Publications: Collection

Year 2015

Games User Research and Physiological Game Evaluation

@incollection{Nacke2015,
abstract = {This chapter introduces physiological measures for game evaluation in the context of games user research (GUR). GUR consists of more than playtesting game; it comprises a collection of methods that allow designers to bring their creations closer to the initial vision of the player experience. With the prices of physiological sensors falling, and the advancement of research in this area, physiological evaluation will soon become a standard tool in GUR and game evaluation. Since mixed-method approaches are of increasingly prominent value, this chapter describes core GUR methods with a special focus on physiological evaluation, keeping in mind both benefits and limitations of the approach in academic and industrial applications.},
author = {Nacke, Lennart E},
booktitle = {Game User Experience Evaluation},
chapter = {4},
doi = {10.1007/978-3-319-15985-0_4},
editor = {Bernhaupt, Regina},
isbn = {978-3-319-15985-0},
mendeley-groups = {HCI Games Group Publications},
pages = {63--86},
publisher = {Springer International Publishing},
title = {{Games User Research and Physiological Game Evaluation}},
url = {https://hcigames.com/download/games-user-research-and-physiological-game-evaluation},
year = {2015}
}

This chapter introduces physiological measures for game evaluation in the context of games user research (GUR). GUR consists of more than playtesting game; it comprises a collection of methods that allow designers to bring their creations closer to the initial vision of the player experience. With the prices of physiological sensors falling, and the advancement of research in this area, physiological evaluation will soon become a standard tool in GUR and game evaluation. Since mixed-method approaches are of increasingly prominent value, this chapter describes core GUR methods with a special focus on physiological evaluation, keeping in mind both benefits and limitations of the approach in academic and industrial applications.

Year 2013

An Introduction to Physiological Player Metrics for Evaluating Games

@incollection{nacke2013introduction,
Abstract = {Evaluating affective user experience in games is an important component of the growing field of game user research, because compelling gameplay experiences incorporate meaningful and, therefore, emotional player decisions. This makes evaluating player emotions and player visceral physiological reactions a fascinating field of study for game researchers. With their recent success in the human factors domain, physiological metrics, which complement game metrics, have been successfully used to study player engagement and emotion in research and industry. This chapter provides a brief introduction to and primer of physiological measures currently used in game research and discusses the benefits and challenges of this quantitative method of game user research.},
Author = {L. E. Nacke},
Booktitle = {Game analytics - maximizing the value of player data},
Chapter = {26},
Doi = {10.1007/978-1-4471-4769-5_26},
Editor = {M. {Seif El-Nasr}, A. Drachen, and A. Canossa},
Img = {http://hcigames.com/wp-content/uploads/2015/05/an_introduction_to_physiological_player_metrics_for_evaluating_games.png},
Isbn = {1447147685},
Pages = {585-619},
Publisher = {Springer London},
Title = {An Introduction to Physiological Player Metrics for Evaluating Games},
Url = {http://link.springer.com/chapter/10.1007/978-1-4471-4769-5_26},
Year = {2013},

Evaluating affective user experience in games is an important component of the growing field of game user research, because compelling gameplay experiences incorporate meaningful and, therefore, emotional player decisions. This makes evaluating player emotions and player visceral physiological reactions a fascinating field of study for game researchers. With their recent success in the human factors domain, physiological metrics, which complement game metrics, have been successfully used to study player engagement and emotion in research and industry. This chapter provides a brief introduction to and primer of physiological measures currently used in game research and discusses the benefits and challenges of this quantitative method of game user research.

Year 2011

BrainHex: Preliminary Results from a Neurobiological Gamer Typology Survey

@incollection{nacke2011brainhex,
Abstract = {This paper briefly presents a player satisfaction model called BrainHex, which was based on insights from neurobiological findings as well as the results from earlier demographic game design models (DGD1 and DGD2). The model presents seven different archetypes of players: Seeker, Survivor, Daredevil, Mastermind, Conqueror, Socialiser, and Achiever. We explain how each of these player archetypes relates to older player typologies (such as Myers-Briggs), and how each archetype characterizes a specific playing style. We conducted a survey among more than 50,000 players using the BrainHex model as a personality type motivator to gather and compare demographic data to the different BrainHex archetypes. We discuss some results from this survey with a focus on psychometric orientation of respondents, to establish relationships between personality types and BrainHex archetypes.},
Address = {Vancouver, BC, Canada},
Author = {L. E. Nacke, C. Bateman, and R. L. Mandryk},
Booktitle = {Proceedings of icec 2011},
Doi = {10.1007/978-3-642-24500-8_31},
Pages = {288-293},
Publisher = {Springer Berlin Heidelberg},
Title = {BrainHex: Preliminary Results from a Neurobiological Gamer Typology Survey},
Url = {https://hcigames.com/download/brainHex-preliminary-results-from-a-neurobiological-gamer-typology-survey},
Year = {2011},
BdskUrl1 = {https://hcigames.com/wp-content/uploads/2015/01/BrainHex-A-Neurobiological-Gamer-Typology-Survey.pdf},
BdskUrl2 = {http://dx.doi.org/10.1007/978-3-642-24500-8%5C_31}}

This paper briefly presents a player satisfaction model called BrainHex, which was based on insights from neurobiological findings as well as the results from earlier demographic game design models (DGD1 and DGD2). The model presents seven different archetypes of players: Seeker, Survivor, Daredevil, Mastermind, Conqueror, Socialiser, and Achiever. We explain how each of these player archetypes relates to older player typologies (such as Myers-Briggs), and how each archetype characterizes a specific playing style. We conducted a survey among more than 50,000 players using the BrainHex model as a personality type motivator to gather and compare demographic data to the different BrainHex archetypes. We discuss some results from this survey with a focus on psychometric orientation of respondents, to establish relationships between personality types and BrainHex archetypes.

Influencing Experience: The Effects of Reading Game Reviews on Player Experience

@incollection{livingston2011influencing,
Abstract = {Game reviews are used by game developers for making business decisions and measuring the success of a title, and have been shown to affect player perception of game quality. We conducted a study where players read positive or negative reviews of a game before playing, and show that the valence of review text affected game ratings and that these differences could not be explained by mediating changes in mood. Although we show predictable changes in player experience over the course of the study (measured objectively through physiological sensors), there were no objective differences in experience depending on review valence. Our results suggest that reading reviews does not directly affect play experience, but rather is a post-play cognitive rationalization of the experience with the content of the review. Our results are important for understanding player experience and to the game industry where reviews and user forums affect a game's commercial success.},
Address = {Vancouver, BC, Canada},
Author = {I. J. Livingston, L. E. Nacke, and R. L. Mandryk},
Booktitle = {Proceedings of icec 2011},
Doi = {10.1007/978-3-642-24500-8_10},
Pages = {89-100},
Publisher = {Springer Berlin Heidelberg},
Title = {Influencing Experience: The Effects of Reading Game Reviews on Player Experience},
Url = {http://dx.doi.org/10.1007/978-3-642-24500-8_10},
Year = {2011},
BdskUrl1 = {http://dx.doi.org/10.1007/978-3-642-24500-8%5C_10}}

Game reviews are used by game developers for making business decisions and measuring the success of a title, and have been shown to affect player perception of game quality. We conducted a study where players read positive or negative reviews of a game before playing, and show that the valence of review text affected game ratings and that these differences could not be explained by mediating changes in mood. Although we show predictable changes in player experience over the course of the study (measured objectively through physiological sensors), there were no objective differences in experience depending on review valence. Our results suggest that reading reviews does not directly affect play experience, but rather is a post-play cognitive rationalization of the experience with the content of the review. Our results are important for understanding player experience and to the game industry where reviews and user forums affect a game's commercial success.

Year 2018

Introduction to biometric measures for Games User Research

@incollection{Nacke2018Bio,
address = {New York, NY},
author = {Nacke, Lennart},
editor = {Drachen, Anders and Mirza-Babaei, Pejman and Nacke, Lennart},
isbn = {978-0198794844},
pages = {281-299},
publisher = {Oxford University Press},
booktitle = {{Games User Research}},
title = {{Introduction to biometric measures for Games User Research}},
year = {2018}
}"

Biometrics provide real-time measures of human responses essential to player experience in Games User Research (GUR) projects. This chapter presents the physiological metrics used in GUR. Aimed at GUR professionals in the games industry, it explains what methods are available to researchers to measure biometric data while subjects are engaged in play. It sets out when it is appropriate to use biometric measures in GUR projects, the kind of data generated, and the differing ways it can be analysed. The chapter also discusses the trade-offs required when interpreting physiological data, and will help games user researchers to make informed decisions about which research questions can benefit from biometric methodologies.