Enabling Curriculum Exploration through Linked Data Visualizations

Tracking #: 1629-2841

This paper is currently under review
Authors: 
Fouad Zablith
Neil Yorke-Smith
Bijan Azad

Responsible editor: 
Guest Editors IE of Semantic Data 2017

Submission type: 
Application Report
Abstract: 
This article investigates the application of linked data to enable better exploration of curriculum information. We propose a linked data model that extends existing vocabularies in the academic domain to represent the concepts exchanged beyond the topical coverage of courses. We collaboratively build the linked data graph, extract the data, and create six different visualizations of the curriculum. We assess the impact of the visualizations through a set of interviews involving faculty volunteers. The collected interview data reveals that the presence of the linked data visualizations enables emerging exploration paths: in addition to the expected content-related exploration patterns, the volunteer users highlighted process-related exploration that includes for example better collaboration with colleagues, course delivery and design. While most of existing efforts in linked data focus on generating and interlinking data at a large, web scale, this work shows how linked data can transform the internal practices of curriculum design and delivery.
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