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The Influence of Prior Knowledge and Additional Courses on the Academic Performance of Students in the Introductory Programming Course CS1.

Authors :
Uhanova, Marina
Prokofyeva, Natalya
Katalnikova, Sabina
Zavjalova, Oksana
Ziborova, Viktorija
Source :
Procedia Computer Science; 2023, Vol. 225, p1397-1406, 10p
Publication Year :
2023

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
225
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
174059180
Full Text :
https://doi.org/10.1016/j.procs.2023.10.128