Factors influencing vocational college students’ creativity in online learning during the COVID-19 pandemic: The group comparison between male and female

Xinchen Niu · Xueshi Wu

28 citations0/0 files storedFrontiers in Psychology

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Technology Adoption and User Behaviour Education during COVID-19 pandemic Creativity in Education and Neuroscience

Abstract

The COVID-19 pandemic has forced higher education institutions to shift their teaching activities from traditional face-to-face to online learning. This brings a great challenge to the creativity training of vocational college students, who not only learn theoretical knowledge but also cultivate technical skills. Therefore, it is very important to explore the influencing factors of online learning on students' creativity during the epidemic. By relying on the related literature review, an extensive model is developed by integrating the expectation confirmation model (ECM), technology task fit model (TTF), and the technology acceptance model (TAM) to illustrate key factors that influence creativity. Based on the proposed model, theory-based hypotheses are tested through structural equation modeling employing empirical data gathered through a survey questionnaire of 229 students from different vocational colleges in China. In addition, to extend the analysis results, this paper performs a comparative analysis based on gender. The findings demonstrate that perceived ease of use and perceived usefulness significantly influence knowledge sharing; knowledge sharing significantly affects creativity. However, there is no substantial relationship between perceived usefulness and attitude, and no relationship between attitude and knowledge sharing. Moreover, a multi-group comparison shows that there is a significant gender difference between perceived ease of use and attitude. Based on the findings, theoretical and practical implications are discussed.

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1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2003User Acceptance of Information Technology: Toward A Unified View1 2018When to use and how to report the results of PLS-SEM 1980Understanding Attitudes and Predicting Social Behavior 2011PLS-SEM: Indeed a Silver Bullet 1985From Intentions to Actions: A Theory of Planned Behavior 2015A primer on partial least squares structural equation modeling (PLS-SEM)1979A Paradigm for Developing Better Measures of Marketing Constructs

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