data Mining Society, 2023
Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…
Descriptors: Academic Achievement, Prediction, Models, Introductory Courses
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Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement