Computing departments' academics' perceptions on the impact of Learning and Management Systems on academic performance

Abstract

There are currently more than 500 commercial e-Learning software packages and 300 educational e-Learning software packages, but the surprising fact is that academic failure remains high in universities, especially for first-year students, despite all these advances made by e-Learning. It is this high failure rate problem in this e-Learning era that is at the core of this study whose aim is to model factors affecting the perceptions of academics on the impact of learning management systems (LMSs) on academic performance. This aim will be achieved by following the research question: what are the factors that are affecting the perceptions of academics on the impact of learning management systems on academic performance? Three types of research objectives are used to achieve this aim, namely: (i) to design a theoretically sound model of the factors affecting the perceptions of academics on the impact of LMSs on academic performance. (ii) to empirically test the designed model. (iii) to suggest recommendations on how to improve the perceptions of academics on the impact of LMSs on academic performance. Objectives (i) was accomplished through a content analysis method of reviewing of existing appropriate literature of factors that are affecting the impact of LMSs on e- Learning context; whilst objective (ii) was met by conducting a survey of seventy-eight (78) academic staffs from four public universities of KwaZulu-Natal province of South Africa. On the other hand, objective (iii) was met through a comparison of the results of the survey conducted against the literature analysed. The outcomes of these three objectives are as follows: (i) the Welberg’s theory of education, the self-determination theory, the self-regulated learning theory, the social constructivism theory, and the task technology fit theory can be used as suitable theories applicable to examine the perceived impact of e-Learning on academic performance. (ii) It makes logic to theorize that, on the one hand, academics’ perceived impact of LMSs on academic performance are indirectly affected by their gender, their type of employment and their ethnicity. On the other hand, academics’ attitude towards e-Learning, their computer self-efficacy, their pedagogical beliefs, and their use of LMSs directly affects their perceived impact of

LMSs on academic performance of students. It can be concluded that academics’ perceived impact of LMSs on academic performance can be enhanced by optimising academics’ computer self-efficacy, their pedagogical beliefs, and their attitude towards LMSs.