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What drives undergraduates’ effort and persistence in learning programming

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Abstract

This study attempts to: (a) investigate whether positive and negative emotions mediate the pathways linking self-efficacy for learning programming with effort and persistence in undergraduates’ learning Scratch programming combining with a programmable hardware platform (i.e., Arduino), and (b) assess the effect of academic major (i.e., information technology-related majors vs non-information technology-related majors) on self-efficacy for learning programming and emotions. With the use of responses collected from a sample of 156 undergraduate students, the research model is empirically validated using partial least squares structural equation modeling (PLS-SEM). The findings reveal that undergraduates’ effort and persistence while learning programming were significantly predicted by positive emotions, but not by negative emotions. Self-efficacy for learning programming significantly and positively influenced positive emotions and negatively influenced negative emotions. Finally, variations in predicting positive emotions were found between different academic majors: students in information technology-related majors experienced less negative emotional experiences than those in non-information technology-related majors.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We would like to thank all the students who participated in this study.

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  1. Department of Information Management, National Changhua University of Education, Changhua, Taiwan

    Guan-Yu Lin & Yi-Shun Wang

  2. Department of Intelligent Commerce, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan

    Yi-Wen Liao

  3. Department of Information Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan

    Zhi-Yuan Su

  4. Department of Information Management, National Chi Nan University, Puli, Taiwan

    Yu-Min Wang

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GYL contributed to analysis and interpretation of data, as well as writing and revision of manuscript. YWL and ZYU contributed to the acquisition and interpretation of data, as well as writing and revision of manuscript. YMW and YSW contributed to the conception and design of research, analysis and interpretation of data, and revision of the manuscript. All authors read and approved the final manuscript.

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Lin, GY., Liao, YW., Su, ZY. et al. What drives undergraduates’ effort and persistence in learning programming. Educ Inf Technol 28, 12383–12406 (2023). https://doi.org/10.1007/s10639-023-11670-3

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