Sage Journals: Discover world-class research

Abstract

Effective teamwork requires both individual domain-specific knowledge and social cognitive skills. In this paper, we discuss a theoretical approach that incorporates metacognitive training to enhance social cognition and theory of mind within teams. By using scaffolding techniques to address cognitive biases, we aim to facilitate efficient collaborative problem-solving. Our goal is to develop individual and team metacognitive awareness in social contexts through various interventions implemented during the preparation, execution, and reflection stages of training. We suggest that metacognitive strategies implemented during team training can enhance individuals’ ability to navigate social interactions and understand others’ perspectives. This approach provides a foundation for researchers interested in studying methods to improve collaboration, for teams seeking to enhance interpersonal understanding, and beneficial for those creating interventions to reduce social cognitive biases and improve theory of mind within collaborative problem-solving scenarios.

Keywords

social cognition theory of mind collaborative problem solving (CPS)

Introduction

The ever-increasing interrelatedness of technology and society in domains like aviation, space exploration, and industrial control has led to highly complex and multifaceted problems (Letsky et al., 2008) which demand a collective approach to problem-solving (He et al., 2017). This has led to a growing focus on developing individuals with the skills needed for effective collaboration (Care et al., 2016). Collaborative problem-solving (CPS) brings people together to leverage their diverse knowledge, skills, and abilities to transform problems into desired outcomes (OECD, 2017). At the highest level, the two main facets of CPS are cognitive and social (Hesse et al., 2015). In the cognitive dimension, group members collaborate to understand the problem, share information, devise strategies, and adjust until goals are met. The social dimension involves interpersonal elements, like communication amongst team members, which can facilitate or impede collaboration (Duruaku et al., 2024; Graesser et al., 2018). Effective collaboration often suffers due to limitations in social cognitive abilities, like theory of mind. Specifically, individuals may struggle to understand perspectives, intentions, and mental states. This poses a need for interventions that enhance team performance through targeted training on social-cognitive dimensions.

We draw upon principles from social cognitive theory, ToM research, and metacognitive theory to discuss the impact of metacognitive training on social cognition and theory of mind within teams with a focus on cognitive biases. Social cognition (SC) posits that individuals’ cognitive processes are influenced by social context (Hamilton & Stroessner, 2020), affecting how they perceive and interpret interpersonal cues while ToM allows individuals to predict and explain others’ behavior and collaborate effectively (Frith & Frith, 1999). One significant challenge to SC and mental state attribution is the presence of cognitive biases. We describe cognitive biases as unconscious sources of error in thinking that distort how we process information (Jones & Roelofsma, 2000), leading to errors in social perception, especially because humans adopt various cognitive shortcuts, can rely on type 1 (automatic) thinking (Kahneman, 2011), and act as cognitive misers (Fiske & Taylor, 1991).

Metacognitive training emphasizes the importance of self-awareness and self-regulation in cognitive processes, suggesting that individuals can improve their cognitive abilities through metacognitive strategies. While the benefits of metacognitive training are being explored in various contexts, research directly examining its impact on social cognition, theory of mind (ToM), and subsequent influence on team collaboration remains an underexplored area. In this paper, we redress this gap by proposing how metacognitive scaffolding, which supports individuals and teams in gaining awareness of their own cognitive processes, abilities, and limitations (e.g., Hill & Hannafin, 2001), can enhance social cognition and ToM within teams to improve collaboration. Our goal is to show how metacognitive scaffolding, as a training intervention, can improve collaborative problem-solving (CPS). We provide a set of research propositions to guide training researchers in exploring how these techniques may influence team members’ awareness of their own and others’ cognitive processes during collaborative problem-solving.

We begin by describing social cognition and theory of mind in team collaboration, metacognition as a cognitive mechanism for collaborative problem solving, and the common cognitive biases that impact social cognition and ToM.

