The dynamics of team cognition: A process-oriented theory of knowledge emergence in teams.

Abstract

Team cognition has been identified as a critical component of team performance and decision-making. However, theory and research in this domain continues to remain largely static; articulation and examination of the dynamic processes through which collectively held knowledge emerges from the individual- to the team-level is lacking. To address this gap, we advance and systematically evaluate a process-oriented theory of team knowledge emergence. First, we summarize the core concepts and dynamic mechanisms that underlie team knowledge-building and represent our theory of team knowledge emergence (Step 1). We then translate this narrative theory into a formal computational model that provides an explicit specification of how these core concepts and mechanisms interact to produce emergent team knowledge (Step 2). The computational model is next instantiated into an agent-based simulation to explore how the key generative process mechanisms described in our theory contribute to improved knowledge emergence in teams (Step 3). Results from the simulations demonstrate that agent teams generate collectively shared knowledge more effectively when members are capable of processing information more efficiently and when teams follow communication strategies that promote equal rates of information sharing across members. Lastly, we conduct an empirical experiment with real teams participating in a collective knowledge-building task to verify that promoting these processes in human teams also leads to improved team knowledge emergence (Step 4). Discussion focuses on implications of the theory for examining team cognition processes and dynamics as well as directions for future research. (PsycINFO Database Record

Shared Mental Models in Support of Adaptive Instruction for Teams Using the GIFT Tutoring Architecture

“…Kozlowski and Ilgen (2006) write of the additional, complex, and dynamic nature of teamwork arising from the constant need to adapt to emergent teamwork processes and phenomena. Grand et al (2016) have described these dynamics by modeling team cognition, shared knowledge of team tasks, and other mechanisms that underlie team knowledge development.…”

Reflections on the micro–macro divide: Ideas from the trenches and moving forward

“…Emergent phenomena and process dynamics cannot be represented or captured by boxes and arrows models incorporating "chain-like unidirectional cause-effect relationships" (McGrath et al, 2000, p. 97) that dominate quantitative organizational research and, incidentally, make it easy to stay at a single level. They necessitate process-oriented theory that focuses, not on observed construct relations, but on the underlying process mechanisms that give rise to manifest phenomena and ultimately are responsible for such observations (e.g., Grand et al, 2016). A push to examine emergent phenomena and process dynamics will go a long way toward bridging the macro-micro divide.…”

“…The increasing availability of "digital traces" (i.e., web search, text-based communication, location services, video surveillance) and advances in technology put us on the cusp of a computational organizational science (Lazer et al, 2009). Computational models (CM), agent-based modeling (ABS), and other system simulation techniques are innovative quantitative methodologies that can model process mechanisms that underlie emergence and can trace its implications for system-level outcomes (Grand et al, 2016;Ilgen and Hulin, 2000;Kozlowski et al, 2013). These new techniques necessitate far more theoretical precision than is currently the norm for the narrative theories that dominate micro, meso, and macro research.…”

Engineering Students Rapidly Learning at Hackathon Events

“…Applying "how knowledge emerges from the individual to the team-level" is important for the spread of information, and in seeing how one's actions of self-regulated learning can affect the team and vice versa. 2 This process theory provides the basis for understanding how learning occurs via self-regulated learning in teams. It also ties directly back to it in the sense that "attending to information in the environment" is a form of context being changed by the learner.…”

“…Guided by Grand et al's process mechanisms 2 , observational data was collected and thematically analyzed. Further analysis combined the two sources of data to give a deeper understanding of self-regulated learning through context from an internal and external perspective 1 .…”