Mastery Learning: Improving the Model

Abstract

In this paper, we report on developments in the Mastery Learning (ML) curriculum and assessment model that has been successfully implemented in a metropolitan university for teaching first-year mathematics. Initial responses to ML were positive; however, we ask whether the nature of the ML tests encourages a focus on shallow learning of procedures, and whether the structure of the assessment regime provides sufficient motivation for learning more complex problem solving. We analysed assessment data, as well as student reports and survey responses in an attempt to answer these questions