Maximising gain for minimal pain: Utilising natural game mechanics

Gordon, Neil; Brayshaw, Mike; Grey, Simon

Abstract

This paper considers the application of natural games mechanics within higher education as a vehicle to encourage student engagement and achievement of desired learning outcomes. It concludes with desiderata of features for a learning environment when used for assessment and a reflection on the gap between current and aspired learning provision. The context considered is higher (tertiary) education, where the aims are both to improve students’ engagement with course content and also to bring about potential changes in the students’ learning behaviour. Whilst traditional approaches to teaching and learning may focus on dealing with large classes, where the onus is frequently on efficiency and on the effectiveness of feedback in improving understanding and future performance, intelligent systems can provide technology to enable alternative methods that can cope with large classes that preserve the cost-benefits. However, such intelligent systems may also offer improved learning outcomes via a personalised learning experience. This paper looks to exploit particular properties which emerge from the game playing process and seek to engage them in a wider educational context. In particular we aim to use game engagement and Flow as natural dynamics that can be exploited in the learning experience.

Citation

Gordon, N., Brayshaw, M., & Grey, S. (2013). Maximising gain for minimal pain: Utilising natural game mechanics. Innovation in teaching and learning in information and computer sciences, 12(1), 27-38. https://doi.org/10.11120/ital.2013.00004

• Journal Article Type: Article
• Acceptance Date: Jul 15, 2013
• Online Publication Date: Dec 15, 2015
• Publication Date: 2013-11
• Deposit Date: Oct 7, 2015
• Publicly Available Date: Nov 23, 2017
• Journal: ITALICS
• Electronic ISSN: 1473-7507
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 1
• Pages: 27-38
• DOI: https://doi.org/10.11120/ital.2013.00004
• Keywords: Game mechanics; Gamification; Intelligent learning systems; Technology enhanced learning
• Public URL: https://hull-repository.worktribe.com/output/379532
• Publisher URL: https://www.heacademy.ac.uk/sites/default/files/ital.12.1d.pdf
• Additional Information: This is the authors' accepted manuscript of an article published in: ITALICS, 2013, v.12, issue 1
• Contract Date: Nov 23, 2017