FACTORS INFLUENCING IMPLEMENTATION OF E-LEARNING IN TECHNICAL AND VOCATIONAL EDUCATION TRAINING INSTITUTIONS IN UASIN GISHU COUNTY, KENYA

Abstract

Globally, e-learning has emerged as a dominant channel of learning but its implementation is not smooth sailing. This is evidenced by unavoidable difficulties in implementing e-learning calling for investigation into the factors influencing the implementation of e-learning. In this regard, the study determined factors that influence implementation of e-learning in TVET institutions in Uasin Gishu County. The study was guided by the following specific objectives, to; assess the influence of institutional management support on implementation of e-learning; analyze the influence of infrastructure on implementation of e-learning; investigate the influence of ICT competence on implementation of e-learning and; influence of organizational learning culture on implementation of e-learning in TVET institutions in Uasin Gishu County. The study was guided by Roger’s theory of Diffusion of innovation. The study adopted an explanatory research design with an accessible population of 94 electrical and electronic engineering trainers and 6 HoDs of electrical and electronic engineering departments from public TVET institutions from Uasin Gishu County who were engaged in the study through census inquiry. Data was collected by use of questionnaire and interview schedule. The instruments were tested for validity and reliability by checking the internal consistency after piloting questionnaire at Kitale National Polytechnic. Quantitative data was analyzed by use of both inferential and descriptive statistics using Statistical Package for Social Sciences (SPSS) version 25 while qualitative data using themes and sub-themes. The inferential statistics, which were used in this study included simple, multiple regression and Pearson’s correlation, Analysis of Variance (ANOVA) while descriptive statistics included mean, standard deviation, and frequencies. From the findings, the coefficient of determination (R square) of 0.758 indicated that the model explained only 75.8 % of the variation or change in implementation of e-learning. ICT competency with a coefficient of determination R square of 0.623 indicated that the model explained 62.3% of the variation or change in implementation of e-learning, infrastructure with a coefficient of determination R square of 0.449 indicated that the model explained 44.9%, of the variation or change in implementation of e-learning, Organizational Learning Culture with a coefficient of determination R square of 0.42 indicated that the model explained 42% of the variation or change in implementation of e-learning and Institutional management support with a coefficient of determination R square of 0.418 indicated that the model explained 41.8% of the variation or change in implementation of e-learning. Based on the multiple regression coefficients ICT competence has the greatest contribution with B of v0.529 however this did not devalue the role of the other factors. Therefore, TVET institutions should consider strengthening institutional management support, infrastructure, ICT competency and organizational learning culture using a policy framework to enhance their synergy in implementation of e-learning in the teaching of electrical and electronic engineering.