Citation
Abstract
Over recent years, computer science (CS) teachers and instructors have faced several challenges in helping students strengthen their understanding of programming. The existing assessment methods could be more effective in assessing students' programming skills and knowledge, thus requiring a review of issues surrounding the instruction of programming courses. Against this backdrop, the authors systematically reviewed the current literature to identify several socio-cognitive factors that can help develop a learner model for learning programming. Specifically, the Systematic Reviews and Meta-Analyses (PRISMA) technique was utilized to identify and select relevant articles from three primary online databases: Scopus, Web of Science, and Eric. Initially, 401 relevant papers were identified and retrieved, further reduced to only 24 articles based on specific selection criteria. As revealed, several demographic factors (such as gender, age, ethnicity, and socioeconomic status) and socio-cognitive factors (motivation, attitude, and interest) have been shown to impact student learning of programming significantly. The authors' findings from the systematic literature review helped synthesize the essential elements of the learner model that must be carefully considered and utilized. Arguably, the use of such a new learner model can compel instructors to teach programming more effectively by clarifying several students' socio-cognitive backgrounds, which collectively have a significant impact on student learning of programming courses or subjects at the primary, secondary, and tertiary levels of education, especially in the Malaysian educational context.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Human Ecology Faculty of Modern Language and Communication |
DOI Number: | https://doi.org/10.37934/araset.33.3.169184 |
Publisher: | Semarak Ilmu Publishing |
Keywords: | Programming; Teaching; Learning; Learner's model |
Depositing User: | Mohamad Jefri Mohamed Fauzi |
Date Deposited: | 15 May 2024 06:13 |
Last Modified: | 15 May 2024 06:13 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.37934/araset.33.3.169184 |
URI: | http://psasir.upm.edu.my/id/eprint/105639 |
Statistic Details: | View Download Statistic |
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