Collaboration is often a critical aspect of scientific research, which is dominated by complex problems, rapidly changing technology, dynamic growth of knowledge, and highly specialized areas of expertise. An individual scientist can seldom provide all of the expertise and resources necessary to address complex research problems. This paper describes collaboration among a group of scientists, and considers how their experiences are socially shaped. The scientists were members of a newly formed distributed, multi-disciplinary academic research center that was organized into four multi-disciplinary research groups. Each group had 14 to 34 members, including faculty, postdoctoral fellows and students, at four geographically dispersed universities. To investigate challenges that emerge in establishing scientific collaboration, data were collected about members' previous and current collaborative experiences, perceptions regarding collaboration, and work practices during the center's first year of operation. The data for the study includes interviews with members of the center, observations of videoconferences and meetings, and a center-wide sociometric survey. Data analysis has led to the development of a framework that identifies forms of collaboration that emerged among scientists (e.g., complementary and integrative collaboration) and associated factors, which influenced collaboration including personal compatibility, work connections, incentives, and infrastructure. These results may inform the specification of social and organizational practices, which are needed to establish collaboration in distributed, multi-disciplinary research centers.

This paper reports on an exploratory study that investigates the relationship between participants' learning style preferences and their perceptions of a professional workshop on collaboration and technology to support collaboration. The Learning Preference Scale‐Students (LPSS) (Owens & Barnes, 1992) was administered to identify participants' learning style preferences as cooperative, competitive and/or individualized. Using cluster analysis two groups, or categories, of learning style preferences among the participants emerged. Group 1 showed a strong preference for the cooperative learning style, and Group 2 showed a strong preference for competitive and cooperative learning styles. Group 1 rated the workshop more positively than Group 2. However, Group 2 reported a larger increase in self‐efficacy compared to those in Group 1 (18.9% vs. 6.0%). Both groups provided different suggestions regarding the content of the workshop. Group 1 suggested adding more discussions and group exercises, whereas Group 2 suggested adding explicit theory or rules to govern behavior. These findings indicate that learning styles should be considered as a potential variable that influences learning outcomes and preferences.