A Computational Intelligence Tool to Support the Design of Outcome- Based Teaching
The use of models, frameworks, and toolkits in learning design serve to support teaching practitioners in producing well-structured learning designs for students. However, existing learning design tools inherently lack an objective metric system which is able to measure the degree to which an educational design is well-formed according to either the principles of constructive alignment or more generally design practices that students find satisfactory in practice. Such a metric system, that could integrate measures of educational theory and practice, would enable teaching practitioners to make more informed design decisions such as which profile of activities/assessments to use for a particular set of learning outcomes. This paper presents the first computational intelligence tool that measures educational design quality in a way that is underpinned by both the theoretical principles of constructive alignment and how it is used in practice. Furthermore, the alignment metrics computed are calibrated by student satisfaction scores to promote those structures that are preferred in practice rather than from a theoretical standpoint thus offering more pragmatic and realistic design solutions.
Published in: Canada International Conference on Education, 2017
- Date of Conference: 26-29 June, 2017
- DOI: 10.2053/CICE.2017.0189
- Electronic ISBN: 978-1-908320-83-4
- Conference Location: University of Toronto Mississauga, Canada