Paper Session: Understanding Team Process and Outcomes via the Study of Group Dynamics

Tuesday, August 2, 2022
3:00 PM - 4:15 PM ET

Processing Team Feedback: Exploring Emotional and Cognitive Responses to Team-Level Feedback

Catherine Gabelica 

Abstract: Research on team feedback acknowledges the importance of feedback mechanisms to team success. However, although processing performance feedback in teams is seen as an important prerequisite to its effectiveness, the processes emerging after feedback reception have been overlooked in past research. This paper seeks to fill this gap by exploring emotional and cognitive responses following team-level feedback, specifically the extent to which members of high vs. low performing teams express (a) (de)activating positive or negative emotions and (b) feedback processing behaviors (i.e., reflective statements and formulation of a general vs. specific focus and/or strategy) when prompted to react to team-level feedback. The participants (N = 111) were last-year business students working in units of a fictitious company over three days. On day 2, they received feedback from customers about their team products.  We used microanalytic protocols to access students' emotional and cognitive responses to this team-level feedback.  Q1: You have just received customers' feedback on the product that your team has been crafting for the last two days. What was your immediate reaction to this feedback?  Q2: Moving forward, how will you use this feedback to improve your team performance? Please be as specific as possible). To understand how students perceived their team feedback, meaningful units of analysis were coded using two coding schemes to affective and cognitive dimensions of feedback perception: team reflexivity coding scheme from Gabelica et al. (2014) (Table 1), and the taxonomy of academic emotions from Pekrun (2006) (Table 2).  Finally, we coded responses to Q2 as expressing (a) a general focus, (b) a specific focus, (c) a general strategy, (d) a specific strategy (see Table 3). The results of our explorative study reveal that members of high-performing teams predominantly express activating positive emotions. Additionally, they provide little evidence of initial team reflection in the first place (Q1). However, it seems that when they are asked to think about how to use their team feedback, they start processing it cognitively. When prompted to strategic planning, they predominantly state (general) strategies to act on feedback. Low-performing teams show more complex patterns of feedback processing. Half of those teams express positive, activating emotions. There are no teams that express team reflexivity statements and negative emotions. Further, team reflexivity rather occurs in teams that have most members expressing positive emotions. Half of those teams already engage in cognitive thinking/processing of feedback at the first stage (Q1). However, after Q2, even teams expressing deactivating negative emotions state a focus and a strategy. Half of those teams even express a specific focus for their next team task.

Fostering constructive controversy for team learning and cooperation: Setting the stage for psychological safety

Marisa Rinkus

Abstract: Disagreement is often seen as something to be avoided, however reasonable disagreement can be useful in surfacing perspectives and reaching mutual understanding. Constructive controversy is the open-minded and productive discussion of opposing viewpoints which supports cooperative interdependence and team confidence by allowing for disagreement, elaboration of views, questioning, and alternative perspectives (Alper, Tjosvold & Law, 1998). Effective management of disagreement fosters a team climate characterized by interpersonal trust, mutual respect, and perceived low interpersonal risk associated with rejection or retaliation related to making mistakes or risk-taking (i.e. psychological safety) (Edmondson, 1999). Prior research indicates a positive correlation between constructive controversy and psychological safety, with the data showing that the benefits of constructive controversy on viewing conflict positively and engaging in creative processes was enhanced when psychological safety was high (Ou, Chen, Li & Tang, 2018). The present study explores the relationship between constructive controversy and psychological safety, using Toolbox dialogue as a proxy for constructive controversy.The Toolbox dialogue method, employed by the Toolbox Dialogue Initiative, is an evidence-informed facilitation approach to dialogue designed to surface implicit assumptions and diverse perspectives in complex, cross-disciplinary research projects for joint consideration and coordination. Designed to provoke reflection and reaction by participants, the Toolbox instrument prompts lend themselves to multiple interpretations and can create disagreement or the illusion of disagreement, encouraging further discussion of differing interpretations and perspectives (Rinkus, Donovan, Hall & O'Rourke, 2021). Using data from 43 Toolbox dialogues, representing 56 research teams, we examine the relationship between constructive controversy and psychological safety. Between October 2021 and May 2022 Toolbox workshop participants were asked to complete an 11-item survey containing a modified 4-item psychological safety scale (Edmondson, 1999) and a modified 7-item constructive controversy scale (Alper et al., 1998). We expect a positive correlation between constructive controversy and psychological safety among workshop participants. We also predict that constructive controversy will positively and uniquely predict psychological safety when controlling for workshop and team variants.By linking the Toolbox Dialogue method with quantitative measures of constructive controversy and psychological safety, we may better understand the role of dialogue in facilitating team communication and collaboration under conditions of team development and thus advance the science of team science.

Complex Coordination Dynamics in Scientific Teams

Travis Wiltshire

Abstract: Scientific teams coordinate in various modalities, across team members and their technology, and through various channels to collaborate effectively and efficiently. These complex interactions, which can be co-located, virtual, or hybrid as well as synchronous or asynchronous, pose unique and interesting challenges for understanding how coordination processes drive effective team science. In this work, I introduce a typology of team coordination dynamics as well as a methodological approach that have potential to provide theoretical and methodological insights for understanding the dynamics of scientific teamwork. First, the typology advances the idea that certain team processes (e.g., developing shared knowledge, adaptation, etc.) can be meaningfully differentiated in terms of levels of dynamic complexity, which has implications for how the dynamics are measured and modeled as well as the timescales over which they unfold. Next, the methodological approach focuses on explicitly selecting observable signals of the team (e.g., physiology, movements, communication patterns) and calculating (time-varying) coordination metrics on these (i.e., methods that estimate synchronization, recurring patterns, or temporal regularity), with a focus on evaluating the time course of coordination and key moments of change. Combined, this typology and methodological approach allows for scientists studying team science to 1) conceptualize team tasks in a typology of increasing system complexity and timescales (see Figure 1), 2) identify the team coordination measure of interest to monitor coordination, (2) describe the trajectory of team coordination over time, (3) apply methods to identify key coordination transitions, and (4) assess the meaning of those transitions in terms of their stability and implications for the team scientific process. To demonstrate the potential of this approach, I present relevant examples from empirical work of laboratory teams performing a variety of collaborative tasks. Key research questions are advanced that extend this prior work to facilitate its application to collaborative science teams, specifically. Figure 1. Representation of team coordination dynamics typology of increasing system levels of dynamic complexity and timescale of observation.