2020
Vahlo, Jukka; Karhulahti, Veli-Matti
Challenge Types in Gaming Validation of Video Game Challenge Inventory (CHA) Journal Article
In: International Journal of Human-Computer Studies, vol. 143, no. 102473, pp. 1-13, 2020, ISSN: 1071-5819.
Abstract | Links | Tags: Challenge, Confirmatory factor analysis, Exploratory factor analysis, Player preferences, Scale validation, Survey
@article{Vahlo2020,
title = {Challenge Types in Gaming Validation of Video Game Challenge Inventory (CHA)},
author = {Jukka Vahlo and Veli-Matti Karhulahti},
url = {https://www.sciencedirect.com/science/article/pii/S1071581920300756},
doi = {10.1016/j.ijhcs.2020.102473},
issn = {1071-5819},
year = {2020},
date = {2020-11-01},
journal = {International Journal of Human-Computer Studies},
volume = {143},
number = {102473},
pages = {1-13},
abstract = {Challenge is a key motivation for videogame play. But what kind of challenge types videogames include, and which of them players prefer? This article helps to answer the above questions by developing and validating Videogame Challenge Inventory (CHA), a psychometrically sound measurement for investigating players’ challenge preferences in videogames. Based on a review of literature, we developed a 38-item version of CHA that was included in a social media user survey (N = 813). An exploratory factor analysis (EFA) revealed a latent structure of five challenge types: Physical, Analytical, Socioemotional, Insight, and Foresight. CHA was amended in another EFA with USA-based survey data (N = 536). The second EFA suggested a four-factor structure similar to the first EFA. A confirmatory factor analysis was executed after an item screening process with a 12-item version of CHA via UK-based survey data (N = 1,463). The 12-CHA had an acceptable fit to the data, and the model passed construct, convergent, and discriminant validity tests. The usefulness of the validated 12-CHA is shown by connecting the discovered challenges and their preferences to known videogame play motivations and to habits of playing specific videogame genres.},
keywords = {Challenge, Confirmatory factor analysis, Exploratory factor analysis, Player preferences, Scale validation, Survey},
pubstate = {published},
tppubtype = {article}
}
Challenge is a key motivation for videogame play. But what kind of challenge types videogames include, and which of them players prefer? This article helps to answer the above questions by developing and validating Videogame Challenge Inventory (CHA), a psychometrically sound measurement for investigating players’ challenge preferences in videogames. Based on a review of literature, we developed a 38-item version of CHA that was included in a social media user survey (N = 813). An exploratory factor analysis (EFA) revealed a latent structure of five challenge types: Physical, Analytical, Socioemotional, Insight, and Foresight. CHA was amended in another EFA with USA-based survey data (N = 536). The second EFA suggested a four-factor structure similar to the first EFA. A confirmatory factor analysis was executed after an item screening process with a 12-item version of CHA via UK-based survey data (N = 1,463). The 12-CHA had an acceptable fit to the data, and the model passed construct, convergent, and discriminant validity tests. The usefulness of the validated 12-CHA is shown by connecting the discovered challenges and their preferences to known videogame play motivations and to habits of playing specific videogame genres.
2019
Vahlo, Jukka; Hamari, Juho
Five-Factor Inventory of Intrinsic Motivations to Gameplay (IMG) Proceedings Article
In: Bui, Tung (Ed.): Proceedings of the 52nd Hawaii International Conference on System Sciences, pp. 2476-2485, HICSS, 2019, ISBN: 978-0-9981331-2-6.
Abstract | Links | Tags: Confirmatory factor analysis, Intrinsic motivation, Motivations to play, Scale validation, Self-determination theory, Survey
@inproceedings{Vahlo2019,
title = {Five-Factor Inventory of Intrinsic Motivations to Gameplay (IMG)},
author = {Jukka Vahlo and Juho Hamari},
editor = {Tung Bui},
url = {https://urn.fi/URN:NBN:fi:tuni-201910244074},
doi = {doi:10.24251/HICSS.2019.298},
isbn = {978-0-9981331-2-6},
year = {2019},
date = {2019-01-08},
urldate = {2019-01-08},
booktitle = {Proceedings of the 52nd Hawaii International Conference on System Sciences},
pages = {2476-2485},
publisher = {HICSS},
abstract = {In this study, we develop and validate Intrinsic Motivations to Gameplay (IMG) inventory. In Study 1, psychometric properties of a preliminary 10-item version of IMG were investigated by employing an online survey data collected among Finnish and Danish population (N = 2,205). In Study 2, a 23-item version of IMG was developed based on further
interview data and survey data collected among Canadian population (N = 1,322). The 23-item version of IMG revealed five factors of intrinsic motivations for gameplay: Relatedness, Autonomy, Competence, Immersion, and Fun. In Study 3, a third survey was conducted among Finnish and Japanese participants (N = 2,057) to design a Self-Determination theory (SDT) informed confirmatory factor analysis (CFA). The CFA validated a 15-item version of IMG inventory, which can be utilized widely in studies on digital gaming and gamification to better understand player preferences.},
keywords = {Confirmatory factor analysis, Intrinsic motivation, Motivations to play, Scale validation, Self-determination theory, Survey},
pubstate = {published},
tppubtype = {inproceedings}
}
In this study, we develop and validate Intrinsic Motivations to Gameplay (IMG) inventory. In Study 1, psychometric properties of a preliminary 10-item version of IMG were investigated by employing an online survey data collected among Finnish and Danish population (N = 2,205). In Study 2, a 23-item version of IMG was developed based on further
interview data and survey data collected among Canadian population (N = 1,322). The 23-item version of IMG revealed five factors of intrinsic motivations for gameplay: Relatedness, Autonomy, Competence, Immersion, and Fun. In Study 3, a third survey was conducted among Finnish and Japanese participants (N = 2,057) to design a Self-Determination theory (SDT) informed confirmatory factor analysis (CFA). The CFA validated a 15-item version of IMG inventory, which can be utilized widely in studies on digital gaming and gamification to better understand player preferences.
