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A Comparative Study of Problem-Based and Traditional Teaching in Computing Subjects

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Abstract

This study aimed to compare the impact of the problem-based (PBL) with the traditional teaching (TLA) approach on students’ academic performance and learning attitudes of computing subjects at the Kolej Profesional MARA Seri Iskandar (KPMSI), Perak, Malaysia. The participants of this study involved 74 students in the second semester of Foundation in Business (FIB 2) and third semester of Higher National Diploma (HND 3). A total of 40 students were allocated in PBL group while 34 students were allocated in TLA group. The participants were selected using a stratified random sampling technique. In this experimental design study, a quantitative method was employed using an adapted pretest and posttest as the research instrument which consists of 30 multiple choice items. Additionally, a structured survey was administered to the students after they are being exposed to a particular teaching method. Findings of the study showed that students instructed with problem-based approach significantly outperformed than those instructed with traditionally designed instruction. This study also suggests that there was a significant relationship between teaching methods and students’ academic performance. A significant relationship also found in students’ learning attitudes and academic performance where the feedback from the students indicated that items “learn from others” and “peer support” have an impact on their academic performance. No statistically significant relationship was found between teaching methods employed and the students’ learning attitudes. The findings from this study will provide educators with an alternative strategy for improving teaching and learning of computing subjects.

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Correspondence to Sariah Rajuli .

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Rajuli, S., Baharun, N. (2017). A Comparative Study of Problem-Based and Traditional Teaching in Computing Subjects. In: Ahmad, AR., Kor, L., Ahmad, I., Idrus, Z. (eds) Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015). Springer, Singapore. https://doi.org/10.1007/978-981-10-2772-7_28

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  • DOI: https://doi.org/10.1007/978-981-10-2772-7_28

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