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开启未来学习:探索高等教育学生采用元教育的意愿。

Unlocking future learning: Exploring higher education students' intention to adopt meta-education.

作者信息

Al-Adwan Ahmad Samed, Alsoud Malek, Li Na, Majali Tha'er, Smedley Jo, Habibi Akhmad

机构信息

Department of Business Technology, Al-Ahliyya Amman University, Jordan.

Department of E-Marketing and Digital Communication, Al-Ahliyya Amman University, Jordan.

出版信息

Heliyon. 2024 Apr 20;10(9):e29544. doi: 10.1016/j.heliyon.2024.e29544. eCollection 2024 May 15.

DOI:10.1016/j.heliyon.2024.e29544
PMID:38698994
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11064079/
Abstract

Despite the potential of meta-education to transform higher education, there remains a scarcity of research investigating students' adoption intentions. This study aimed to identify factors influencing students' intentions to adopt meta-education using an extended Decomposed Theory of Planned Behavior model (DTPB). Data was collected via an online survey of 596 higher education students from Jordan who were purposefully selected. Structural equation modeling using partial least squares analysis revealed attitude, social influence, and perceived behavioral control as key antecedents of adoption intention. Furthermore, newly added variables including perceived enjoyment, herd behavior, student autonomy, and student innovativeness showed efficiency in explaining variance in attitude, social influence, and perceived behavioral control. Overall, the extended model provided meaningful insights on factors driving students' willingness to adopt meta-education. The study contributes to theory by extending the decomposed TPB model in the context of emerging educational technologies. It also provides practical implications for policymakers and educators aiming to encourage meta-education adoption.

摘要

尽管元教育有改变高等教育的潜力,但对学生采用意愿的研究仍然匮乏。本研究旨在使用扩展的计划行为分解理论模型(DTPB)来识别影响学生采用元教育意愿的因素。通过对596名来自约旦的高等教育学生进行有目的抽样的在线调查收集数据。使用偏最小二乘法分析的结构方程模型显示,态度、社会影响和感知行为控制是采用意愿的关键前因。此外,新增加的变量,包括感知乐趣、羊群行为、学生自主性和学生创新性,在解释态度、社会影响和感知行为控制的方差方面显示出有效性。总体而言,扩展模型为推动学生采用元教育的因素提供了有意义的见解。该研究通过在新兴教育技术背景下扩展分解的TPB模型为理论做出了贡献。它还为旨在鼓励采用元教育的政策制定者和教育工作者提供了实际启示。

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User experience evaluation of a 3D virtual reality educational program for illegal drug use prevention among high school students: Applying the decomposed theory of planned behavior.
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An explanatory study of factors influencing engagement in AI education at the K-12 Level: an extension of the classic TAM model.K-12 阶段人工智能教育参与影响因素的解释性研究:经典 TAM 模型的扩展。
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