2025
Vahlo, Jukka; Tuuri, Kai
Validating Motives of Autonomous Players (MAP) inventory : a bottom-up model of general motivational factors to videogame play Journal Article
In: User Modeling and User-Adapted Interaction, vol. 35, 2025, ISSN: 0924-1868.
Abstract | Links | Tags: Factor analysis, Human-computer interaction, Motivation, Scale validation, Videogames
@article{Vahlo2025,
title = {Validating Motives of Autonomous Players (MAP) inventory : a bottom-up model of general motivational factors to videogame play},
author = {Jukka Vahlo and Kai Tuuri },
url = {https://doi.org/10.1007/s11257-025-09431-7
https://link.springer.com/article/10.1007/s11257-025-09431-7},
doi = {10.1007/s11257-025-09431-7},
issn = {0924-1868},
year = {2025},
date = {2025-03-30},
urldate = {2025-03-30},
journal = {User Modeling and User-Adapted Interaction},
volume = {35},
abstract = {In this study, we develop and validate Motives of Autonomous Players (MAP) inventory. Several models on videogame motives have been published recently, but typically these models focus either on specific videogame types, on individual games, or on a particular theory on human motivation. The MAP model takes an integrative approach that considers why people play games in general. This is done by adopting an inductive bottom-up research attitude and by focusing on motives that can be argued to be broadly applicable for all kinds of videogames, ranging from casual mobile games to massively multiplayer online role-playing games. Since the MAP model is based on extensive player data that represent a great variety of player motives, the results are widely applicable in player modeling and in understanding player–game interaction at large. The initial MAP model was developed by analyzing open-ended gaming motive descriptions (N 1,648) by a content analysis procedure. A preliminary 101-item MAP inventory was included in a UK-based survey (N 600). A nine-factor model was identified and further validated as a 34-item version by making a confirmatory factor analysis with a USA-based survey data (N 600). Additional analyses on construct validity were performed for investigating how motives to play videogames predict players’ game enjoyment factors that were kept analytically distinct from general motivational factors to play videogames.},
keywords = {Factor analysis, Human-computer interaction, Motivation, Scale validation, Videogames},
pubstate = {published},
tppubtype = {article}
}
In this study, we develop and validate Motives of Autonomous Players (MAP) inventory. Several models on videogame motives have been published recently, but typically these models focus either on specific videogame types, on individual games, or on a particular theory on human motivation. The MAP model takes an integrative approach that considers why people play games in general. This is done by adopting an inductive bottom-up research attitude and by focusing on motives that can be argued to be broadly applicable for all kinds of videogames, ranging from casual mobile games to massively multiplayer online role-playing games. Since the MAP model is based on extensive player data that represent a great variety of player motives, the results are widely applicable in player modeling and in understanding player–game interaction at large. The initial MAP model was developed by analyzing open-ended gaming motive descriptions (N 1,648) by a content analysis procedure. A preliminary 101-item MAP inventory was included in a UK-based survey (N 600). A nine-factor model was identified and further validated as a 34-item version by making a confirmatory factor analysis with a USA-based survey data (N 600). Additional analyses on construct validity were performed for investigating how motives to play videogames predict players’ game enjoyment factors that were kept analytically distinct from general motivational factors to play videogames.
2022
Tuuri, Kai; Vahlo, Jukka
Discovering the Motivational Constitution of ‘Playing Games for Fun’ Proceedings Article
In: Göbl, Barbara; van der Spek, Erik; Baalsrud Hauge, Jannicke; McCall, Rod (Ed.): Entertainment Computing – ICEC 2022., Springer International Publishing, 2022, ISSN: 0302-9743.
Abstract | Links | Tags: Fun, Gameplay, Motivation, Self-determination
@inproceedings{Tuuri2022,
title = {Discovering the Motivational Constitution of ‘Playing Games for Fun’},
author = {Kai Tuuri and Jukka Vahlo},
editor = {Barbara Göbl and Erik van der Spek and Baalsrud Hauge, Jannicke and Rod McCall},
url = {https://link.springer.com/chapter/10.1007/978-3-031-20212-4_3},
doi = {https://doi.org/10.1007/978-3-031-20212-4_3},
issn = {0302-9743},
year = {2022},
date = {2022-10-24},
urldate = {2022-10-24},
booktitle = {Entertainment Computing – ICEC 2022.},
issuetitle = {21st IFIP TC 14 International Conference, ICEC 2022},
journal = {Lecture Notes in Computer Science},
volume = {13477},
publisher = {Springer International Publishing},
abstract = {Regardless of its all-encompassing and ubiquitous nature, game and play researchers have often steered away from applying fun as a research concept. If a concept seems to be associated with everything, it logically follows that the concept lacks explanatory power. In this paper, we do not merely settle for the blunt conclusion that fun is not an interesting research concept. Rather we start to explore the phenomenon of fun by approaching it through three lenses: motivation to play, gameplay experience, and psychological need satisfaction. By analyzing two large survey samples collected in Finland (N = 879) and South-Korea (N = 1519), we cluster survey participants into player types according to their gameplay motivations. It is revealed that all players are more motivated by fun than by other need-based gaming motives, but also that a significant minority of players are only motivated by fun. By studying player preferences of the player types, it is furthermore highlighted that these Fun-Seekers generally dislike most gameplay activities and differ from other player types also regarding their genre play habits. Practical and theoretical implications of these findings are discussed.},
keywords = {Fun, Gameplay, Motivation, Self-determination},
pubstate = {published},
tppubtype = {inproceedings}
}
Regardless of its all-encompassing and ubiquitous nature, game and play researchers have often steered away from applying fun as a research concept. If a concept seems to be associated with everything, it logically follows that the concept lacks explanatory power. In this paper, we do not merely settle for the blunt conclusion that fun is not an interesting research concept. Rather we start to explore the phenomenon of fun by approaching it through three lenses: motivation to play, gameplay experience, and psychological need satisfaction. By analyzing two large survey samples collected in Finland (N = 879) and South-Korea (N = 1519), we cluster survey participants into player types according to their gameplay motivations. It is revealed that all players are more motivated by fun than by other need-based gaming motives, but also that a significant minority of players are only motivated by fun. By studying player preferences of the player types, it is furthermore highlighted that these Fun-Seekers generally dislike most gameplay activities and differ from other player types also regarding their genre play habits. Practical and theoretical implications of these findings are discussed.
Vahlo, Jukka; Tuuri, Kai; Välisalo, Tanja
Exploring Gameful Motivation of Autonomous Learners Journal Article
In: Frontiers in Psychology, vol. 13, 2022, ISSN: 1664-1078.
Abstract | Links | Tags: Autonomous learner, Engagement, Games, Motivation, Motives, Online learning, Playfulness, Self-determination
@article{Vahlo2022b,
title = {Exploring Gameful Motivation of Autonomous Learners},
author = {Jukka Vahlo and Kai Tuuri and Tanja Välisalo},
url = {http://urn.fi/URN:NBN:fi:jyu-202202281734},
doi = {10.3389/fpsyg.2022.825840},
issn = {1664-1078},
year = {2022},
date = {2022-02-25},
urldate = {2022-02-25},
journal = {Frontiers in Psychology},
volume = {13},
abstract = {In this explorative study, we investigated motives of autonomous learners to participate in an online course, and how these motives are related to gameplay motivations, engagement in the course experience, and learning outcomes. The guiding premise for the study has been the idea that learning and game playing carry phenomenal similarities that could be revealed by scrutinizing motives for participating in a massive open online course that does not involve any intentionally game-like features. The research was conducted by analyzing survey data (N = 705) collected from individuals who had voluntarily participated in an open online course about artificial intelligence and its societal impact. The survey included an explorative Motives for Autonomous Learning (MAL) inventory. Exploratory factor analysis suggested that the MAL inventory consisted of six dimensions out of which four were consistent with factors that earlier research has associated with motives to engage with video games. Of the identified factors, the dimension that most clearly described autonomous and playful predispositions was found to be a main precedent for both experienced gamefulness of the learning experience and positive learning outcomes. In all, the results of this study demonstrated that playfulness and autonomy were both prominent and significant factors across the whole learning process.},
keywords = {Autonomous learner, Engagement, Games, Motivation, Motives, Online learning, Playfulness, Self-determination},
pubstate = {published},
tppubtype = {article}
}
In this explorative study, we investigated motives of autonomous learners to participate in an online course, and how these motives are related to gameplay motivations, engagement in the course experience, and learning outcomes. The guiding premise for the study has been the idea that learning and game playing carry phenomenal similarities that could be revealed by scrutinizing motives for participating in a massive open online course that does not involve any intentionally game-like features. The research was conducted by analyzing survey data (N = 705) collected from individuals who had voluntarily participated in an open online course about artificial intelligence and its societal impact. The survey included an explorative Motives for Autonomous Learning (MAL) inventory. Exploratory factor analysis suggested that the MAL inventory consisted of six dimensions out of which four were consistent with factors that earlier research has associated with motives to engage with video games. Of the identified factors, the dimension that most clearly described autonomous and playful predispositions was found to be a main precedent for both experienced gamefulness of the learning experience and positive learning outcomes. In all, the results of this study demonstrated that playfulness and autonomy were both prominent and significant factors across the whole learning process.