Adapting Cognitive Walkthrough to Support Game Based Learning Design

Adapting Cognitive Walkthrough to Support Game Based Learning Design

David Farrell, David C. Moffat
Copyright: © 2014 |Pages: 12
DOI: 10.4018/ijgbl.2014070103
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

For any given Game Based Learning (GBL) project to be successful, the player must learn something. Designers may base their work on pedagogical research, but actual game design is still largely driven by intuition. People are famously poor at unsupported methodical thinking and relying so much on instinct is an obvious weak point in GBL design practice. Cognitive Walkthrough (CW) is a user-interface design technique that helps designers model how a type of user will understand an interface. The authors suggest that CW should be extended for use in any context where a designer must model a user's thinking. They present an extension of CW that is suitable for constructivist GBL and apply it to a previously evaluated game to understand why one section of the game was more successful than another. The CW extension explains hitherto puzzling results and suggests further development of CWs for designer support may be beneficial.
Article Preview
Top

The E-Bug Platform Game

e-Bug was a European Commission, DG-SANCO funded project that aimed to improve young people’s understanding of microbes, hygiene and antibiotics, with the ultimate aim of reducing antibiotic misuse. As part of e-Bug, two games were designed that could be included in, or work independently of, curricula across 18 partner countries in Europe. One of those games was the e-Bug Platform Game, designed for primary school children aged 9-11. Because the game’s goal was to teach the player, it was important that it be based on good pedagogy.

Complete Article List

Search this Journal:
Reset
Volume 14: 1 Issue (2024)
Volume 13: 1 Issue (2023)
Volume 12: 4 Issues (2022): 1 Released, 3 Forthcoming
Volume 11: 4 Issues (2021)
Volume 10: 4 Issues (2020)
Volume 9: 4 Issues (2019)
Volume 8: 4 Issues (2018)
Volume 7: 4 Issues (2017)
Volume 6: 4 Issues (2016)
Volume 5: 4 Issues (2015)
Volume 4: 4 Issues (2014)
Volume 3: 4 Issues (2013)
Volume 2: 4 Issues (2012)
Volume 1: 4 Issues (2011)
View Complete Journal Contents Listing