Description

Author

Emmanuel O. Ojo(a) and Anthony J. Onwuegbuzie(b)

(a) School of Education, Faculty of Humanities, University of the Witwatersrand, Johannesburg, South Africa; (b) Faculty of Education, University of Cambridge, England; Department of Educational Leadership and Management/Department of Educational Psychology, University of Johannesburg, Johannesburg, South Africa; and Dialectical Publishing, LLC, Bloomington, IN, USA

Abstract

On 18 March 2020, all South African universities and colleges were closed due to the COVID-19 virus. By early April, 10 universities announced that they were planning to resume teaching and learning online, including the University of the Witwatersrand (i.e., Wits University), Johannesburg, which is the joint highest ranked university in Africa. Therefore, the purpose of this editorial was to examine the perceptions and attitudes of these students regarding online learning in an era of disruption of COVID-19, uniquely using both multi-mixed methods research approaches (i.e., involving the partial integration of multiple methods research approaches and mixed methods research approaches) and meta-methods study approaches (i.e., involving the full[er] integration of multiple methods research approaches and mixed methods research approaches). A total of 4,419 Wits University students completed an online survey. A principal components analysis of one of survey’s scales, namely, the Attitude of Students Towards COVID-19 and its Impact on Higher Education scale, revealed 2 subscales, namely, Students’ Self-regulation Towards COVID-19-Based Higher Education and Attitudes Toward Teaching, Learning, and Assessment in COVID-19-Based Higher Education. Nonparametric analyses revealed that scores on these measures discriminated gender, age group, level of student (i.e., undergraduate vs. postgraduate), locality status (i.e., local vs. international student), and registration status (i.e., full-time vs. part-time). A multiple analysis of the open-ended responses by the VOSviewer 1.6.14 text mining software program led to the identification of 6 metathemes. Similarly, WordStat 8.0.29 topic modeling yielded 5 metathemes that mapped onto VOSviewer’s 6 metathemes, indicating triangulation of findings. A sentiment analysis revealed negative sentiments that identified not only the biggest challenges for students but also the characteristics of students who experience these challenges. Finally, a cluster analysis, combined with chi-square analyses, led to the identification of 4 clusters of students who differed with respect to their attitudes and online experiences. Implications of these findings are discussed.