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Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
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Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
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Sahebi, Shaghayegh; Lin, Yu-Ru; Brusilovsky, Peter – International Educational Data Mining Society, 2016
We propose a novel tensor factorization approach, Feedback-Driven Tensor Factorization (FDTF), for modeling student learning process and predicting student performance. This approach decomposes a tensor that is built upon students' attempt sequence, while considering the quizzes students select to work with as its feedback. FDTF does not require…
Descriptors: Data Analysis, Prediction, Models, Learning
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Maranga, Jemar Jude A.; Matugas, Leilla Keith J.; Lim, Jorge Frederick W.; Romana, Cherry Lyn C. Sta. – International Association for Development of the Information Society, 2019
Teaching an introductory programming course to an average of 40 students while monitoring their performance can be a challenge for instructors. Preparing coding exercises with test cases and checking students' programs can prove to be time consuming at times. Moreover, programming has been known to be quite difficult for students to learn. To…
Descriptors: Online Courses, Programming Languages, Introductory Courses, Computer Science Education
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Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
Stuckey, Bronwyn; Hensman, Jim; Hofmann, Tobias; Dewey, Barbara; Brown, Helen; Cameron, Sonja – 2002
Arguably the biggest "buzz word" of the current year has been "learning or knowledge object". To understand the learning object and why it should be such a highly desirable commodity, it is necessary to unpack not only this concept but more importantly revisit some contributing concepts and constructs (more buzz words) that support the building of…
Descriptors: Computer Assisted Instruction, Constructivism (Learning), Data Analysis, Epistemology