Continuance Intention of University Students and Online Learning during the COVID-19 Pandemic: A Modified Expectation Confirmation Model Perspective

Abstract

The prevalence of COVID-19 has changed traditional teaching modes. For many teachers, online learning effectively compensated for the absence of traditional face-to-face instruction. Online learning can support students and schools and can create unique opportunities under emergency management. Educational institutions in various countries have launched large-scale online course modes in response to the pandemic. Additionally, online learning during a pandemic differs from traditional online learning modes. Through surveying students in higher education institutions, educational reform under emergency management can be explored. Therefore, university students were surveyed to investigate their continuance intention regarding online learning during the pandemic. Expectation confirmation theory was extended using the task-technology fit model to ascertain whether the technical support of promoting online learning helped student’s complete course learning tasks during the pandemic and spawned a continuance intention to use online learning in the future. Data were collected through online questionnaires. A total of 854 valid responses were collected, and partial least squares structural equation modeling was employed to verify the research hypotheses. The results revealed that the overall research framework largely explained continuance intention. Concrete suggestions are proposed for higher education institutions to promote online learning modes and methods after the COVID-19 pandemic.

Determining Factors Affecting Acceptance of E-Learning Platforms during the COVID-19 Pandemic: Integrating Extended Technology Acceptance Model and DeLone & McLean IS Success Model

“…According to Yakubu and Dasuki [15], the Structural Equation Modeling is a collection of methods and techniques that are commonly used to analyze and eventually explain the connection between multiple variables using a series of equations and computations. Additionally, SEM can analyze the most complex linkages between latent factors [46][47][48][49][50][51]. Because of this, SEM can be used for analyzing the factors on why the users use technology in the first place [52,53].…”

How Gamification Leads to Continued Usage of MOOCs? A Theoretical Perspective

“…In addition, the main objective of online learning, including MOOCs, according to existing literature, is to increase the accessibility of education to the general public, enhance the quality of learning, and lower the cost of education delivery [5], [19], [33]- [35]. Generally, learners benefit from MOOCs because they may learn from anywhere, at any time, at their own pace, and most of the MOOC courses are free.…”

“…Several studies highlighted that one of the most criticized aspects is the high dropout rate, and on average, less than 10 % of MOOC learners accomplish their courses [1]- [4]. Hence, further research is needed on learners' continuance intention to use MOOCs [4], [5]. Continuance intention to use refers to learners' enthusiasm to continue participating in a particular course; therefore, if learners have a strong continuance intention to use a given platform, they will be motivated to use it and will more likely persevere in their learning [4]- [6].…”

“…Also, MOOCs provide an emerging form of education and learning. However, the success of MOOCs depends on users' willingness to use and acceptance of the system and its continued usage by learners themselves is a key to the success of MOOC's [4], [5], [7]. The low completion rate is because students are enrolling in MOOCs for different reasons, and there is a considerable variation of motive in interest also [8].…”

Technological pedagogical knowledge self-efficacy and continuance intention of Philippine teachers in remote education amid COVID-19 crisis

“…A review of recent scholarly works shows an emerging body of studies on student self-efficacy and continuance intention in online learning (e.g. Chauhan et al, 2021;Cicha et al, 2021;Cui, 2021;Lin, 2021;Mo et al, 2021;Wang et al, 2021). There is limited interest in teacher TPK self-efficacy (e.g.…”