ONLINE PEDAGOGICAL INFRASTRUCTURE AND THEIR EFFECT ON LEARNING IN PUBLIC UNIVERSITIES. THE CASE OF MASINDE MULIRO UNIVERSITY OF SCIENCE AND TECHNOLOGY, KENYA

Abstract

The demand for higher education has tremendously increased in the past few decades. With increased population in universities and unplanned pandemics like Covid-19, technology has provided universities with the infrastructure to facilitate online learning. In accepting these technologies, implementation challenges leave stakeholders dissatisfied. Post covid 19 pandemic exposed universities lack of capacity to conduct online learning and as a result delayed learning occurred. Masinde Muliro University of Science and Technology (MMUST) as a public university also witnessed drawbacks which were pointers to challenges of implementing online pedagogical infrastructure. The purpose of this study was to investigate online pedagogical infrastructure used in public universities and its effect on learning. The study was conducted at MMUST. Mixed methods research design was adopted in this study. The study population consisted of 7,000 students, 400 members of faculty, 60 university management staff and 6 ODEL staff. Stratified and Random Sampling techniques were used to select the respondents. The sample size included 397 students, 210 faculty members, 6 ODEL staff, and 55 university management staff. Questionnaires, Interviews, Observation and Content Analysis were used as data collection instruments. The instruments were checked for content and face validity and piloted in three schools within the university. Cronbach alpha coefficient of internal consistency was used as a reliability measure where alpha (α) = 0.833 and 0.76 were obtained for faculty and students’ questionnaire. Data collected was cleaned, organized, and analyzed using tables, frequencies, percentages, means, standard deviations and ordered logistic regression analysis. The study revealed that inadequacy of necessary equipment, absence of approved online learning policy and unreliable internet to support online learning greatly affected the use of online infrastructure for learning. The data collected were used to test hypothesis in order draw relevant conclusions at 0.05 level of significance. The data from students and faculty showed that use of online pedagogical infrastructure does not affect learning (Wald =0.07, X2 (1) =17.475, p=4.177). It was also noted that the perception of online pedagogical infrastructure users affects learning (Wald =1.627, X2 (1) =10.285, p=0.025). The study further determined that the challenges currently faced by the university significantly affect learning (Wald =0.673, X2 (1) =2.767, p=0.041). It is recommended that the university should provide necessary resources, train both faculty and students, employ technical staff in ODEL and more so, improve bandwidth for internet connectivity within the university. The outcome of the study contributes to the body of knowledge by forming an important basis for promoting quality online learning. The findings are envisaged to guide policy makers in the formulation of policies that would ensure appropriate development, implementation, and maintenance of online learning infrastructure.