An empirical investigation of student online learning continuance intention in the post-COVID-19 pandemic era

M. Cocosila, Houda Trabelsi, Glen Farrelly
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Abstract

Purpose The purpose of this paper is to investigate students’ viewpoint regarding continuation of using online learning in the post-COVID-19 pandemic world. While during the pandemic years predominantly all formal learning was forced to move online, in the postpandemic environment traditional postsecondary education institutions generally resumed in-person (or face-to-face) learning. Nonetheless, it is possible that some students would like to continue using online learning after using such a system during COVID-19 restrictions. Therefore, it is important for postsecondary institutions to understand students’ views on continuing with online learning so that these institutions can better adapt their offerings to learners’ preferences. Design/methodology/approach This study uses a cross-sectional online survey-based approach grounded on an innovative theoretical framework blending the unified theory of acceptance and use of technology 2 into the expectation-confirmation model of information systems continuance. Data were collected from 247 students in Canada in Fall 2022 and were analyzed with partial least squares structural equation modeling techniques. Findings Perceptions of usefulness and of monetary benefits relative to costs together with developing positive habits regarding online learning are the most significant beliefs motivating students to want to continue with online learning. Furthermore, positive disconfirmation of initial expectations and satisfaction relying on previous use together with a favorable attitude with respect to online learning strongly influence the intention to continue with online education. Originality/value The study opens the door for similar research in other cultural contexts (e.g. with a different individualistic-collectivistic pattern) and for other domains that moved totally online during the COVID-19 pandemic (e.g. primary health care) to maximize people satisfaction while minimizing societal costs.
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后 COVID-19 大流行时代学生在线学习持续意向的实证调查
本文的目的是调查学生对在 19 世纪 COVID 大流行后继续使用在线学习的看法。在大流行时期,所有正规学习都被迫转移到网上,而在大流行后的环境中,传统的中学后教育机构普遍恢复了面对面(或面对面)学习。尽管如此,一些学生在 COVID-19 限制期间使用过在线学习系统后,仍有可能希望继续使用在线学习。因此,中学后教育机构有必要了解学生对继续使用在线学习的看法,这样这些机构才能更好地根据学习者的偏好调整其教学内容。本研究采用了一种基于横断面在线调查的方法,该方法以创新的理论框架为基础,将接受和使用技术的统一理论2与信息系统持续性的期望-确认模型相结合。研究收集了 2022 年秋季加拿大 247 名学生的数据,并采用偏最小二乘法结构方程模型技术对数据进行了分析。研究结果对有用性和相对于成本的货币收益的看法,以及对在线学习养成积极习惯的看法,是促使学生愿意继续在线学习的最重要的信念。此外,对最初期望的积极否定和对以前使用情况的满意度,以及对在线学习的良好态度,都强烈影响着学生继续在线学习的意愿。原创性/价值这项研究为在其他文化背景下(如不同的个人主义-集体主义模式)以及在 COVID-19 大流行期间完全转向在线学习的其他领域(如初级卫生保健)开展类似研究打开了大门,从而在最大程度上提高人们的满意度,同时最大程度地降低社会成本。
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来源期刊
Journal of Systems and Information Technology
Journal of Systems and Information Technology Computer Science-Computer Science (all)
CiteScore
4.40
自引率
0.00%
发文量
18
期刊介绍: The Journal provides an avenue for scholarly work that researches systems thinking applications, information systems, electronic business, data analytics, information sciences, information management, business intelligence, and complex adaptive systems in the application domains of the business environment, health, the built environment, cultural settings, and the natural environment. Papers examine the wider implications of the systems or technology being researched. This means papers consider aspects such as social and organisational relevance, business value, cognitive implications, social implications, impact on individuals or community perspectives, and the development of solutions, rather than focusing solely on the technology. The Journal of Systems and Information Technology is open to a wide range of research methodologies and paper styles including case studies, surveys, experiments, review papers, design science, design thinking and both theoretical and methodological papers. The focus of the journal will be to publish work that fits into the following broad areas of research: Behavioural Information Systems and Human-Computer Interaction, Data Analytics, Data, Information and Security, E-Business, Intelligent Systems and Applications, Logistics and Supply Chain Management/Optimisation, Social Media Analysis, Technology Enhanced Learning.
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