A Framework for Cross-Disciplinary Team Learning and Performance

Title: A Framework for Cross-Disciplinary Team Learning and Performance
Authors: Schaffer, Scott P;Lei, Kimfong;Paulino, Lisette Reyes
Reference: Schaffer, Scott P;Lei, Kimfong;Paulino, Lisette Reyes (2008) A Framework for Cross-Disciplinary Team Learning and Performance, Performance Improvement Quarterly; 21, 3

Abstract: The construct of teamwork has been of considerable interest to researchers and practitioners across domains. The literature on teams includes many studies related to team composition, processes, and roles, but it pays much less attention to how teams learn and innovate. Studies examining how cross-disciplinary teams interact during projects are even less common. The study examined here was conceived to fill the need for a theoretical framework to describe how individuals from different disciplines evolve into a team that creates new forms of knowledge and innovative solutions or products. The framework, which was validated in a university service-learning program with over 25 teams, is a comprehensive theory merging two existing team models within a sociocultural system framework emphasizing the mediating aspects of the collective team and context. The theoretical foundations, the definitions, and dimensions of the framework are presented in this article.

Notes: Scanning the literature on creative teamwork, most papers seem to be about developing hypothetical models, and reinforcing some commonsensical and general ideas. The modified CDTL proposed here is interesting, well presented, yet fails to contribute anything new as the conclusions are that "cross-disciplinary team learning is more likely to be found when:

• Members shift from self-efficacy to collective efficacy
• They shift from individual process orientation to team goal orientation
• Shift from knowledge acquisition to creation
• Become aware of others' "functional discipline knowledge shifts"

Which to me seem like four different ways of saying that good teams are more likely when their members work more as a team than a collection of individuals, which is kind of circular and obvious. Will keep looking for more complete studies that lead to more detailed and reliable models.