Social Cognition and Theory of Mind in Team Collaboration

Successful team collaboration requires more than just individual technical skills and expertise. Teams need to navigate the social dynamics at work, and two key cognitive processes are crucial for this: social cognition (SC) and theory of mind (ToM). Social cognition is the mental process through which individuals perceive, interpret, and respond to social cues, including the thoughts, intentions, emotions, and behaviors of others (Fiske & Taylor, 1991; Frith, 2008). It includes a range of skills that are relevant to teamwork; when team members utilize these social cognitive skills they can build trust, communicate clearly and coordinate efforts towards a common goal. Dual process theories of social cognition propose that we have two distinct ways of processing information in social settings (Evans & Stanovich, 2013; Wiltshire et al., 2014). This may affect how teams collaborate on problems. Type 1 processing is fast and automatic. This might help teams move swiftly, coordinating actions based on immediate social assessments. Type 2 processing is slower and more deliberate. This might allow for the consideration of different viewpoints and strategizing effectively.

Theory of mind takes social cognition a step further. It refers to the ability to attribute mental states such as beliefs, desires, and intentions to oneself and others, and to understand that these mental states can differ from one’s own (Premack & Woodruff, 1978). Findings from social neuroscience reveal two frameworks for explaining the process involved in how we understand others’ behavior (Alcalá-López et al., 2019): Theory Theory (TT) and Simulation (ST). In TT, people use abstract principles about human behavior, learned from experience, to interpret and predict others’ mental states and actions (Carruthers, 2009; Gopnik & Wellman, 1992). In ST, individuals mentally simulate others’ experiences, using their own minds as models to understand others’ mental states (Gallese & Goldman, 1998; Saxe, 2005). Over time, various tests have been designed to assess ToM capabilities, including tasks like “Reading the Mind in Eyes” and “Reading the Mind in Film,” which require participants to identify mental states depicted in visual stimuli (Lobato et al., 2014).

During team collaboration, ToM would help individuals predict the behavior of other team members by understanding their thoughts and intentions (Woolley et al., 2010). Ultimately, we suggest that SC and ToM enable team members to navigate social complexities, understand each other’s perspectives, and coordinate their efforts to achieve shared objectives in collaborative problem-solving contexts.

Metacognitive Training in CPS

Metacognition involves an individual’s understanding of how their cognitive abilities function. As already described, it encompasses awareness, assessment, and regulation of one’s own thinking processes (Flavell, 1979; Victoria & Athanasios, 2023). As such, it is a necessary component of problem solving, in general (Schaeffner et al., 2021) and CPS in particular. CPS requires a group of individuals working together to identify, analyze, and resolve complex issues or challenges to change a problem state into a desired state (Fiore et al., 2017; Graesser et al., 2018). While existing research has established connections between metacognition, ToM, and social cognition in enhancing collaborative problem-solving, there is a little research on how metacognitive training can be specifically applied to improve ToM and social cognition for this purpose. Hence, we begin by describing how metacognitive scaffolding can address this gap.

Metacognitive training focuses on enhancing team members’ awareness and control over their own cognitive processes. Research has demonstrated that metacognitive skills are advantageous in communication (Flavell, 1979), complex problem-solving, and expertise development through task training (Fiore et al., 2002). Evidence from learning and cognition studies at the individual level show that reflecting on the comprehension process improves knowledge acquisition (for a discussion, see Fiore & Vogel-Walcutt, 2010). We suggest that training researchers explore how to optimize team collaboration using metacognitive training through scaffolding.

Metacognitive scaffolding is the support structure put in place to facilitate the development and application of metacognitive skills within a team. Effective scaffolding should conform to three essential elements: diagnosis, calibration, and fading (Puntambekar & Hübscher, 2005). Continuous “diagnosis” allows facilitators to “calibrate” scaffolds that promote ToM and SC in teams. As teams improve, the scaffolds “fade,” fostering stronger team dynamics and task performance. Therefore, we propose that:

Proposition I: Metacognitive scaffolding techniques will enhance social cognition and theory of mind within teams and lead to effective problem solving.

Following earlier theorizing on metacognitive training for teams, we delineate three phases based on the stages of learning, known as the “training cycle” (Fiore & Vogel-Walcutt, 2010). This includes preparation, execution, and reflection and each phase plays a critical role in developing and applying metacognitive strategies within teams to improve their problem-solving capabilities. We suggest that the preparation phase be used to help team members calibrate their ToM. In the execution phase, social cognitive interventions can help teams attend to social cues during collaboration. These should also be devised to provide feedback (e.g., are team members accurate about their ToM assessments). The last phase involves reflection on some performance episode (cf. Gabelica et al., 2016). In this phase, not only should team members attend to their performance, but interventions can also help them focus on ToM by, for example, trying to assess teammate intentions or beliefs at critical points that affected CPS outcomes. From the above distinctions, we propose that:

Proposition II: Implementing metacognitive scaffolding techniques into the three phases of training will increase team awareness of their own cognitive processes and that of their team members during CPS.

