How patterns of computer-supported collaboration impact technology appropriation, learning, and performance [electronic resource]
Keywords: Education.

Computer-supported collaboration is critical to success in today's work force, particularly for the STEM fields (Science, Technology, Engineering, and Math). In these fields technology is the medium for collaboration and, increasingly, computer-supported collaboration is critical to educational success as well. Collaborative projects have multiplied across all educational levels in the STEM disciplines, spurred on by the National Science Foundation's call for their inclusion (1996), and industry demands for graduates that are able to innovate and work effectively in teams. Yet while courses require students to work together in order to complete course requirements, few courses, if any, teach students the basics of successful collaboration. The lack of practical education on collaborative practices is partially due to the fact that collaboration is challenging to achieve. It is very easy for an activity designed to promote collaborative learning to be devolved, implemented, or interpreted by the participants as competitive, coercive, or merely cooperative. As challenging as collaboration is to achieve, it is even more challenging to research. The factors that contribute to successful group work and that impact collaborative learning are not well understood, especially with respect to each other. Researchers have attempted to elucidate how different factors impact learning and collaboration, yet under-represented research areas hold the potential to greatly improve collaborative practice, particularly in the domains of computer-supported collaborative work and collaborative learning. Existing research has focused on collaborations between pairs of students completing workbook problems together under laboratory conditions. Generalizing these results to real-world group collaborations is challenging, as relationship complexity grows exponentially with group size. Widening the problem space from the constrained problems with a small set of possible solutions, to ill-defined real-world problems is similarly daunting. However, these are precisely the type of challenging problems where research findings would have the most practical impact, helping guide both the group composition and collaborative processes of key decision makers in high-stakes 'wicked' problems, across fields of expertise. We need to understand what factors impact collaboration and learning in these real-world, technology-mediated contexts to increase the productivity and satisfaction of collaborations at work and school, to lessen the frustrations of students and professionals, and to maximize learning. This dissertation analyzes patterns of use of collaborative technologies to identify factors impacting the success or failure of real-world teamwork. The three articles presented here contribute to the collaboration research canon through robust, mixed-methods, real-world collaboration studies. By identifying the factors responsible for the largest impact on the group's performance and the individual student's learning, this dissertation also informs the design of collaboration technology, including individual and awareness applications. Each of the three articles in this dissertation studies groups of students collaborating through and with technology, attempting to solve real-world 'wicked' problems, outside laboratories and traditional classrooms. The data are drawn from two different educational contexts: a Human-Computer Interaction (HCI) Design course in a major university in the United States, and a middle-school science course. While there is a difference in academic content and age of the participants, the salient features of the collaborative learning under analysis remains constant across all three articles, as does the larger defining goal of identifying factors that impact real-world teamwork. The commonalities shared across the articles include, first, the Activity Theory framework that guided the formulation of the research questions. The second commonality is the mediating technology that the student participants collaborated with (and through). And lastly, all three articles are based on data drawn from real world activities, in terms of the geographical locations where the team carries out their tasks, and in terms of the definition of the problems the participants solve. In each article, students collaborate in groups of four with a digital pen and augmented paper system, with the goal of completing a project they formulate themselves. The problems tackled by student teams in both educational contexts are designed to be open-ended in terms of their solution, and in the process by which students arrive at that solution. In terms of the theoretical contributions of this dissertation, each of the articles identifies factors that impact computer-supported collaboration and learning, leading the teams towards success or failure. In terms of practical contributions, the findings presented in this dissertation guide anyone desiring to improve any collaboration, and those seeking to design systems that support collaboration, towards identifying which factors to prioritize for successful outcomes. The first article, "How do different roles impact individual performance?, " determined that prior friendship among teammates significantly impacts the group's outcomes in a negative way. In fact, prior friendship impacts group performance more than other known predictors, including group cohesion and skill complementarity. The second article, "How do collaborative processes impact technology appropriation and team performance?, " identifies detrimental patterns of creating and sharing within groups. The article's analysis links these patterns of use of the collaborative technology to traditional group problems, particularly the problem of social loafing. Lastly, the "How do different roles impact individual performance?" article evaluates the ways in which different technologies mediate learning during the collaboration. This dissertation also contributes to the design of collaborative technologies through an additional dimension. The analysis presented through the articles in this dissertation demonstrates how to distill collaborative signals about the team as they carry out their project tasks. For example, by linking the group members' speech patterns to their learning outcomes, the "How do different roles impact individual performance?" article suggests how dynamic signals may be visualized to let educators and students change their behavior accordingly. And the "How do collaborative processes impact technology appropriation and team performance?, " suggests that visualizing patterns of creation and sharing of content would lead groups to change their behavior and improve their collaborative processes and outcomes. While the technology featured in this dissertation may not always be readily available, the patterns of collaboration discovered through the analyses presented in these articles will remain relevant for any technology that supports creation and sharing of content, such as internet connected laptops. These patterns of collaboration, if presented to the group and individual students, hold the potential to motivate behavior changes, improving individual learning, group performance, and satisfaction.