Abstract
There have been manifold thrilling studies strikingly conducted in recent years to explore factors influencing student acceptance of massive open online courses (MOOCs). The principal goal was to determine future prediction and sustainable use of MOOCs for providing pervasive quality education services. This has led to the examination of different theoretical models tested on varying sample sizes for factor exploration. However, existing studies have reflected heterogeneous results caused by divergent sources not observed in the literature using the multiple correspondence analysis (MCA). This study aimed to apply the data science method of MCA to explore hidden associations amongst factors influencing student acceptance of MOOCs and heterogeneity sources of theoretical models and sample sizes to blur the literature hiatus. Results based on data extracted from 54 primary studies published from 2015 to 2021 with a total of 19,638 valid student responses generally conclude the existence of four main levels of associations. The four associations were respectively composed of single, blended, extended and complex theories and each level is associated with distinct categories and a combination cloud of similar categories. Moreover, results indicated that very small sample size is the most unusual under the basic assumption that none of the variables are correlated. It is practically germane to confirm hidden associations in a dataset of influencing factors to help reach a much greater understanding of the application and performance of MOOCs for sustainable education services.
Highlights
The technology of massive open online courses (MOOCs) has become a recent educational innovation for sustainable online education services that have gained widespread popularity across the world [1]
multiple correspondence analysis (MCA) locates the variable categories in Euclidean space and the principal inertia is usually expressed as a percentage of the total inertia
The previous study has suggested an adjusted version of inertia that was inspired by the joint correspondence analysis (JCA) to allow for higher and more meaningful percentages for the maps [97]
Summary
The technology of massive open online courses (MOOCs) has become a recent educational innovation for sustainable online education services that have gained widespread popularity across the world [1]. MOOC is generally recognized as one of the most recent developmental phases of open educational resources that have tremendously transformed higher education institutions and significantly minimized the spiraling costs of learning. It is reshaping the quality of teaching and learning experiences for students and it provides a wide diversity of high-quality courses and valuable learning materials for the diverse needs of students [3]. MOOC can improve the quality of learning pedagogy, help accelerate collaboration, ensure social cohesion and promote sustainable development growth [8,9]
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