An empirical assessment of technological support for eLearning in selected Zimbabwean universities

Abstract

The rapid adoption of eLearning tools in higher education has created a significant need to evaluate technological support systems in universities. Accordingly, this study was conducted across five universities in Zimbabwe to assess eLearning technological support. A quantitative research methodology was adopted to enable the systematic collection and analysis of numerical data. The study targeted a population of 25,000 individuals across five universities. Using the Raosoft sample size calculator, a sample size of 379 respondents was calculated. A total of 505 survey questionnaires were distributed, of which 379 were completed and returned, yielding a response rate of approximately 75%. Convenience sampling was used as a non-probability sampling technique. While this method facilitated efficient and cost-effective data collection, it may limit the representativeness of the sample and reduce the generalisability of the findings to the broader population. The data gathered were analysed using descriptive statistics and one-way Analysis of Variance (ANOVA), with results presented through Microsoft Excel tables, bar graphs. The findings reveal notable differences in eLearning experiences across the five participating universities. The UZ and CUT demonstrated the strongest technological infrastructures, characterised by reliable internet connectivity, well-performing devices, and robust technical support. In contrast, the ZOU and HIT experienced moderate challenges, particularly with slow loading times and occasional system downtime, despite having access to basic eLearning infrastructure. BUSE exhibited the greatest difficulties, with frequent connectivity issues and limited technical assistance. At the aggregate level, 87.1% of students expressed satisfaction with platform performance; however, 43% rated overall institutional support as inadequate. ANOVA confirmed that inter-institutional differences across all key indicators were statistically significant (p < 0.001).