Browsing by Subject "Academic achievement -- Evaluation"

Throughput rates, student retention, and dropout rates of postgraduate students remain a critical concern facing higher education institutions around the globe. Higher education institutions continuously strive to find ways in which the various stakeholders can make important decisions to ensure acceleration of throughput rates amongst postgraduate students at these institutions, particularly because the economic crisis relies highly on learned and skillful personnel to stir nations towards developmental goals. Industries requiring skilled personnel are often disappointed by the absence of people able to come to task and this results in a poorer industry when compromises are made to fulfill positions. This study highlighted the most common factors that affect the throughput rates of postgraduate students globally, as well as within South African higher education institutions. This study, however, aimed to investigate the factors that impact throughput rates of postgraduate students at one of the Universities of Technology in South Africa. To achieve the results, a structured questionnaire was administered to Masters's students that have registered at the university since 2012. This research used a mixed-methods approach which includes both qualitative and quantitative research and used a structured questionnaire to collect data. The findings of this study have highlighted that work commitment, supervisor relationship, lack of time management, and the fact that research is a grey area as factors that affected throughput rate of postgraduate students at the University of Technology. Based on the findings and conclusions of the study, it is recommended that more support should be provided to those students that are struggling with work commitments, relationships with supervisors should be encouraged and enhanced, use of planners should be encouraged by breaking down the research into milestones and enforcing timeframes with major consequences to tackle time management and for those that are struggling with the research part of their studies, more exposure of research at the undergraduate level is required.

Universities in South Africa are faced with low student success and throughput rates. These challenges go beyond the strength of the available tools, yet universities continue to use the same tools in addressing their challenges and yet they expect different outcomes. As a result, universities are taking steps towards improving their students’ performance. In addressing these challenges, several universities have taken progressive steps; moving towards a digitalisation of education to apply data-driven decisions. So far, this has been a positive move towards addressing some of the challenges that are contributing to low student performance. This study aims to investigate the potential of introducing learning analytics as a tool to analyse student data and to respond to the low student performances faced by South African universities. Learning analytics is an emerging field with the potential to enable higher education institutions to gather information and thus provide an understanding of students’ learning needs, and to use this to improve student performance and throughput. Learning analytics has been studied and implemented in other countries, such as the United Kingdom, Australia, and other parts of Europe. In these countries, learning analytics as one of the systematic ways of analysing data, has been reported to have the ability to improve student success and throughput. It also provides an opportunity for the early identification of students who are at risk. Among other things facing the universities of South Africa, are the factors mentioned above. Informed by the background explained above, the main question of the study is: How will the introduction of learning analytics help South African universities to improve student success and throughput rate? To respond to this question, South African Technology Network (SATN) was used as case study and thematic analysis was applied to analyse the collected data.