Assessment for Learning: The University of Toronto Temerty Faculty of Medicine M.D. Program Experience - Glendon R. Tait; Kulamakan Mahan Kulasegaram (MDPI AG, 2022)
(1) Background: Programmatic assessment optimizes the coaching, learning, and decision-making functions of assessment. It utilizes multiple data points, fit for purpose, which on their own guide learning, but taken together form the basis of holistic decision making. While they are agreed on principles, implementation varies according to context. (2) Context: The University of Toronto MD program implemented programmatic assessment as part of a major curriculum renewal. (3) Design and implementation: This paper, structured around best practices in programmatic assessment, describes the implementation of the University of Toronto MD program, one of Canada's largest. The case study illustrates the components of the programmatic assessment framework, tracking and making sense of data, how academic decisions are made, and how data guide coaching and tailored support and learning plans for learners. (4) Lessons learned: Key implementation lessons are discussed, including the role of context, resources, alignment with curriculum renewal, and the role of faculty development and program evaluation. (5) Conclusions: Large-scale programmatic assessment implementation is resource intensive and requires commitment both initially and on a sustained basis, requiring ongoing improvement and steadfast championing of the cause of optimally leveraging the learning function of assessment.