Routing in intended learning outcome networks

Abstract

This thesis explores the potential that Intended Learning Outcomes (ILOs) networks have to support learning and teaching, particularly for supporting self-directed learners. As a contribution to knowledge, this work presents evidence that suggests algorithms traversing ILO networks can produce learning routes that are similar to routes produced by teachers.

For this thesis, an ILO network comprised of cognitive learning outcomes in the area of music theory was created, and algorithms to traverse the network were designed. Trials were undertaken to determine the interpretability of the ILOs and the ILO network to non-subject matter experts. Further trials explored to what degree the routes produced by the traversal algorithms differed from routes produced by contemporary teaching professionals.

Findings indicate that ILOs and ILO networks were understood well by the learners involved in the first trial. Results from the second trial suggest that the algorithms produced similar routes to those produced by teachers, but conclude that the metrics and the route lengths may need to be refined in order to better reflect the scale of educational undertakings pursued today.

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