interview data and survey data collected among Canadian population (N = 1,322). The 23-item version of IMG revealed five factors of intrinsic motivations for gameplay: Relatedness, Autonomy, Competence, Immersion, and Fun. In Study 3, a third survey was conducted among Finnish and Japanese participants (N = 2,057) to design a Self-Determination theory (SDT) informed confirmatory factor analysis (CFA). The CFA validated a 15-item version of IMG inventory, which can be utilized widely in studies on digital gaming and gamification to better understand player preferences.
2018
Vahlo, Jukka; Smed, Jouni; Koponen, Aki
Validating gameplay activity inventory (GAIN) for modeling player profiles Journal Article
In: User Modeling and User-Adapted Interaction, vol. 28, no. 4–5, pp. 425–453, 2018, ISSN: 15731391.
Abstract | Links | Tags: Confirmatory factor analysis, Digital games, Media choice, Player profiles, Scale development, Scale validation
@article{Vahlo2018a,
title = {Validating gameplay activity inventory (GAIN) for modeling player profiles},
author = {Jukka Vahlo and Jouni Smed and Aki Koponen},
doi = {10.1007/s11257-018-9212-y},
issn = {15731391},
year = {2018},
date = {2018-11-13},
urldate = {2018-11-13},
journal = {User Modeling and User-Adapted Interaction},
volume = {28},
number = {4–5},
pages = {425–453},
publisher = {Springer Netherlands},
address = {Dordrecht},
abstract = {In the present study, we validated Gameplay Activity Inventory (GAIN), a short and psychometrically sound instrument for measuring players' gameplay preferences and modeling player profiles. In Study 1, participants in Finland (N= 879) responded to a 52-item version of GAIN. An exploratory factor analysis was used to identify five latent factors of gameplay activity appreciation: Aggression, Management, Exploration, Coordination, and Caretaking. In Study 2, respondents in Canada (N= 1322) and Japan (N= 1178) responded to GAIN, and the factor structure of a 15-item version was examined using a Confirmatory Factor Analysis. The results showed that the short version of GAIN has good construct validity, convergent validity, and discriminant validity in Japan and in Canada. We demonstrated the usefulness of GAIN by conducting a cluster analysis to identify player types that differ in both demographics and game choice. GAIN can be used in research as a tool for investigating player profiles. Game companies, publishers and analysts can utilize GAIN in player-centric game development and targeted marketing and in generating personalized game recommendations.},
keywords = {Confirmatory factor analysis, Digital games, Media choice, Player profiles, Scale development, Scale validation},
pubstate = {published},
tppubtype = {article}
}
In the present study, we validated Gameplay Activity Inventory (GAIN), a short and psychometrically sound instrument for measuring players' gameplay preferences and modeling player profiles. In Study 1, participants in Finland (N= 879) responded to a 52-item version of GAIN. An exploratory factor analysis was used to identify five latent factors of gameplay activity appreciation: Aggression, Management, Exploration, Coordination, and Caretaking. In Study 2, respondents in Canada (N= 1322) and Japan (N= 1178) responded to GAIN, and the factor structure of a 15-item version was examined using a Confirmatory Factor Analysis. The results showed that the short version of GAIN has good construct validity, convergent validity, and discriminant validity in Japan and in Canada. We demonstrated the usefulness of GAIN by conducting a cluster analysis to identify player types that differ in both demographics and game choice. GAIN can be used in research as a tool for investigating player profiles. Game companies, publishers and analysts can utilize GAIN in player-centric game development and targeted marketing and in generating personalized game recommendations.