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https://zone.biblio.laurentian.ca/handle/10219/3391
Titre: | Dynamic difficulty adjustment: using the Wizard of Oz method to investigate potential improvements through biofeedback |
Auteurs: | Horne, Stéphane Thomas |
Mots clés: | engagement;flow;dynamic difficulty adjustment;Wizard of Oz |
Date publié: | 19-déc-2018 |
Abstrait: | Engagement is a key factor to consider when developing video games. Flow theory—one of the required components of engagement—dictates that in order to achieve flow, there must be an adequate balance between the player’s skill level and the challenge they’re faced with. Consequently, game developers have created several AI systems to tailor a game’s difficulty to players’ skill levels, such as Dynamic Difficulty Adjustment (DDA). This system uses player performance as an indicator of their emotional state. However, this is not the most accurate measure. In this work, the Wizard of Oz method was used to determine if DDAs could elicit higher levels of engagement if given access to information relating to players’ emotional states, such as their facial expressions and body language. Results showed that there were no significant differences in engagement between the DDA and the Wizard |
URI: | https://zone.biblio.laurentian.ca/handle/10219/3391 |
Apparaît dans les collections: | Computational Sciences - Master's theses Master's Theses |
Fichiers dans cet item:
Fichier | Description | Taille | Format | |
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Stephane Horne - Thesis - Final Copy.pdf | 2.33 MB | Adobe PDF | Parcourir/Ouvrir |
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