Strengths-based analysis of student success in online courses

Abstract

The purpose of this research was to increase understanding of post-secondary student success in online courses by evaluating a contextually rich combination of personal, circumstantial, and course variables. A strengths-based perspective framed the investigation. Mixed-method data were collected and analyzed sequentially in three phases: two phases of quantitative collection and analysis were followed by qualitative interviews and comprehensive analysis. The study first used logistic regression to analyze existing data on more than 27,000 student enrollments, spanning a time period of four academic years. The second phase of research enhanced the modeling focused on a subset of the total population; students from a single semester were invited to complete an assessment of non-cognitive attributes and personal perceptions. Between the two phases, 28 discreet variables were analyzed. Results suggest that different combinations of variables may be effective in predicting success among students with varying levels of educational experience. This research produced preliminary predictive models for student success at each level of class standing. The study concluded with qualitative interviews designed to explain quantitative results more fully. Aligned with a strengths-based perspective, 12 successful students were asked to elaborate on factors impacting their success. Themes that emerged from the interviews were congruent with quantitative findings, providing practical examples of student and instructor actions that contribute to online student success.