Evaluation of a learning outcomes taxonomy to support autonomous classification of instructional activities

Abstract

With an increased focus on assuring the quality of student achievement in higher education, there is a commensurate need for tools to assist academics in understanding the nature of assessment and how it can provide evidence of student learning outcomes. This paper describes research conducted the Instructional Activity Matrix; a taxonomy that was developed as the basis of a learning support tool, Maestro, that automatically analyses outcomes and assessment statements to show the cognitive level and nature of knowledge inherent in them. Findings indicate that the matrix is a valid tool for defining the nature of learning outcomes and had value in clarifying the nature of assessment and outcomes. However, issues identified with the inherent ambiguity of some instructional statements and their contextually-laden language provided insights into how Maestro will need to be refined to provide appropriate support for teachers, with a range of experience across multiple disciplines.