Mixed Methods for Video Games User Research: Enhancing Qualitative Evaluations with Quantitative Data

视频游戏用户研究的混合方法：利用定量数据增强定性评估

• 批准号: RGPIN-2014-05763
• 负责人: MirzaBabaei, Pejman
• 金额: $ 1.68万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588601
• 关键词: Mixed; Methods; Video; Games; User

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.

我的研究目标是开发快速，具有成本效益和易于理解的方法和框架，用于收集，分析和报告来自混合游戏数据集的结果。其目的是加强对玩家体验的评估，以适应游戏开发周期，为游戏开发人员提供形成性反馈。这里提出的工作分为两个研究要素：首先，通过探索目前的方法，我计划开发混合方法，提高定性和定量数据收集和分析的有效性和效率。其次，我计划推进有意义的玩家体验分析可视化框架，将定性和定量数据结合在一起。因此，这项研究的成果将包括适用的工具和方法，以及优化游戏行业人机交互（HCI）方法的最佳实践。 由于视频游戏开发的许多变化（如新的商业模式，扩大玩家人口统计和新的交互模式），在过去几年中，对用户及其与视频游戏交互的研究需求有所增长。游戏用户研究（GUR）是一个相对较新的领域，使用HCI和心理学的评估方法，旨在通过为设计师提供足够的游戏信息来改进游戏设计，从而得出优化设计的最佳结论。虽然标准的人机交互评估方法在理解生产力应用程序的可用性方面取得了进展，但视频游戏的特定特性（例如只要是游戏设计的一部分，就允许挫折）意味着许多既定的用户研究方法不能以同样的方式应用于GUR。此外，游戏用户研究人员通常要处理大量复杂的数据集。因此，挑战之一是提高数据收集方法的效率，并使这些数据的解释在更好地理解玩家体验和促进设计决策方面有意义。 我的研究重点是通过开发工具和框架来解决这些不足，这些工具和框架用于使用系统和科学的方法分析玩家体验。该建议解决了应用GUR设置中的一个重要问题，即通过开发一种快速，具有成本效益且易于理解的方法来提高对玩家体验的定性评估，该方法将定量和定性数据相结合。这项研究的主要成果将包括玩家体验评估的新方法，以及根据实际案例研究和玩家体验科学实验的结果产生的最佳实践和游戏设计指南。 我使用定性和定量研究方法，但我对定性研究和实际案例研究更感兴趣，在那里我可以参与真实的世界的复杂性和数据丰富性。这个建议可以被看作是我以前与游戏开发者合作加强游戏用户研究方法的工作的延续。我相信与专业人士的高度参与和对真实的世界案例的关注会给研究问题和发现带来力量。 如果这个建议是成功的，我希望培训多达10个HQP，包括博士。学生，硕士和本科研究助理通过参与我的研究计划。