When: Wednesday Oct 24th, 12pm
Where: DH Active Learning Space, Food Science Building 4.58
Presentations last ~30mins, followed by short discussion

A VIRTUAL REALITY GAME FOR TEACHING GRAPH THEORY:
A STUDY OF ITS EFFECTIVENESS IN IMPROVING OUTCOMES AND ENCOURAGING AUTONOMY

Larkin Cunningham

Abstract
A game was developed using virtual reality (VR) technologies to teach graph theory in a visual, hands-on way. An iterative model was devised to design, build and pilot the game. With virtual hands, learners were able to manipulate graphs in an immersive environment. The game guided the learner through the game’s mechanics and fundamental concepts of graph theory before presenting real-world examples of graph theory and progressively more difficult challenges to solve. Learners were also presented with a dashboard containing visualizations, such as progression of learning (mapped to Biggs’s SOLO taxonomy), badges and a leaderboard. A study was carried out with the purpose of: measuring the effectiveness of the game in teaching graph theory; measuring the game’s success from a universal design for learning standpoint; measuring how motivated learners were to play more games like it; discovering strategies employed by learners in an immersive VR environment; analysing gathered data to gain insights into how learners learned and solved challenges.

The presentation will show video of the VR game, examples of learning analytics visualizations and the mixed methods approach employing triangulation, will also be discussed.

About the Speaker
Larkin Cunningham is a lecturer in computer science in Cork Institute of Technology and is in the final stages of a PhD in Digital Humanities at UCC. He teaches numerous modules related to computer science, including games development, big data, agile project management, microservice architecture and more. In the coming years he plans to supervise technology enhanced learning PhD students in CIT with an emphasis on game based learning and learning analytics, as well as seeking funding for GBL / learning analytics projects.