There is existing evidence that cognitive biases influence social interactions and theory of mind during teamwork, hindering effective problem-solving. Recognizing these biases is crucial for developing strategies to enhance team performance. Thus, we will describe these in the next section.

Cognitive Biases Influencing Social Cognition and ToM

Teamwork thrives on our ability to understand each other. However, this capacity is shaped by our backgrounds, experiences, and cultures. Because collaboration involves individuals with different cultural and interpersonal exposures (Gehlbach & Vriesema, 2019), it creates room for biases that lead to errors in social perception and judgment. Biases are systematic deviations from rational judgment that arise when people process and interpret information (Tversky & Kahneman, 1974). We describe the cognitive biases that affect SC and ToM that may cause disruptions in CPS.

Confirmation Bias

This refers to an individual’s inclination to prefer information that supports or reinforces their preexisting beliefs or values (Gatlin et al., 2017; Nickerson, 1998). In social contexts, people are primed to focus on cues from team members that support their expectations and devalue those that do not, thus impairing theory of mind. This distorted social cognition can hinder effective CPS, as decisions are based on a limited view of others’ perspectives.

Correspondence Bias

This refers to a cognitive tendency where people attribute others’ behaviors to their personality traits regardless of whether the behavior is socially constrained or caused by situational factors (Gilbert & Malone, 1995; Nier et al., 2013). This bias can lead to misinterpretations of the mental states of others (i.e., ToM) and interpretation of behaviors (i.e., SC) leading to misunderstandings during collaboration.

Anchoring Effect

This bias occurs when the first piece of information (i.e., the “anchor”), we encounter heavily influences our subsequent judgments, even if it’s completely unrelated (Wickens et al., 2010; Wilde et al., 2018). This bias makes it difficult to gauge the mental states of others because we rely heavily on initial impressions.

Availability Bias

This refers to the mental shortcut where we judge the likelihood or importance of something based on how easily examples of it come to mind (Tversky & Kahneman, 1974). It can lead to misattributions of mental states based on how easily we can recall similar experiences and disproportionately affect judgments of social behaviors.

Halo & Horn Effects

The halo effect is the tendency to let a single positive characteristic about someone color our perception of their entire personality (Radeke & Stahelski, 2020) while the horn effect is the tendency to let a single negative characteristic taint our entire impression of someone (Cook et al., 2003). The halo/horn effects skew how we perceive and evaluate people, often based on superficial traits.

Group Think

This is when the desire for harmony and conformity results in irrational or dysfunctional decision-making outcomes (Janis, 1991) in teams. In social settings, members may refrain from voicing disagreements or alternative viewpoints to avoid conflicts or rejection. The presence of psychological safety plays a crucial role in mitigating groupthink. When team members feel safe to express their opinions and concerns without fear of negative consequences, they are more likely to share diverse perspectives (Edmondson, 1999).

In-Group Bias

This refers to the tendency for individuals to favor and prioritize the interests of their own group over those of out-groups (Tajfel et al., 1979). In teams, members tend to attribute positive behaviors to in-group members while attributing negative traits to out-group members (cf. Brewer, 1979). They may find it harder to accurately infer the mental states of out-group members due to a lack of empathy and understanding (Molenberghs, 2013). Based on the above, we propose that:

Proposition III: Implementing metacognitive training programs designed to target specific cognitive biases will lead to improvements in social cognition and theory of mind required for effective CPS.

Theoretical Approach

Enhancing social cognition can be achieved through a targeted approach that focuses on training both individuals and teams about the ways in which cognitive biases interfere with their ability to accurately interpret and understand others’ behaviors (ToM). We adopt an approach that recognizes that our innate biases often act as barriers to effective social understanding and interaction. By bringing these biases to light and providing strategies to mitigate their effects, individuals and teams can develop more accurate and nuanced social cognitive skills. This, in turn, can lead to improved communication and better teamwork.

