The Influence of Prior Knowledge and Additional Courses on the Academic Performance of Students in the Introductory Programming Course CS1
Procedia Computer Science 2023
Marina Uhanova, Natālija Prokofjeva, Sabina Kataļņikova, Oksana Zavjalova, Viktorija Ziborova

This article discusses the correlation between first-year students' prior knowledge of programming and their academic achievements. Many students who enroll in the Faculty of Computer Science and Information Technology at Riga Technical University drop out during their first year. Therefore, it is crucial to support first-year students in acquiring programming knowledge successfully. The Faculty of Computer Science and Information Technology provides an additional course called “Algorithmization Practice” for students without prior programming experience. The authors of this paper conducted research to investigate whether this course helps bridge the gap between students with and without prior programming knowledge and whether it improves the academic performance of students without prior knowledge in their first year. The collected data was summarized using descriptive statistics, and the final scores of students from different groups were compared to identify any differences between those who attended the “Algorithmization Practice” course and those who did not. Based on a sample of 1744 introductory programming course students, our analysis indicates that students who attended the additional course demonstrated better academic performance.


Keywords
introductory programming; CS1; prior experience assessment; learning performance improvement
DOI
10.1016/j.procs.2023.10.128
Hyperlink
https://www.sciencedirect.com/science/article/pii/S1877050923012863?via%3Dihub

Uhanova, M., Prokofjeva, N., Kataļņikova, S., Zavjalova, O., Ziborova, V. The Influence of Prior Knowledge and Additional Courses on the Academic Performance of Students in the Introductory Programming Course CS1. Procedia Computer Science, 2023, Vol. 225, pp.1397-1406. ISSN 1877-0509. Available from: doi:10.1016/j.procs.2023.10.128

Publication language
English (en)
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