Learning by Reviewing Paper-Based Programming Assessments

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Abstract

This paper presents a retrospective analysis of students’ use of self-regulated learning strategies while using an educational technology that connects physical and digital learning spaces. A classroom study was carried out in a Data Structures & Algorithms course offered by the School of Computer Science. Students’ reviewing behaviors were logged and the associated learning impacts were analyzed by monitoring their progress throughout the course. The study confirmed that students who had an improvement in their performance spent more time and effort reviewing formal assessments, particularly their mistakes. These students also demonstrated consistency in their reviewing behavior throughout the semester. In contrast, students who fell behind in class ineffectively reviewed their graded assessments by focusing mostly on what they already knew instead of their knowledge misconceptions.

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APA

Paredes, Y. V., Azcona, D., Hsiao, I. H., & Smeaton, A. (2018). Learning by Reviewing Paper-Based Programming Assessments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11082 LNCS, pp. 510–523). Springer Verlag. https://doi.org/10.1007/978-3-319-98572-5_39

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