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Predicting students' intention to continue online learning post-COVID-19 pandemic: extension of the unified theory of acceptance and usage technology

Edward E. Marandu (Faculty of Business, University of Botswana, Gaborone, Botswana)
Ivy Rose Mathew (Botho University, Gaborone, Botswana)
Tendai Douglas Svotwa (Graduate Studies and Research, Botho University, Gaborone, Botswana)
Robert P. Machera (Faculty of Business and Accounting, Botho University, Gaborone, Botswana)
Olumide Jaiyeoba (Graduate Studies and Research, Botho University, Gaborone, Botswana)

Journal of Applied Research in Higher Education

ISSN: 2050-7003

Article publication date: 27 May 2022

Issue publication date: 7 April 2023

678

Abstract

Purpose

The purpose of this study is to predict the intention to continue online learning post the coronavirus disease 2019 (COVID-19) pandemic among students in the two largest universities of higher learning in Botswana. Furthermore, the purposes of this study are to elucidate the nexus between performance expectancy and continuance intention to establish the effects of efforts expectancy on continuance intention to investigate the relationship between social influence and continuance intention to determine the relationship between facilitating conditions and continuance intention and to examine the relationship between satisfaction and continuance intention using the extended unified theory of acceptance and usage technology (UTAUT) model postulated by Venkatesh et al. (2003).

Design/methodology/approach

The study is based on the descriptive research design, using a structured questionnaire to collect quantitative data from 509 undergraduate and postgraduate students at Botswana's two major Universities using convenience sampling strategy. An online survey was used to gather primary data due to the COVID-19 pandemic. The study employed correlation and regression analysis in testing the five hypothesized relationships.

Findings

Using the extended theory of UTAUT as a theoretical lens, the study found that: performance expectancy, social influence and satisfaction predict continuance intention of online learning services. These factors have shown to be good predictors of intention in previous research. Expectancy effort had no influence on intention.

Research limitations/implications

The current study covered on only university students from two tertiary institutions; therefore, results cannot safely be generalized to the student population in the country. Therefore, future research should consider enlisting more universities to be more representative, focusing on lecturers, which is an important group in fostering online teaching that could have a spill-over effect on the students' continued online learning.

Practical implications

Implications for online technology selection: These findings suggest that although most universities temporarily adopted online teaching as an emergency solution, students appear to have felt that the outcomes delivered by the system improved their performance. This implies that academic institutions need to consider adjusting the curriculum to promote online learning in the future, whether there is pandemic or no pandemic. Implications for teaching and learning: First, the concept of social influence suggests that lecturers can make use of online chat discussion boards and rooms to foster student collaboration and a sense of community. Second, and finally online service providers should foster a close relationship with students to understand their expectations and extend the performance of their applications to satisfy their users.

Originality/value

This study contributes to literature on online learning during the COVID-19 pandemic period by including satisfaction and continuance intention to the original UTAUT model thus extending the practical value of the model. This study extends knowledge on the factors that determine continuance intention by incorporating satisfaction in addition to the four factors of the traditional UTAUT. The study provides evidence for the predominance of satisfaction over the four traditional factors in predicting intention to continue online learning among students.

Keywords

Citation

Marandu, E.E., Mathew, I.R., Svotwa, T.D., Machera, R.P. and Jaiyeoba, O. (2023), "Predicting students' intention to continue online learning post-COVID-19 pandemic: extension of the unified theory of acceptance and usage technology", Journal of Applied Research in Higher Education, Vol. 15 No. 3, pp. 681-697. https://doi.org/10.1108/JARHE-02-2022-0061

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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