Learning Analytics Usability Factors towards Learner Performance Assessment – A Review of Literature

Abstract

The Covid-19 pandemic significantly accelerated the adoption of e-learning, resulting in increased investment in digital education platforms and the generation of vast amounts of learner data, commonly referred to as big data. This shift has propelled the development of learning analytics, a field focused on the systematic collection, analysis, and reporting of data to better understand learner behavior and enhance educational outcomes. Despite growing interest in learning analytics, there remains limited understanding of its usability, particularly in assessing student performance within virtual learning environments. This paper presents a critical literature review examining the usability factors of learning analytics in the context of Kenyan universities. Using a desktop research approach, the study synthesizes existing research to identify key gaps and highlight usability dimensions relevant to performance assessment. The review identifies four primary factors influencing the usability of learning analytics tools: perceived usefulness, perceived ease of use, user satisfaction, and learnability. These findings provide a foundation for future empirical studies aimed at evaluating the impact of these factors on learner performance in virtual settings