FoodChoices(Q):Exploring the design of a serious game proxy for Likert-style survey questionnaires

Rogoda, Kamil and Daniszewski, Piotr and Florowski, Kamil and Mathur, Rishabh and Amouzgar, Kourosh and Mackenzie, James and Sauvé, Kim and Karnik, Abe (2022) FoodChoices(Q):Exploring the design of a serious game proxy for Likert-style survey questionnaires. Proceedings of the ACM on Human-Computer Interaction, 6 (CHIPLA). (In Press)

[img]
Text (FoodChoices v0.71-OA)
FoodChoices_v0.71_OA.pdf - Accepted Version
Restricted to Repository staff only until 2 November 2022.
Available under License Creative Commons Attribution-NonCommercial.

Download (801kB)

Abstract

Likert-style questionnaires and surveys are commonly used tools for research. To alleviate survey-fatigue, researchers have explored gamification routes to increase engagement and lower drop-outs. However, these attempts still rely on direct use of questionnaire text and focus on creating engagement around the actual activity and do not fully alleviate the challenges of filling survey. In this paper, we explore an alternative approach involving the use of a serious game to capture user responses through in-game activities rather than direct questions. We chose the Food Choice Questionnaire (FCQ) and explored the design challenges of creating a serious game which deploys a sub-sample of the FCQ questions as four mini-game activities. The player actions and decisions are used to compute a result which is compared with their FCQ responses. We demonstrate the method to evaluate the equivalence of game results to the questionnaire responses. We discuss how future serious games can be designed and evaluated to generate similar outcomes while avoiding potential pitfalls through design and analysis.

Item Type:
Journal Article
Journal or Publication Title:
Proceedings of the ACM on Human-Computer Interaction
Additional Information:
© ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the ACM on Human-Computer Interaction, 6, CHI PLAY, November 2022 https://dl.acm.org/doi/10.1145/3549499
ID Code:
174606
Deposited By:
Deposited On:
15 Aug 2022 13:20
Refereed?:
Yes
Published?:
In Press
Last Modified:
15 Aug 2022 13:20