Abstract
Play-testing of digital games is a crucial part of any game development process, used to gather feedback about the game and correct any existing and potential flaws with the design. However, due to the nature of human subject testing, the feedback being collected in such experiments is prone to biases. Players' expectations play a great role in dictating their gaming experience, which means the information players receive before trying a new game, as well as the knowledge they already possess, may affect their perception and experience of the game. Two studies were conducted in order to evaluate how priming players to expect a game technology can positively influence their experience. The results supported the hypothesis that even basic instructions can change players' perception of the game, and lead to a higher level of perceived immersion when knowing that the game contains an improved feature, the adaptive artificial intelligence (AI), while it is not present in the game.
Original language | English |
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Title of host publication | CHI PLAY 2015 - Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play |
Publisher | ACM |
Pages | 23-33 |
Number of pages | 11 |
ISBN (Print) | 9781450334662 |
DOIs | |
Publication status | Published - 5 Oct 2015 |
Event | 2nd ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2015 - London, United Kingdom Duration: 5 Oct 2015 → 7 Oct 2015 |
Conference
Conference | 2nd ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2015 |
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Country/Territory | United Kingdom |
City | London |
Period | 5/10/15 → 7/10/15 |
Keywords
- Adaptive artificial intelligence
- Biasing effects
- Immersion
- Player experience
- Player knowledge
Profiles
Datasets
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Alena Denisova: PhD 4 Placebo Effect (between)
Denisova, A. (Creator) & Cairns, P. A. (Creator), University of York, Mar 2018
DOI: 10.15124/d723f438-d4c8-4d53-964b-d4ffd30ac072
Dataset
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Alena Denisova: PhD 3 Placebo Effect
Denisova, A. (Creator) & Cairns, P. A. (Creator), University of York, Feb 2018
DOI: 10.15124/1b664aa5-e93b-4716-a679-feaacbfb769a
Dataset