Grant: Discovery Grants Program - Individual
University of Ontario Institute of Technology
$23,000.00
Mixed Methods for Video Games User Research: Enhancing Qualitative Evaluations with Quantitative Data
EF 2017-18
Résumé
The goal of my research is to develop quick, cost-effective and easy-to-understand methods and frameworks for collecting, analysing and reporting findings from mixed gameplay datasets. The aim is to enhance evaluation of player experience to suit the game development cycle towards providing a formative feedback for game developers. The work proposed here is divided into two research elements: First, by exploring current approaches I plan to develop mixed methods that improve effectiveness and efficiency of qualitative and quantitative data collection and analysis. Second, I plan to advance frameworks for meaningful visualisation of player experience analysis, tying qualitative and quantitative data together. Hence the outcome of this research will include applicable tools and methods as well as best practices on optimisation of human-computer interaction (HCI) methods for the game industry.As a result of many changes in video games development (such as new business models, widening player demographics and new interaction modes) the demand for studies dealing with users and their interactions with video games has grown in the past few years. Games user research (GUR) is a relatively new field using evaluation methods from HCI and psychology aiming to improve game design by providing sufficient information about gameplay for designers to draw the best conclusion possible for optimising their designs. Although standard HCI evaluation methods have made progress in understanding the usability of productivity applications, the specific characteristics of video games (such as frustration being allowed as long as it is part of the game design) mean that many established methods of user research cannot be applied in the same way for GUR. Moreover, games user researchers are usually dealing with massive and complex datasets. Thus, one of the challenges is to improve the efficiency of data gathering approaches and in making the interpretation of these data meaningful in terms of better understanding of player experience and facilitating design decisions. My research focuses to answer these shortfalls by developing tools and frameworks for analysing player experience using systematic and scientific approaches. This proposal tackles an important problem in applied GUR setting, which is to improve qualitative evaluation of player experience by developing a quick, cost-effective and easy-to-understand methods that integrates quantitative and qualitative data. Major outcomes of this research will include novel approaches for player experience evaluation as well as best practices and game design guidelines generated based on results from practical case studies and scientific experiments of player experience.I use both qualitative and quantitative research approaches, but I have more interest toward qualitative research and practical case studies where I can get involved with the complexity and data richness of real world. This proposal can be seen as a continuation to my previous works on enhancing games user research methodologies in collaboration with game developers. I believe high involvement with professionals and focusing on real world cases brings strength to research questions and findings.If this proposal is successful I expect to train up to ten HQPs, including Ph.D. students, Master?s and Undergraduate research assistants through participation in my research program.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2014-05763
Name nom
MirzaBabaei, Pejman
Department département
Business and Information Technology, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2014
Award amount
23000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2710
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information systems design
Research subject fr
Conception de systèmes d'information
Partie
4
Nb partie
5
Application title
Mixed Methods for Video Games User Research: Enhancing Qualitative Evaluations with Quantitative Data
Keyword
NSERC
Application summary
The goal of my research is to develop quick, cost-effective and easy-to-understand methods and frameworks for collecting, analysing and reporting findings from mixed gameplay datasets. The aim is to enhance evaluation of player experience to suit the game development cycle towards providing a formative feedback for game developers. The work proposed here is divided into two research elements: First, by exploring current approaches I plan to develop mixed methods that improve effectiveness and efficiency of qualitative and quantitative data collection and analysis. Second, I plan to advance frameworks for meaningful visualisation of player experience analysis, tying qualitative and quantitative data together. Hence the outcome of this research will include applicable tools and methods as well as best practices on optimisation of human-computer interaction (HCI) methods for the game industry.As a result of many changes in video games development (such as new business models, widening player demographics and new interaction modes) the demand for studies dealing with users and their interactions with video games has grown in the past few years. Games user research (GUR) is a relatively new field using evaluation methods from HCI and psychology aiming to improve game design by providing sufficient information about gameplay for designers to draw the best conclusion possible for optimising their designs. Although standard HCI evaluation methods have made progress in understanding the usability of productivity applications, the specific characteristics of video games (such as frustration being allowed as long as it is part of the game design) mean that many established methods of user research cannot be applied in the same way for GUR. Moreover, games user researchers are usually dealing with massive and complex datasets. Thus, one of the challenges is to improve the efficiency of data gathering approaches and in making the interpretation of these data meaningful in terms of better understanding of player experience and facilitating design decisions. My research focuses to answer these shortfalls by developing tools and frameworks for analysing player experience using systematic and scientific approaches. This proposal tackles an important problem in applied GUR setting, which is to improve qualitative evaluation of player experience by developing a quick, cost-effective and easy-to-understand methods that integrates quantitative and qualitative data. Major outcomes of this research will include novel approaches for player experience evaluation as well as best practices and game design guidelines generated based on results from practical case studies and scientific experiments of player experience.I use both qualitative and quantitative research approaches, but I have more interest toward qualitative research and practical case studies where I can get involved with the complexity and data richness of real world. This proposal can be seen as a continuation to my previous works on enhancing games user research methodologies in collaboration with game developers. I believe high involvement with professionals and focusing on real world cases brings strength to research questions and findings.If this proposal is successful I expect to train up to ten HQPs, including Ph.D. students, Master?s and Undergraduate research assistants through participation in my research program.