AN INDUCTIVELY DERIVED RESEARCH FRAMEWORK FOR STUDENT SATISFACTION IN ODL: THE HIGHER EDUCATION ENVIRONMENT

Abstract

Student satisfaction, as a key psychological-affective outcome of tertiary education, is a direct measure of the success of Open Distance Learning (ODL). It is therefore vital for ODL Higher Education Institutions to assess and improve student satisfaction constantly. Existing theories on student satisfaction are mostly derived from deductive research, i.e. from research that considers the existing body of knowledge, followed by an investigation of a specific aspect or component, in order to reach a specific conclusion. We, however, maintain the inductive stance that a research framework for student satisfaction in ODL should be derived from students themselves. Accordingly, we purposively collected qualitative data from N=34 South African postgraduate ODL students, representative of various cultural language groups, with regard to student satisfaction. Supported by Atlas.ti, we composed an integrated dataset comprised of students’ responses to two focus-group interviews, as well as students’ written narratives in response to qualitative questions. Through meticulous qualitative data-analysis, we detected data categories, sub-categories, patterns and regularities in the integrated dataset. Theories and findings from the existing corpus of knowledge pertaining to student satisfaction in ODL illuminated our qualitative findings. This paper reports on the knowledge we gained from our participants pertaining to their student satisfaction with the Higher Education (HE) environment, the first of three main research components of an inductively derived research framework for student satisfaction in ODL.