What drives undergraduates’ effort and persistence in learning programming

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) asse...

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Veröffentlicht in:	Education and information technologies Jg. 28; H. 10; S. 12383 - 12406
Hauptverfasser:	Lin, Guan-Yu, Liao, Yi-Wen, Su, Zhi-Yuan, Wang, Yu-Min, Wang, Yi-Shun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2023 Springer Springer Nature B.V
Schlagworte:	Academic Persistence College students Computer Appl. in Social and Behavioral Sciences Computer Science Computers and Education Education Educational Technology Emotions Information Systems Applications (incl.Internet) Information Technology Least Squares Statistics Majors (Students) Mediation Methods Persistence Positive Attitudes Predictor Variables Programming Psychological Patterns Self Efficacy Structural Equation Models Undergraduate Students User Interfaces and Human Computer Interaction Taiwan Persistence Learning programming Emotions Academic discipline Self-efficacy Effort
ISSN:	1360-2357, 1573-7608
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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.
AbstractList	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.
Audience	Higher Education Postsecondary Education Academic
Author	Liao, Yi-Wen Lin, Guan-Yu Wang, Yi-Shun Wang, Yu-Min Su, Zhi-Yuan
Author_xml	– sequence: 1 givenname: Guan-Yu surname: Lin fullname: Lin, Guan-Yu organization: Department of Information Management, National Changhua University of Education – sequence: 2 givenname: Yi-Wen surname: Liao fullname: Liao, Yi-Wen organization: Department of Intelligent Commerce, National Kaohsiung University of Science and Technology – sequence: 3 givenname: Zhi-Yuan surname: Su fullname: Su, Zhi-Yuan organization: Department of Information Management, Chia Nan University of Pharmacy and Science – sequence: 4 givenname: Yu-Min surname: Wang fullname: Wang, Yu-Min organization: Department of Information Management, National Chi Nan University – sequence: 5 givenname: Yi-Shun orcidid: 0000-0002-0161-5520 surname: Wang fullname: Wang, Yi-Shun email: yswang@cc.ncue.edu.tw organization: Department of Information Management, National Changhua University of Education
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Copyright	The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. COPYRIGHT 2023 Springer
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. – notice: COPYRIGHT 2023 Springer
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SubjectTerms	Academic Persistence College students Computer Appl. in Social and Behavioral Sciences Computer Science Computers and Education Education Educational Technology Emotions Information Systems Applications (incl.Internet) Information Technology Least Squares Statistics Majors (Students) Mediation Methods Persistence Positive Attitudes Predictor Variables Programming Psychological Patterns Self Efficacy Structural Equation Models Undergraduate Students User Interfaces and Human Computer Interaction
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Title	What drives undergraduates’ effort and persistence in learning programming
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