{"id":{"repo_id":"western-cape","oai_identifier":"oai:uwcscholar.uwc.ac.za:10566/20811"},"canonical_url":"https://search.dev.ndltd.org/etd/western-cape/oai:uwcscholar.uwc.ac.za:10566/20811","repository":{"repo_id":"western-cape","name":"University of the Western Cape","base_url":"https://uwcscholar.uwc.ac.za:8443/server/oai/request"},"display":{"title":"A framework for data-driven decision-making at a South African higher education institution","abstract":"Data-driven decision-making (D3M) has practical benefits to higher education institutions (HEIs), but its adoption and use in South African HEIs are still low. This low adoption is attributed to various reasons based on decision-makers’ perceptions, expectations and experiences of data-driven decision-making tools and techniques. This thesis presents an analysis of data-driven decision-making (D3M) in a South African Higher Education Institution, addressing the need for effective decision-making approaches to enhance student experiences and institutional performance. The purpose of this study was to identify factors that influence the adoption of D3M and explore strategies for integrating D3M tools and approaches to improve educational outcomes. this study aimed to propose a framework for improving the adoption and use of data to make informed decisions at a South African HEI by addressing decision-makers' perceptions, expectations and experiences, which, in turn, will enhance student experiences. This aim is articulated through three primary objectives: first, to explore ways in which D3M can enhance student experiences; second, to investigate the institutional and individual factors affecting the adoption of D3M; and third, to analyse the perceptions, experiences, and expectations of decision-makers in utilising a data- driven approach. The study utilised the exploratory sequential mixed-methods research methodology, incorporating interviews and a survey to gather data from personnel within the institution.","abstract_html":"Data-driven decision-making (D3M) has practical benefits to higher education institutions (HEIs), but its adoption and use in South African HEIs are still low. This low adoption is attributed to various reasons based on decision-makers’ perceptions, expectations and experiences of data-driven decision-making tools and techniques. This thesis presents an analysis of data-driven decision-making (D3M) in a South African Higher Education Institution, addressing the need for effective decision-making approaches to enhance student experiences and institutional performance. The purpose of this study was to identify factors that influence the adoption of D3M and explore strategies for integrating D3M tools and approaches to improve educational outcomes. this study aimed to propose a framework for improving the adoption and use of data to make informed decisions at a South African HEI by addressing decision-makers' perceptions, expectations and experiences, which, in turn, will enhance student experiences. This aim is articulated through three primary objectives: first, to explore ways in which D3M can enhance student experiences; second, to investigate the institutional and individual factors affecting the adoption of D3M; and third, to analyse the perceptions, experiences, and expectations of decision-makers in utilising a data- driven approach. 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