Examining key factors of beginner's continuance intention in blended learning in higher education.

IF 4.5 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
He Yang, Jin Cai, Harrison Hao Yang, Xiaochen Wang
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引用次数: 15

Abstract

With the outbreak of the COVID-19 pandemic, blended learning became exceptionally widespread, especially in higher education. As a result, many college students became beginners in this learning method. To identify key factors that impact beginners' continuance intention in blended learning, this study surveyed 1845 first-year college students at a university in central China in the falls of 2020 and 2021 who used blended learning for the first time. Structural equation modeling was employed to verify a model that integrates intrinsic motivation and academic self-efficacy in the Expectation-Confirmation Model of Information System Continuance. The results show that performance expectancy, intrinsic motivation, and satisfaction significantly impact beginners' continuance intention in blended learning. Moreover, performance expectancy, intrinsic motivation, and confirmation significantly impact beginners' continuance intention through mediating variable satisfaction. Academic self-efficacy does not directly impact college students' continuance intention but indirectly impacts their continuance intention through intrinsic motivation. Finally, this study provides suggestions for educators to improve beginners' blended learning experience thus promoting their continuance intention in blended learning.

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高等教育混合式学习中初学者继续学习意愿的关键因素研究。
随着COVID-19大流行的爆发,混合式学习变得异常普遍,特别是在高等教育中。因此,许多大学生成为这种学习方法的初学者。为了确定影响混合式学习初学者继续学习意愿的关键因素,本研究于2020年和2021年秋季对华中地区一所大学1845名首次使用混合式学习的一年级大学生进行了调查。采用结构方程模型对信息系统连续性期望-确认模型中整合了内在动机和学术自我效能感的模型进行验证。结果表明,绩效期望、内在动机和满意度对混合式学习初学者的继续学习意愿有显著影响。此外,绩效期望、内在动机和确认通过中介变量满意度显著影响初学者的继续学习意愿。学业自我效能感并不直接影响大学生的继续意向,而是通过内在动机间接影响大学生的继续意向。最后,本研究为教育工作者提供了改善初学者混合学习体验的建议,从而促进他们在混合学习中的继续意愿。
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来源期刊
Journal of Computing in Higher Education
Journal of Computing in Higher Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.10
自引率
3.60%
发文量
40
期刊介绍: Journal of Computing in Higher Education (JCHE) contributes to our understanding of the design, development, and implementation of instructional processes and technologies in higher education. JCHE publishes original research, literature reviews, implementation and evaluation studies, and theoretical, conceptual, and policy papers that provide perspectives on instructional technology’s role in improving access, affordability, and outcomes of postsecondary education.  Priority is given to well-documented original papers that demonstrate a strong grounding in learning theory and/or rigorous educational research design.
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