demonstrated student performance

Educators are faced with many challenging questions in designing an eective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top-performing group? How does the intended learning specication compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specication in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing condence and reliability metrics for each of these mappings; and nally, comparing and reecting on the learning specication against actual student performance. We present a webbased implementation of the model, and validate it by mapping the nal exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom’s Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource.