FACTORS AFFECTING EFFECTIVE ADOPTION OF E-LEARNING IN KENYAN UNIVERSITIES: THE CASE OF JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY

Abstract

This study aimed to analyse the reasons for the limited success in implementation of eLearning at JKUAT. The study analyzed to what extent individual, organizational and technological or system factors contributed to poor adoption of eLearning by JKUAT faculty. A descriptive and correlational research design were applied to collect and analyze data from a sample 146 faculty at the University‘s main campus. A stratified sampling technique was used. The sample was stratified according to the Schools within the main campus proportionately allocated from each of the 7 schools. The main data collection instrument was a questionnaire administered to the faculty. Data analysis was done using both the descriptive (frequency counts, percentages, and means) and inferential statistics (correlation analysis, regression analysis and principal component analysis). The study was undertaken in May / June 2013. The total number of respondents that were registered on the Learning Management System LMS were 39.7%. The highest percentage of registered faculty were found in Institute of Computer Science and Information Technology (ICSIT) (58.3%) followed closely by Agriculture (50.0%). The lowest registration was found in the School of Architecture and Building Sciences (SABS) (16.7%) and the College of Health Sciences (COHES) (33.3%). The attendance of LMS training was 43.2 % showing that the majority of the faculty had not attended a training. On the most limiting factor for using the LMS, access to internet (49.3%), inadequate training (48.0%) and insufficient incentives (50.0%) were rated high (level 4 and 5) by almost half of the respondents. The majority of the respondents accessed internet using their own broadband modem. Among individual factors, computer literacy was significantly correlated to the period of LMS usage, frequency of LMS use and LMS adoption. Computer anxiety and age were found to be significantly negatively correlated with LMS adoption. From the regression analysis, none of the individual factors were significant predictors of LMS adoption. Among the organizational factors, management support, institutional leadership, school and institution wide eLearning strategy, ease of use of the system and ICT infrastructure were rated below average, showing that the faculty had a negative perception about the variables. The school and institution wide eLearning strategy, management support and social influence were found to be significantly correlated to the frequency of LMS use. In v the linear regression, management support was the only predictor variable that was significant and therefore explained the variance of the frequency of LMS use. Among technological factors, ICT infrastructure, perceived usefulness, output quality and job relevance were rated above average, showing the faculty had a slightly positive perception about the variables while perceived ease of use was rated low. Perceived usefulness, perceived ease of use, output quality and job relevance were found to be significantly correlated with the frequency of LMS use. On linear regression, ICT infrastructure, perceived usefulness and job relevance were the only predictor variables that were significant, showing they were significant predictors of behavioral intention. Efforts to improve eLearning adoption should therefore concentrate on improving computer literacy. The faculty had a negative perception of management support, institutional leadership and school and institutional wide eLearning strategy accorded to eLearning. The University therefore requires to undertake measures to enhance management support such as training support, incentives, provision of necessary resources to support use of the system, help desk support, and sufficient time to design and deliver online content. The faculty had a slightly negative perception on the ease of use of the system showing that they were not very comfortable with the system. The university should invest more on ICT infrastructure such as in fast and reliable internet access and provide a dedicated mirrored server for eLearning. The university should also integrate eLearning into the university strategic plan and annual work plans and develop a clear policy and also fund eLearning initiatives.