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Measuring the experience of playing self-paced games

Cutting, Joe (2018) Measuring the experience of playing self-paced games. PhD thesis, University of York.

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Self-paced games are digital games which do not require players to make a move within a particular period of time, so the game can be played at whichever speed the player desires. Game experience measures can help game designers and increase understanding of how games create engagement. This thesis aimed to develop new measures of the experience of playing self-paced games. It investigated two possible measures; measuring cognitive load using pupil dilation and measuring attention using irrelevant distractor images. The first approach found a significant difference in pupil dilation between easy and hard variants of a task taken from the game Two Dots. In a subsequent study, participants played three different versions of Two Dots – one of which required no cognitive effort. There was no significant difference in pupil dilation due to cognitive load between the games. It seems likely that although players could use sustained cognitive effort to play the game, they chose not to, and use other strategies instead. I concluded that pupil dilation is unlikely to be an effective measure of game experience. The second approach developed a new measure known as the distractor recognition paradigm. This measure surrounds the game with constantly changing irrelevant images. After playing, participants are tested on how many of these images they recognise. An initial study found a significant difference in images recognised between two very different versions of the game Two Dots. There was also a significant difference in distractors recognised between three more similar games. This was found to be a stronger measure of game attention than using eye tracking and also found to be effective if the distractor images were placed inside the game graphics. This approach succeeded in the aim of the thesis which was to find a new measure of the experience of playing self-paced games.

Item Type: Thesis (PhD)
Related URLs:
Academic Units: The University of York > Computer Science (York)
Identification Number/EthosID: uk.bl.ethos.778909
Depositing User: Dr Joe Cutting
Date Deposited: 04 Jun 2019 13:26
Last Modified: 19 Feb 2020 13:08
URI: http://etheses.whiterose.ac.uk/id/eprint/24103

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