Predicting Learning Outcomes in Distance Learning Universities: Perspectives from an Integrated Model

The progressive spread of online academic courses is a result of the flexible and customisable nature of the
related learning process, while some studies on students’ achievement in distance learning universities
have underlined retention as a priority issue for future research. Despite the number of studies that have
investigated specific variables related to online learning, there are no systemic reference models that
consider specific online environmental variables, IT competence and outcomes together. This paper offers
an integrated model to test the contribution of different variables in predicting student performance in
online academic courses, building on the literature on the digital learning environment and achievement.
The model, based on the initial Biggs’ 3P learning model, aims to evaluate technical competency and the
ability to self-manage as personal variables; furthermore, it proposes the analysis of a set of perceptions
related to course design. Through the proposed model, a student’s background, personal variables,
perception of the physical learning environment and perception of the course design can be utilized as
predictors of student performance. Future research should investigate the applicability of the model in
academic distance learning contexts.