Determinants of High School Learners' Continuous Use of Mobile Learning during the Covid-19 Pandemic

Abstract

Every child has a right to education and attending school is a must in South Africa. However, school attendance was severely disrupted by the Covid-19 pandemic outbreak. Regardless, the academic process has to continue, hence the use of mobile devices as pedagogical tools for learning. The aim of this study therefore is to explore the determinants of high school learners' continuous use of mobile learning in order that the academic project may continue. The study employed a survey design in which quantitative data were collected using a seven-point Likert-type scale questionnaire developed by the researchers. A stratified sample of 500 high school learners participated in the survey of which 419 of them successfully completed the survey, giving a success rate of 83.8%. The remaining 16.2% submissions were spoilt and hence discarded. The study combined three models, namely the technology acceptance model (TAM), self-determination theory (SDT), and the expectation-confirmation model (ECT) in its analysis of the developed seven-construct model which used partial least squares structural equation modelling (PLS-SEM). SmartPLS v 3.0 was used to validate the measurement and structural models of the study. Results showed that all six variables identified for the model were good predictors of high school learners’ continuous use of mobile learning with 68% explained variance for satisfaction and 39.1% for continuous use. The study developed and validated a robust mobile learning model which is recommended to stakeholders for continuous use of mobile learning. Future researchers are encouraged to search for more determinants of continuous use of mobile learning that have not been identified in this study.

Smart Mobile Learning Success Model for Higher Educational Institutions in the Context of the COVID-19 Pandemic

“…Several studies have supported the belief that EUS influences users' intention to use a particular technology [40][41][42][43]. Similarly, previous research has indicated that users find M-learning technology useful and productive if its use does not require much time and effort [44][45][46][47][48]. Hence, it can be argued that students are more likely to use M-learning services if they find that doing so is not complicated.…”

“…According to previous studies [40][41][42][43], the TAM model is one of the most suitable models to measure the acceptance of M-learning among users. This model comprises five main factors-namely, AU, intention to use (IU), attitude (AT), EUS, and PUS-according to Davis [44][45][46]. These factors are considered to be predictors of the acceptance and usage of M-learning, according to previous studies [46][47][48].…”

“…This model comprises five main factors-namely, AU, intention to use (IU), attitude (AT), EUS, and PUS-according to Davis [44][45][46]. These factors are considered to be predictors of the acceptance and usage of M-learning, according to previous studies [46][47][48]. Figure 1 presents the pictorial presentation of the TAM model constructs.…”

The integration of mobile learning in STEM-PjBL for Physics learning: a systematic literature review

“…In today's scienceand technology-rich society, such literacy is important to being a smart consumer and thoughtful participant in democratic decision-making and making sense of the world more generally. Thus, STEM education prepares a scientific and technical workforce, where integration is becoming increasingly common in cutting-edge research and development and a scientifically and technologically literate and more informed society [16]. The STEM-PjBL learning process in guiding students consists of five steps, each step aims to achieve a specific process.…”

The Role of Quality Measurements in Enhancing the Usability of Mobile Learning Applications during COVID-19

“…Third, it can enhance a sense of cooperation and use learning outcomes for the future [29][30][31]. Finally, these applications let students use self-regulated learning and let teachers use personalized instruction [32]. Based on the above, the rapid transition to mobile learning has started.…”