Our framework is based upon an integration of theoretical factors centered on improving learning. We adapt the training cycle (Fiore & Vogel-Walcutt, 2010), which outlined the phases of learning and tailored the scaffolds appropriately, namely: preparation, execution, monitoring, and reflection scaffolds (Newton et al., 2018; Wiltshire et al., 2014). From this, we provide metacognitive prompts (see Table 1) to scaffold cognitive biases that can influence SC and ToM during CPS. Note that we provide representative prompts tailored for both the individual and the team. From this, training researchers are able to adapt as needed for interventions aimed at the individual or team level, or both. Further, for the execution phase prompts, it is expected that they be introduced in a “stop and think” type format; that is, training scenarios can be interrupted to some degree such that a prompt is introduced, allowing team members to reflect on the prompt. For the reflection phase, following the tenets of team reflexivity (Gabelica et al., 2016), it is expected that these prompts not only be asked, but that trainees also reflect on how to refine these strategies for future interactions. We anticipate that the proposed approach will be useful for team researchers seeking to manage social cognitive biases and improve theory of mind and social cognition within collaborative problem-solving scenarios.

Table 1.

Metacognitive Training Interventions to Improve Social Cognition and Theory of Mind.

Phases of CPS	Notional metacognitive prompts to address cognitive biases
Preparation	Individual preparation-based prompting • What pre-existing beliefs or assumptions might influence your perception of social cues in the upcoming collaborative task? • How might your interpretations of behaviors (e.g., eye contact, use of humor, speaking volume) differ from those of your teammates? • For the upcoming collaborative task, how will you ensure that your initial impressions of team members, based on their roles or backgrounds, do not disproportionately influence your perception of their input? • How will you ensure that the most recent or memorable interactions with team members do not unduly influence your perception of their social cues? • How will you interpret social cues fairly during your imminent collaboration, considering the strengths and weaknesses of each team member, without letting one trait overshadow others? • What strategies will you employ to encourage independent thinking and critical evaluation of ideas to mitigate its effects on decision-making processes during the upcoming collaboration? • In your upcoming collaboration, how do you plan to identify and address instances where you might favor certain team members based on personal connections or similarities, while being attentive to social cues? Team preparation-based prompting • What strategies can the team employ to remain open-minded and objective in interpreting social cues for the upcoming collaboration? • What steps can the team take to better attend to the traits and situational factors that will influence interpretation of social cues of its members? • For the upcoming collaboration, what strategies can the team employ to encourage actively questioning starting points or first impressions, rather than allowing them to unduly influence your judgments? • How can the team ensure that the understanding of social cues is informed by diverse perspectives, rather than just a few standout examples? • How can the team encourage diverse perspectives and fairly evaluate contributions and avoid the influence of initial positive or negative impressions? • How can the team actively monitor and address signs of conformity during decision-making to ensure diverse perspectives are considered? • In the upcoming collaborative task, how can the team ensure it is sensitive to social cues that indicate whether all team members feel included?
Execution	Individual execution-based prompting • How are you monitoring the influence of your initial beliefs and interpretations of social cues? • How are you navigating misunderstandings or misattributions of intentionality during the collaborative problem-solving task? • How are you actively questioning and adjusting your interpretations of social cues, or are you allowing initial impressions or limited information to exert a disproportionate influence on your judgments? • Are you allowing recent or highly salient examples to exert a disproportionate influence on your perceptions? • How are you allowing a single positive or negative trait to disproportionately shape your perceptions? • How are you actively listening to and valuing the input of all team members, especially those who may have differing viewpoints? • How are you actively monitoring your behavior and the social cues of others to ensure you are not unfairly favoring certain individuals? Team execution-based prompting • How are the team’s prior assumptions influencing the interpretation of social cues? • Is the team considering situational factors when interpreting each other’s actions and behaviors? • How is the team encouraging consideration of additional context or information to avoid relying too heavily on the limited cues? • How is the team maintaining awareness of the tendency to prioritize recent social cues during the collaborative task? • How is the team ensuring that the perceptions of the social cues of others are not overly influenced by the halo effect such as initial positive impressions of some members, but the contributions of all team members? • How is the team monitoring social cues to ensure that all members are participating and feel comfortable expressing their views? • How is the team monitoring interactions to ensure that all members feel included and valued during the collaboration?
Reflection	Individual reflection-based prompting • What strategies did you employ to mitigate the effects of pre-existing beliefs in decision-making processes within your team? • How did your perception of social cues map to the externally observed behaviors during the collaboration? • During the collaboration task, how did you manage the impact of initial impressions when responding to social cues? • How did you consider all relevant social cues during the collaboration, not just those that come readily to mind? • During the collaborative task, were your initial impressions or judgments based on a single positive or negative trait and did that influence your perception and interpretation of social cues? • How did you ensure that you are open to diverse opinions and perspectives from your team members, rather than conforming to the majority view? • Considering the social cues presented, what steps did you take to ensure that your judgments and decisions are fair and impartial? Team reflection-based prompting • During the collaborative episode, were there any instances where the team successfully mitigated the influence of pre-existing beliefs? How did the team achieve this? • How did the team’s awareness and consideration of contextual factors influence its interpretation of actions and behaviors during collaboration? • During your collaboration, what strategies did the team find effective in mitigating the influence of first impressions or limited social cues? • What strategies did the team implement to ensure a balanced and objective assessment of all available perspectives and experiences when interpreting social cues during the collaboration? • How did the team identify and acknowledge the potential influence of first impressions on their perception of social cues? • What strategies were effective in promoting open dialogue and diverse input in your team? • How effectively did the team recognize and respond to social cues indicating inclusion or exclusion during the collaborative task?

