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Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
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
Boberic-Krsticev, Danijela; Tešendic, Danijela – Informatics in Education, 2013
The paper elaborates on experiences and lessons learned from the course on object-oriented analyses and design at the Faculty of Sciences, Novi Sad. The course on OOAD is taught to students of computer science and to the students of mathematical programme. Conclusions made in this paper are based on results of students' assignments as well as…
Descriptors: Foreign Countries, Computer Science Education, Programming, College Students