Multiscale movement coordination dynamics in collaborative team problem solving

Wiltshire, Travis J.; Steffensen, Sune Vork; Fiore, Stephen M.

doi:10.1016/j.apergo.2018.07.007

Cited by 47 publications

(67 citation statements)

References 78 publications

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“…Interpersonal coordination provides the social glue that holds a team together (von Zimmermann & Richardson, 2016), facilitating greater perceived rapport, liking, feelings of interpersonal connectedness, prosocial behavior, and cooperation (Cross, Wilson, & Golonka, 2016;Lakens & Stel, 2011;Reddish, Fischer, & Bulbulia, 2013;Valdesolo & DeSteno, 2011;Valdesolo, Ouyang, & DeSteno, 2010). Interpersonal coordination is also associated with enhanced task performance, reflecting a process through which team members interact to share knowledge, reach a mutual understanding, and complete the task-at-hand (Gorman, Amazeen, & Cooke, 2010;Miles, Lumsden, Flannigan, Allsop, & Marie, 2017;Richardson & Dale, 2005;Wiltshire, Butner, & Fiore, 2018;Wiltshire, Steffensen, & Fiore, 2019).…”

Section: Introductionmentioning

confidence: 99%

Beyond Dyadic Coordination: Multimodal Behavioral Irregularity in Triads Predicts Facets of Collaborative Problem Solving

2019

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We hypothesize that effective collaboration is facilitated when individuals and environmental components form a synergy where they work together and regulate one another to produce stable patterns of behavior, or regularity, as well as adaptively reorganize to form new behaviors, or irregularity. We tested this hypothesis in a study with 32 triads who collaboratively solved a challenging visual computer programming task for 20 min following an introductory warm‐up phase. Multidimensional recurrence quantification analysis was used to examine fine‐grained (i.e., every 10 s) collective patterns of regularity across team members' speech rate, body movement, and team interaction with the shared user interface. We found that teams exhibited significant patterns of regularity as compared to shuffled baselines, but there were no systematic trends in regularity across time. We also found that periods of regularity were associated with a reduction in overall behavior. Notably, the production of irregular behavior predicted expert‐coded metrics of collaborative activity, such as teams' ability to construct shared knowledge and effectively negotiate and coordinate execution of solutions, net of overall behavioral production and behavioral self‐similarity. Our findings support the theory that groups can interact to form interpersonal synergies and indicate that information about system‐level dynamics is a viable way to understand and predict effective collaborative processes.

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Section: Introductionmentioning

confidence: 99%

Beyond Dyadic Coordination: Multimodal Behavioral Irregularity in Triads Predicts Facets of Collaborative Problem Solving

2019

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“…No relationship was observed between PS and perceived or objective group CPS performance. The current findings are in line with previous studies that found no association between PS and group performance in CPS (Amon et al ., 2019; Wiltshire, 2015). The non‐significant relationship can be explained in several ways.…”

Section: Discussionmentioning

confidence: 99%

“…CPS is not a monolithic process and includes various cyclical phases (eg, planning, strategy development and enactment, monitoring, evaluation) (Hadwin et al ., 2018; Winne, 2010). Thus, PS in specific phases of CPS may be more influential on group performance than the overall PS in the whole session (Dindar et al ., 2019; Wiltshire, 2015). Future research can utilise methods (eg, video analysis) to identify the phases of CPS and investigate whether PS in specific CPS phases is related to group performance.…”

Section: Discussionmentioning

confidence: 99%

“…In some studies, the relationship between PS and group performance was mediated by other variables, such as perceptual sensitivity (Valdesolo, Ouyang, & DeSteno, 2010). Other studies reported no association between PS and group performance (Amon, Vrzakova, & D’Mello, 2019; Wiltshire, 2015), whereas some reported a negative relationship (Dich, Reilly, & Schneider, 2018; Strang et al ., 2014; Wallot, Mitkidis, et al ., 2016). The current literature indicates that further research is necessary in order to elucidate the association between PS and group task performance.…”

Section: Ps As An Indicator Of Cps Processesmentioning

confidence: 99%

“…For example, in order to understand how CPS unfolds over time, researchers have employed video annotations (Dindar, Alikhani, Malmberg, Järvelä, & Seppänen, 2019), think‐aloud protocols (Siddiq & Scherer, 2017), micro‐level interaction analyses (Pöysä‐Tarhonen, Care, Awwal, & Häkkinen, 2018) and computer‐generated log‐files (He, von Davier, Greiff, Steinhauer, & Borysewicz, 2017). However, the field is still in search of novel methods and data forms that can capture temporal aspects of CPS unobtrusively (Wiltshire, Steffensen, & Fiore, 2019). In light of this gap, the current study explores the potential of multimodal data analytics in CPS.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

What does physiological synchrony reveal about metacognitive experiences and group performance?

Dindar¹,

Järvelä²,

Haataja³

2020

Brit J Educational Tech

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There is a growing body of research on physiological synchrony (PS) in Collaborative Problem Solving (CPS). However, the current literature presents inconclusive findings about the way in which PS is reflected in cognitive and affective group processes and performance. In light of this, this study investigates the relationship between PS and metacognitive experiences (ie, judgement of confidence, task interest, task difficulty, mental effort and emotional valence) that are manifested during CPS. In addition, the study explores the association between PS and group performance. The participants were 77 university students who worked together on a computer‐based CPS simulation in groups of three. Participants’ electrodermal activity (EDA) was recorded as they worked on the simulation and metacognitive experiences were measured with situated self‐reports. A Multidimensional Recurrence Quantification Analysis was used to calculate the PS among the collaborators. The results show a positive relationship between continuous PS episodes and groups’ collective mental effort. No relationship was found between PS and judgement of confidence, task interest, task difficulty or emotional valence. The relationship between PS and group performance was also non‐significant. The current work addresses several challenges in utilising multimodal data analytics in CPS research and discusses future research directions.

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Local Exceptionality Detection in Time Series Using Subgroup Discovery: An Approach Exemplified on Team Interaction Data

2021

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Multiscale movement coordination dynamics in collaborative team problem solving

Cited by 47 publications

References 78 publications

Beyond Dyadic Coordination: Multimodal Behavioral Irregularity in Triads Predicts Facets of Collaborative Problem Solving

Beyond Dyadic Coordination: Multimodal Behavioral Irregularity in Triads Predicts Facets of Collaborative Problem Solving

What does physiological synchrony reveal about metacognitive experiences and group performance?

Local Exceptionality Detection in Time Series Using Subgroup Discovery: An Approach Exemplified on Team Interaction Data

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