Conclusion

By integrating metacognitive scaffolding techniques into team processes during planning, execution, and reflection, teams can achieve heightened awareness of their cognitive processes and improve coordination and communication during CPS tasks. In practical terms, this paper offers actionable research directions for designing and implementing metacognitive training programs in real-world team settings. Ultimately, our goal is to help guide future training research to explore and test metacognitive scaffolding in team settings to unlock its full potential and drive positive outcomes in teamwork and collaborative problem-solving.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The writing of this paper was partially supported by the US Air Force Office of Scientific Research (AFOSR) grant FA9550-22-1-0151 awarded to Stephen M. Fiore. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the AFOSR or the University of Central Florida.

ORCID iDs

Fiona Duruaku

Blake Nguyen

Olivia B. Newton

Stephen M. Fiore

References

Alcalá-López

Vogeley

Binkofski

Bzdok

(2019). Building blocks of social cognition: Mirror, mentalize, share? Cortex, 118, 4–18. https://doi.org/10.1016/j.cortex.2018.05.006

Brewer

M. B.

(1979). In-group bias in the minimal intergroup situation: A cognitive-motivational analysis. Psychological Bulletin, 86(2), 307–324. https://doi.org/10.1037/0033-2909.86.2.307

Care

Scoular

Griffin

(2016). Assessment of collaborative problem-solving in education environments. Applied Measurement in Education, 29(4), 250–264.

Carruthers

(2009). How we know our own minds: The relationship between mindreading and metacognition. Behavioural and Brain Sciences, 32(2), 121–138.

Cook

G. I.

Marsh

R. L.

Hicks

J. L.

(2003). Halo and devil effects demonstrate valences-based influences on source-monitoring decisions. Consciousness and Cognition, 12(2), 257–278. https://doi.org/10.1016/S1053-8100(02)00073

Duruaku

Fiore

S. M.

Jentsch

F. G.

(2024). Cognitive Dynamics of Theory of Mind in Collaborative Problem-Solving: A Framework for Understanding Teamwork in Complex Environments. In Proceedings of the International Conference on Human-Computer Interaction (HCII, 2024). Advance online publication.

Edmondson

(1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999

Evans

J. S. B.

Stanovich

K. E.

(2013). Dual-process theories of higher cognition: Advancing the debate. Perspectives on Psychological Science, 8(3), 223–241. https://doi.org/10.1177/1745691612460685

Fiore

S. M.

Cuevas

H. M.

Scielzo

Salas

(2002). Training individuals for distributed teams: Problem solving assessment for distributed mission research. Computers in Human Behavior, 18(6), 729–744. https://doi.org/10.1016/S0747-5632(02)00027-4

10.

Fiore

S. M.

Graesser

A. C.

Greiff

Griffin

Gong

Kyllonen

P. C.

Massey

C. S.

O’Neil

H. F.

Pellegrino

Rothman

R. A.

Soulé

Davier

A. A.

(2017). Collaborative problem solving: Considerations for the national assessment of educational progress.

11.

Fiore

S. M.

Vogel-Walcutt

J. J.

(2010). Making metacognition explicit: Developing a theoretical foundation for metacognitive prompting during scenario-based training. Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting, 54(27), 2233–2237. https://doi.org/10.1177/154193121005402703.

12.

Fiske

S. T.

Taylor

S. E.

(1991). Social cognition. McGraw-Hill Book.

13.

Flavell

J. H.

(1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906.

14.

Frith

C. D.

(2008). Social cognition. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1499), 2033–2039. https://doi.org/10.1098/rstb.2008.0005

15.

Frith

C. D.

Frith

(1999). Interacting minds—A biological basis. Science, 286(5445), 1692–1695. https://doi.org/10.1126/science.286.5445.1692

16.

Gabelica

Van den Bossche

Fiore

S. M.

Segers

Gijselaers

W. H.

(2016). Establishing team knowledge coordination from a learning perspective. Human Performance, 29(1), 33–53. https://doi.org/10.1080/08959285.2015.1120304

17.

Gallese

Goldman

(1998). Mirror neurons and the simulation theory of mind-reading. Trends in Cognitive Sciences, 2(12), 493–501. https://doi.org/10.1016/S1364-6613(98)01262-5

18.

Gatlin

K. P.

Hallock

Cooley

L. G.

(2017). Confirmation bias among business students: The impact on decision-making. Review of Contemporary Business Research, 6(2), 10–15. https://doi.org/10.15640/rcbr.v6n2a2

19.

Gehlbach

Vriesema

C. C.

(2019). Meta-bias: A practical theory of motivated thinking. Educational Psychology Review, 31, 65–85. https://doi.org/10.1007/s10648-018

20.

Gilbert

D. T.

Malone

P. S.

(1995). The correspondence bias. Psychological Bulletin, 117(1), 21–38.

21.

Gopnik

Wellman

H. M.

(1992). Why the child’s theory of mind really is a theory. Mind & Language, 7(1–2), 145–171. https://doi.org/10.1111/j.1468-0017.1992.tb00202.x

22.

Graesser

A. C.

Fiore

S. M.

Greiff

Andrews-Todd

Foltz

P. W.

Hesse

F. W.

(2018). Advancing the science of collaborative problem solving. Psychological Science in the Public Interest, 19(2), 59–92. https://doi.org/10.1177/1529100618808244

23.

Hamilton

D. L.

Stroessner

S. J.

(2020). Social cognition: Understanding people and events. SAGE.

24.

Von Davier

Greiff

Steinhauer

E. W.

Borysewicz

P. B.

(2017). Collaborative problem-solving measures in the Programme for International Student Assessment (PISA). In Innovative assessment of collaboration (pp. 95–111). Springer International Publishing. https://doi.org/10.1007/978-3-319-33261-1_7

25.

Hesse

Care

Buder

Sassenberg

Griffin

(2015). A framework for teachable collaborative problem-solving skills. In Griffin

Care

(Eds.), Assessment and teaching of 21st-century skills: Methods and approach (pp. 37–56). Springer.

26.

Hill

J. R.

Hannafin

M. J.

(2001). Teaching and learning in digital environments: The resurgence of resource-based learning. Educational Technology Research and Development, 49(3), 37–52. https://doi.org/10.1007/BF02504914

27.

Janis

(1991). Groupthink. In Griffin

(Ed.), A first look at communication theory (pp. 235–246). McGrawHill.

28.

Jones

P. E.

Roelofsma

P. H.

(2000). The potential for social contextual and group biases in team decision-making: Biases, conditions and psychological mechanisms. Ergonomics, 43(8), 1129–1152.

29.

Kahneman

(2011). Thinking, fast and slow. Farrar, Straus and Giroux.

30.

Letsky

Warner

Fiore

S. M.

Smith

(Eds.). (2008). Macrocognition in teams: Theories and methodologies. Ashgate Publishing Ltd.

31.

Lobato

E. J. C.

Wiltshire

T. J.

Fiore

S. M.

(2013). A dual-process approach to understanding human-robot interaction. In Proceedings of the Human Factors and Ergonomics Society 57th Annual Meeting, 1263–1267. https://doi.org/10.1177/1541931213571280

32.

Molenberghs

(2013). The neuroscience of in-group bias. Neuroscience and Biobehavioral Reviews, 37(8), 1530–1536. https://doi.org/10.1016/j.neubiorev.2013.06.002

33.

Newton

O. B.

Wiltshire

T. J.

Fiore

S. M.

(2018). Macrocognition in teams and metacognition: Developing instructional strategies for complex collaborative problem solving. In Building intelligent tutoring systems for teams: What matters (pp. 33–54). Emerald Publishing Limited. https://doi.org/10.1108/S1534-085620180000019006

34.

Nickerson

R. S.

(1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175

35.

Nier

J. A.

Bajaj

McLean

M. C.

Schwartz

(2013). Group status, perceptions of agency, and the correspondence bias: Attributional processes in the formation of stereotypes about high and low status groups. Group Processes & Intergroup Relations, 16(4), 476–487. https://doi.org/10.1177/1368430212453866

36.

OECD. (2017). PISA 2015 collaborative problem-solving framework. PISA 2015 assessment and analytical framework: Science, reading, mathematic, financial literacy and collaborative problem solving. OECD Publishing. https://doi.org/10.1787/9789264281820-en

37.

Premack

Woodruff

(1978). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1(4), 515–526.

38.

Puntambekar

Hübscher

(2005). Tools for scaffolding students in a complex learning environment: What have we gained and what have we missed? Educational Psychologist, 40(1), 1–12. https://doi.org/10.1207/s15326985ep4001_1

39.

Radeke

M. K.

Stahelski

A. J.

(2020). Altering age and gender stereotypes by creating the Halo and Horns Effects with facial expressions. Humanities and Social Science Commununications, 7, 14. https://doi.org/10.1057/s41599-020-0504-6

40.

Saxe

(2005). Against simulation: The argument from error. Trends in Cognitive Sciences, 9(4), 174–179. https://doi.org/10.1016/j.tics.2005.01.012

41.

Schaeffner

Chevalier

Kubota

Karbach

(2021). Metacognitive training. In Strobach

Karbach

(Eds.), Cognitive training (pp. 255–270). Springer.

42.

Tajfel

Turner

J. C.

Austin

W. G.

Worchel

(1979). An integrative theory of intergroup conflict. In Organizational identity: A reader (pp. 56–65). In W. G. Austin, & S. Worchel (Eds.), The Social Psychology of Intergroup Relations (pp. 33–47). Brooks/Cole.

43.

Tversky

Kahneman

(1974). Judgment under uncertainty: Heuristics and biases. Science (New York, N.Y.), 185(4157), 1124–1131. https://doi.org/10.1126/science.185.4157.1124

44.

Victoria

Athanasios

(2023). Theory of mind in relation to metacognition and ICTs. A metacognitive approach to ToM. Scientific Electronic Archives, 16(4), 34–52. https://doi.org/10.36560/1642023171

45.

Wickens

C. D.

Ketels

S. L.

Healy

A. F.

Buck-Gengler

C. J.

Bourne

L. E.

(2010). The anchoring heuristic in intelligence integration: A bias in need of de-biasing. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 54(27), 2324–2328. https://doi.org/10.1177/154193121005402722

46.

Wilde

T. R.

Ten Velden

F. S.

De Dreu

C. K.

(2018). The anchoring-bias in groups. Journal of Experimental Social Psychology, 76, 116–126. https://doi.org/10.1016/j.jesp.2018.02.001

47.

Wiltshire

T. J.

Snow

S. L.

Lobato

E. J. C.

Fiore

S. M.

(2014). Leveraging social judgment theory to examine the relationship between social cues and signals in human-robot interactions. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 58(1), 1336–1340. https://doi.org/10.1177/1541931214581279

48.

Woolley

A. W.

Chabris

C. F.

Pentland

Hashmi

Malone

T. W.

(2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686–688. https://doi.org/10.1126/science.1193147

Scaffolding Team Minds: Using Metacognitive Training to Boost Social Cognition and Theory of Mind for Effective Collaborative Problem-Solving

Abstract

Keywords

Introduction

Social Cognition and Theory of Mind in Team Collaboration

Metacognitive Training in CPS

Cognitive Biases Influencing Social Cognition and ToM

Confirmation Bias

Correspondence Bias

Anchoring Effect

Availability Bias

Halo & Horn Effects

Group Think

In-Group Bias

Theoretical Approach

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iDs

References