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Exploring Personality and Learning Motivation Influences on Students’ Computational Thinking Skills in Introductory Programming Courses

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Abstract

Computational thinking (CT) is an essential skill required for every individual in the digital era to become creative problem solvers. The purpose of this research is to investigate the relationships between computational thinking skills, the Big Five personality factors, and learning motivation using structural equation modeling (SEM). The research administered the computational thinking scale, NEO FFI scale, and Motivated Strategies for Learning Questionnaire to a sample of 92 students pursuing degrees in Computer Science and Engineering. Based on the result analysis, it was determined that both personality and learning motivation had positive and significant impacts on computation thinking skills. Personality had a major contribution to the prediction of CT, with consciousness being the most influential predictor. The findings of this study suggest that educators and academics should focus on the significance of the psychological side of CT for the improvement of students’ CT skills.

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Data Availability

The CSE students’ dataset generated and analyzed during the current study are not publicly available due the fact that the dataset constitute an excerpt of research in progress but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors would like to thank the Department of Computer Science and Department of Computer Engineering and technology, GNDU for their support in administering questionnaires during student induction. This work has been supported by Maulana Azad National Fellowship.

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  1. Department of Computer Science, Guru Nanak Dev University, Amritsar, Punjab, India

    Amanpreet Kaur & Kuljit Kaur Chahal

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  1. Amanpreet Kaur
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Correspondence to Amanpreet Kaur.

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Kaur, A., Chahal, K.K. Exploring Personality and Learning Motivation Influences on Students’ Computational Thinking Skills in Introductory Programming Courses. J Sci Educ Technol 32, 778–792 (2023). https://doi.org/10.1007/s10956-023-10052-1

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