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Evaluating the effect of Arabic engineering students’ learning styles in blended programming courses

Al-Azawei, A., Al-Bermani, A. K. and Lundqvist, K. (2016) Evaluating the effect of Arabic engineering students’ learning styles in blended programming courses. Journal of Information Technology Education: Research, 15. pp. 109-130. ISSN 1539-3585

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To link to this item DOI: 10.28945/3423


This study investigated the complex relationship among learning styles, gender, perceived satisfaction, and academic performance across four programming courses supported by an e-learning platform. A total of 219 undergraduate students from a public Iraqi university who recently experienced e-learning voluntarily took place in the study. The integrated courses adopted a blended learning mode and all learners were provided the same learning content and pathway irrespective of their individual styles. Data were gathered using the Index of Learning Styles (ILS), three closed-ended questions, and the academic record. Traditional statistics and partial least squares structural equation modelling (PLS-SEM) were performed to examine the proposed hypotheses. The findings of this research suggested that, overall, learning style dimensions are uncorrelated with either academic performance or perceived satisfaction, except for the processing dimension (active/reflective) that has a significant effect on the latter. Furthermore, gender is unassociated with any of the proposed model’s constructs. Finally, there is no significant correlation between academic performance and perceived satisfaction. These results led to the conclusion that even though Arabic engineering students prefer active, sensing, visual, and sequential learning as do other engineering students from different backgrounds, they can adapt to a learning context even if their preferences are not met. The research contributes empirically to the existing debate regarding the potential implications of learning styles and for the Arabic context in particular, since respective research remains rare.

Item Type:Article
ID Code:73434
Uncontrolled Keywords:General Computer Science, Education
Publisher:Informing Science Institute

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