Abstract:

Learning Analytics is an advanced technology feature of learning management systems built on continuous aggregated data to track academic activities and participation, performance outputs and inform strategies to improve learning outcomes and administrative decision-making. Compared to high income countries, relatively limited studies in Sub-Saharan Africa context have investigated how Learning Analytics has transformed the outcomes of enhanced engagement and performance of teachers and learners in higher education since the transition to virtual learning environments at the peak of COVID-19. If the capabilities of Learning Analytics are not optimally utilized, higher education institutions (HEIs) in Sub-Saharan are at risk of not evolving from current learning and teaching styles to meet requirements for participation in the fourth industrial revolution. The aim of this paper is to establish the use or non-use of Learning Analytics to transform teaching and learning performance (in)adequacies at HEIs particularly in Sub-Saharan Africa. The guiding question for this paper is: What are the factors that enable the beneficial use of Learning Analytics beyond the enhancement of engagement and performance towards transforming the outcomes of teaching and learning in HEIs of Sub-Saharan Africa? An analysis of peer-reviewed literature was conducted to identify factors that would enable the optimal use of Learning Analytics towards a positive transformation in the HEIs of Sub-Saharan Africa. Findings from literature show that there is an awareness of Learning Analytics in the learning management systems used in HEIs of Sub-Saharan Africa however, they are underutilized. There is a lack of skills to interpret and optimally benefit from the datasets generated from the Learning Analytics tools by educators, students and HEIs' management. While the information quality generated by Learning Analytics might be accurate, effort expectancy and facilitating conditions are crucial factors to consider during the design phase, if its transformation outcomes are to be realized by HEIs in the context of Sub-Saharan Africa. The practical implications of the paper is to highlight (1) how local HEIs in the context of Sub-Saharan Africa should extend the use of Learning Analytics to intentionally tailor the skills development of students towards addressing real life issues affecting their immediate society, (2) factors that drive the use of Learning Analytics as a transformation tool in HEIs and (3) the need to develop framework(s) to guide transformation goals of key beneficiaries including students, educators and HEIs, through the use of Learning Analytics.

Keywords:

Learning Analytics, Transformation, Performance, Effort Expectancy, Higher Education, Sub-Saharan Africa.