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Zhang, Yingbin; Pinto, Juan D.; Fan, Aysa Xuemo; Paquette, Luc – Journal of Educational Data Mining, 2023
The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…
Descriptors: Problem Solving, Introductory Courses, Computer Science Education, Programming
Ma, Yingbo; Katuka, Gloria Ashiya; Celepkolu, Mehmet; Boyer, Kristy Elizabeth – Journal of Educational Data Mining, 2023
Collaborative learning has numerous benefits such as enhancing learners' critical thinking, developing social skills, and improving learning gains. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. However, detecting learners' satisfaction…
Descriptors: Cooperative Learning, Group Dynamics, Student Satisfaction, Prediction
Gitinabard, Niki; Gao, Zhikai; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – Journal of Educational Data Mining, 2023
Few studies have analyzed students' teamwork (pairwork) habits in programming projects due to the challenges and high cost of analyzing complex, long-term collaborative processes. In this work, we analyze student teamwork data collected from the GitHub platform with the goal of identifying specific pair teamwork styles. This analysis builds on an…
Descriptors: Cooperative Learning, Computer Science Education, Programming, Student Projects
Paassen, Benjamin; McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – Journal of Educational Data Mining, 2021
Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…
Descriptors: Data Analysis, Programming Languages, Networks, Novices
Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – Journal of Educational Data Mining, 2022
Demand for education in Computer Science has increased markedly in recent years. With increased demand has come to an increased need for student support, especially for courses with large programming projects. Instructors commonly provide online post forums or office hours to address this massive demand for help requests. Identifying what types of…
Descriptors: Computer Science Education, Help Seeking, College Faculty, Teacher Role
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology