Factors Influence Students’ Switching Behavior to Online Learning under COVID-19 Pandemic: A Push–Pull–Mooring Model Perspective

Lin, Chien‐Liang; Jin, Yunlong; Zhao, Qun; Yu, Sung Wen; Su, Yu

doi:10.1007/s40299-021-00570-0

Cited by 103 publications

(84 citation statements)

References 89 publications

(177 reference statements)

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“…Members in the chat groups of university teachers created in WeChat and Tencent QQ were invited to distribute the questionnaire to their students. To improve the sample quality, the following four principles proposed in previous studies [83][84][85] were used to screen for valid samples. First, respondents require 8-15 min to complete the questionnaire, thus, samples that were completed within 3 min were considered invalid.…”

Section: Data Collectionmentioning

confidence: 99%

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Hsieh

Lin

et al. 2021

Sustainability

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In order to enable online learning to continue developing when the COVID-19 pandemic passes, this study aimed to identify the critical factors that affected the use of e-learning by university students during the pandemic. These critical factors will help to increase the efficiency of future development and deployment of online learning systems. Through a literature review, this study employed the technology acceptance model, social support, and task–technology fit as the theoretical basis to establish the framework of the online learning environment with regards to the technology acceptance model in the context of emergency management. A questionnaire survey was administered to students in universities that had implemented online teaching during the pandemic, and 552 valid responses were collected. The survey explored the factors affecting the willingness of higher education institution students to continue using online learning, and the following conclusions were drawn. (1) The easier an online learning platform was to navigate, the better it was perceived by the students, and thus the students were more willing to use it. (2) Ease of use and usefulness were associated with the teachers’ choice of platform and their ability to achieve a satisfactory fit between the course design and platform navigation, which thereby affected the students’ learning outcomes and attitude towards use. (3) The positive attitude of teachers towards teaching increased the students’ perceived ease of use of online learning. (4) During the pandemic, family support—a major support for teachers in online teaching—enhanced teachers’ attitudes towards, and willingness to provide, online teaching. A high level of support showed that the parents urged the students to learn and complete online learning tasks as instructed by the teachers, implying that family support could affect the students’ habits towards, adaptation to, and identification of online learning. The study results provide insights into the factors affecting the willingness of teachers and students to continue using e-learning platforms.

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Section: Data Collectionmentioning

confidence: 99%

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Hsieh

Lin

et al. 2021

Sustainability

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“…The perceived security risk arose from the three questions raised ( Grewal et al, 2003 ). In terms of operational definition, the perceived security risk is defined as a safety problem that affects the offline courses during the COVID-19 pandemic, which prompts college students to turn to the online learning platform with a lower security risk ( Lin et al, 2021 ). Second, the pull factor consists of two subconstructs of usefulness and TTF.…”

Section: Methodsmentioning

confidence: 99%

“…In terms of the operability of questionnaire design, whether the learning objectives and online platform meet the needs of learning of the students were mainly explored. To ensure the accuracy of the analysis of measurement items, in this study, based on the operational definition of the pull factor by existing studies, the construct is defined as the formative indicator of a two-stage model consisting of two subconstructs including TTF and usefulness ( Chen and Keng, 2019 ; Lin et al, 2021 ). The switching cost and switching intention were designed with the scale introduced by Chen and Keng (2019) and Jin et al (2021) .…”

Section: Methodsmentioning

confidence: 99%

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Push-Pull-Mooring Analysis of Massive Open Online Courses and College Students During the COVID-19 Pandemic

et al. 2021

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The partial least squares structural equation modeling (PLS-SEM) provides researchers with an analysis tool for prediction theory. As the coronavirus disease 2019 (COVID-19) brings risks to teaching and learning, students have been forced to switch from classroom learning to online learning and most subjects have chosen massive open online courses (MOOCs) for online learning in China. This study examines whether MOOCs can replace traditional classroom education and explores the factors that influence the intentions of switching of the students from offline to online. We sequenced the PLS-SEM analysis of data with 397 students from a university in Zhejiang province of China, testing the model parameters, and discussing the push-pull-mooring (PPM) theory. Our data demonstrate that security risk is a push factor, switching costs are a mooring factor, and perceived usefulness and task–technology fit are pull factors that pull students from traditional, offline learning to MOOCs. In addition, the PPM model of the analysis results provides a more specific understanding of the importance–performance analysis of each factor. Our findings suggest that to constantly improve the switching intention to address unexpected challenges in the future, teachers should establish an effective emergency management measures, including curriculum design, to be consistent with their needs.

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“…Regarding questionnaire retrieval, we collected 833 questionnaires. Items were eliminated about the standards of Lin et al (2021a) . (1) Participants were estimated to require 5–10 min to complete the questionnaire.…”

Section: Methodsmentioning

confidence: 99%

Influencing Factors of University Relocation on College Students’ Intention to Engage in Local Entrepreneurship and Employment

et al. 2021

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In modern society, the power of college students has been able to provide creative growth for the local economy, so the work situation of college students is closely related to the social dynamics. Colleges and universities are important places for talent cultivation and output. They are closely related to the cultivation of college students and the choice of employment and entrepreneurship of college students. Entrepreneurship and employment are interdependent. It is not enough to rely only on entrepreneurs to make enterprises stronger. In order to increase the creativity and environmental adaptability of enterprises, there need to be sufficient and excellent employees who are willing to work in the regions where enterprises are located. Therefore, enterprises need college students with innovation and creativity in their regions. In this study, graduates from a university in Zhejiang Province were selected as the subjects. Based on the Theory of Reasoned Action, literature analysis and interview method were combined to systematically construct a research model affecting college Students’ choice of entrepreneurship and employment. The questionnaire survey method and structural equation model (PLS-SEM) were used to test the hypothesis. A total of 798 valid questionnaires were collected. The results show that local attraction and family factors are the two most important factors affecting the entrepreneurship and employment of college students. Family factors have a significant positive impact on the attitude toward entrepreneurship and employment, subjective norms and intention to entrepreneurship and employment; local attraction also has a significant positive impact on the subjective norms, intention to entrepreneurship and employment, and attitude toward entrepreneurship and employment. The results of this study provide a reference for the decision-making of improving local attractiveness and promoting college Students’ employment in start-up enterprises under the background of higher education popularization.

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Factors Influence Students’ Switching Behavior to Online Learning under COVID-19 Pandemic: A Push–Pull–Mooring Model Perspective

Cited by 103 publications

References 89 publications

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Exploring the Critical Factors, the Online Learning Continuance Usage during COVID-19 Pandemic

Push-Pull-Mooring Analysis of Massive Open Online Courses and College Students During the COVID-19 Pandemic

Influencing Factors of University Relocation on College Students’ Intention to Engage in Local Entrepreneurship and Employment

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