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Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
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Zi Xiang Poh; Ean Teng Khor – International Journal on E-Learning, 2024
Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…
Descriptors: Learning Analytics, Goodness of Fit, Academic Achievement, Online Courses
Mok, Heng Ngee – Online Submission, 2011
Differentiated instruction in the form of tiered take-home lab exercises was implemented for students of an undergraduate-level programming course. This paper attempts to uncover the perceptions and usage patterns of students toward these new lab exercises using a comprehensive survey. Findings reveal that these tiered exercises are generally very…
Descriptors: Learner Engagement, Cooperative Learning, Programming, Individualized Instruction