While work in fields of CSCW (Computer Supported Collaborative Work), Psychology and Social Sciences have progressed our understanding of team processes and their effect performance and effectiveness, current methods rely on observations or self-report, with little work directed towards studying team processes with quantifiable measures based on behavioral data. In this report we discuss work tackling this open problem with a focus on understanding individual differences and its effect on team adaptation, and further explore the effect of these factors on team performance as both an outcome and a process. We specifically discuss our contribution in terms of methods that augment survey data and behavioral data that allow us to gain more insight on team performance as well as develop a method to evaluate adaptation and performance across and within a group. To make this problem more tractable we chose to focus on specific types of environments, Alternate Reality Games (ARGs), and for several reasons. First, these types of games involve setups that are similar to a real-world setup, e.g., communication through slack or email. Second, they are more controllable than real environments allowing us to embed stimuli if needed. Lastly, they allow us to collect data needed to understand decisions and communications made through the entire duration of the experience, which makes team processes more transparent than otherwise possible. In this report we discuss the work we did so far and demonstrate the efficacy of the approach.
翻译:虽然在CSCW(计算机支持的合作工作)、心理学和社会科学等领域的工作已使我们对团队进程及其效果和有效性的理解有所进展,但目前的方法依靠的是观察或自我报告,很少以观察或自我报告为基础,没有开展什么工作来研究基于行为数据的量化措施的团队进程;在本报告中,我们讨论如何解决这一开放问题,重点是了解个人差异及其对团队适应的影响,并进一步探讨这些因素对团队业绩的影响,既作为一种结果,又作为一个过程。我们具体讨论了我们在增强调查数据和行为数据的方法方面的贡献,这些方法使我们能够更多地了解团队业绩,以及制定评估跨小组和小组内部适应和绩效的方法。为了使这一问题更加易于处理,我们选择把重点放在特定类型的环境、替代现实运动(ARGs)上,并出于若干原因。首先,这些类型的游戏涉及与现实世界设置相似的设置,例如,通过松懈或电子邮件进行沟通。第二,它们比实际环境更容易控制,使我们能够在需要的情况下嵌入Simuli系统。最后,它们使我们能够收集到更透明的数据,我们选择了以其他方式来理解决策和团队工作效率的方法。