学生计算机程序设计学习自我效能感的影响因素及调节因素探讨

IF 2.1 2区 工程技术 Q2 EDUCATION, SCIENTIFIC DISCIPLINES
Ying-Chieh Liu;Hung-Yi Chen
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引用次数: 0

摘要

贡献:扩大影响自我效能感的因素范围,强调教学质量、同伴支持、课程感知价值、自我调节的调节作用和逆境商(AQ)的重要性。背景:自我效能感被认为是影响学生学习绩效的重要因素。然而,很少有研究探讨自我效能感在学生学习计算机程序设计过程中的前因。研究问题:在计算机编程学习的背景下,影响学生自我效能感的因素是什么?这些因素又如何影响学生在计算机编程学习中的自我效能感?方法:从台湾四所大学收集有效问卷523份。研究发现:三个前因(讲课质量、同伴互惠辅导和感知课程价值)对自我效能感有正向影响。两个调节因子(自我调节和问责)正向调节讲课质量、对等同伴辅导与自我效能之间的关系,而对课程价值感知与自我效能之间的关系无正向调节作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the Antecedents and Moderators of Impacting Self-Efficacy in Students’ Learning Computer Programming
Contribution: Expand the scope of factors influencing self-efficacy and highlight the importance of teaching quality, peer support, perceived course value, the moderating effects of self-regulation, and adversity quotient (AQ). Background: Self-efficacy has been regarded as an important factor in students’ learning performance. However, little research has explored the antecedents of self-efficacy in the context of students’ learning computer programming. Research Question: What are the factors affecting students’ self-efficacy in the context of learning computer programming? And how do these factors influence students’ self-efficacy in learning computer programming?Methodology: Five hundred and twenty-three validated questionnaires were collected from four universities in Taiwan. Findings: Three antecedents (the quality of lectures, reciprocal peer tutoring, and perceived course value) positively affected self-efficacy. Two moderators (self-regulation and AQ) positively moderated the relationships between the quality of lectures, reciprocal peer tutoring, and self-efficacy but not the relationship between perceived course value and self-efficacy.
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来源期刊
IEEE Transactions on Education
IEEE Transactions on Education 工程技术-工程:电子与电气
CiteScore
5.80
自引率
7.70%
发文量
90
审稿时长
1 months
期刊介绍: The IEEE Transactions on Education (ToE) publishes significant and original scholarly contributions to education in electrical and electronics engineering, computer engineering, computer science, and other fields within the scope of interest of IEEE. Contributions must address discovery, integration, and/or application of knowledge in education in these fields. Articles must support contributions and assertions with compelling evidence and provide explicit, transparent descriptions of the processes through which the evidence is collected, analyzed, and interpreted. While characteristics of compelling evidence cannot be described to address every conceivable situation, generally assessment of the work being reported must go beyond student self-report and attitudinal data.
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