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The strength of the strongest ties in collaborative problem solving.

ABSTRACT: Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

SUBMITTER: de Montjoye YA

PROVIDER: S-EPMC4064431 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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The strength of the strongest ties in collaborative problem solving.

de Montjoye Yves-Alexandre YA Stopczynski Arkadiusz A Shmueli Erez E Pentland Alex A Lehmann Sune S

Scientific reports 20140620

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly corre ...[more]

PMID: 24946798

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Project description:This study is based on one collaborative problem solving task from an international assessment: the Xandar task. It was developed and delivered by the Organization for Economic Co-operation and Development Program for International Student Assessment (OECD PISA) 2015. We have investigated the relationship of problem solving performance with invested time and number of actions in collaborative episodes for the four parts of the Xandar task. The parts require the respondent to collaboratively plan a process for problem solving, implement the process, reach a solution, and evaluate the solution (For a full description, see the Materials and Methods section, "Parts of the Xandar Task.") Examples of an action include posting to a chat log, accessing a shared resource, or conducting a search on a map tool. Actions taken in each part of the task were identified by PISA and recorded in the data set numerically. A confirmatory factor analysis (CFA) model looks at two types of relationship: at the level of latent variables (the factors) and at extra dependencies, which here are direct effects and correlated residuals (independent of the factors). The model, which is well-fitting, has three latent variables: actions (A), times (T), and level of performance (P). Evidence for the uni-dimensionality of performance level is also found in a separate analysis of the binary items. On the whole for the entire task, participants with more activities are less successful and faster, based on the United States data set employed in the analysis. By contrast, successful participants take more time. By task part, the model also investigates relationships between activities, time, and performance level within the parts. This was done because one can expect dependencies within parts of such a complex task. Results indicate some general and some specific relationships within the parts, see the full manuscript for more detail. We conclude with a discussion of what the investigated relationships may reveal. We also describe why such investigations may be important to consider when preparing students for improved skills in collaborative problem solving, considered a key aspect of successful 21st century skills in the workplace and in everyday life in many countries.

Project description:Collaborative problem-solving has been gaining attention as more and more students and employees work together all around the world to find solutions to complex problems. This trend goes hand in hand with a growing interest in the role of affective processes in learning and problem-solving fields. However, the comprehension of real-time dynamics between emotional sharing and collaborative exchanges (what we propose to call "collaborative act") still needs to be deepened. The challenge is especially on understanding the interplay between real-time changes in epistemic and relational dimensions. In this study, we propose to explore this question in dyadic creative problem-solving. Eleven pairs of participants used an argument graph tool to co-create a slogan against violence at school. The tool was used to write down slogans and build a joint map of the group argumentation. During the collaboration, they had access to an emotion awareness tool, allowing them to share emotional labels in real time. An indicator of real-time use was computed to track ongoing changes in collaborative acts during collaboration. Then, using both inferential and descriptive statistics, we first investigated whether emotional sharing induces real-time adaptation of both emitter's and receiver's collaborative acts. Second, we looked at privileged relationships between emitter's collaborative acts, emitter's emotion sharing, and receiver's collaborative acts. The preliminary results obtained (1) confirm that emotional sharing regulates emitter's and receiver's collaborative acts and (2) strongly suggest that specific emotions mark specific patterns of collaboration in different collaborative phases, implying both the epistemic and the relational spaces of collaboration. These results highlight the value of studying emotional sharing for a deeper comprehension of the factors regulating collaborative problem-solving. Perspectives in educational psychology and computer science are considered, with the will to understand and promote better self- and co-regulation of collaborative problem-solving through emotional sharing.

Project description:Background: Studies have acknowledged that social media enables students to connect with and learn from experts from different ties available in the students' personal learning environment (PLE). Incorporating experts into formal learning activities such as scaffolding problem-solving tasks through social media, allows students to understand how experts solve real-world problems. However, studies that evaluate experts' problem-solving styles on social media in relation to the tie strength of the experts with the students are scarce in the extant literature. This study aimed to explore the problem-solving styles that the experts portrayed based on their ties with the students in problem-based learning (PBL) on Facebook. Methods: This study employed a simultaneous within-subject experimental design which was conducted in three closed Facebook groups with 12 final year management students, six business experts, and one instructor as the participants. The experts were invited by the students from the weak and strong ties in their PLE. Hinging on the Strength of Weak Ties Theory (Granovetter, 1973) and problem-solving styles (Selby et al., 2004), this study employed thematic analysis using the ATLAS.ti qualitative data analysis software to map the experts' comments on Facebook. Results: The experts from strong and weak ties who had a prior relationship with the students showed people preference style by being more sensitive to the students' learning needs and demonstrating firmer scaffolding compared to the weak ties' experts who had no prior relationship with the students. Regardless of the types of ties, all experts applied all manner of processing information and orientation to change but the degree of its applications are correlated with the working experience of the experts. Conclusion: The use of weak or strong ties benefited the students as it expedited their problem-solving tasks since the experts have unique expertise to offer depending on the problem-solving styles that they exhibited.

Project description:In this paper we argue that a synthesis of findings across the various sub-areas of research in complex problem solving and consequently progress in theory building is hampered by an insufficient differentiation of complexity and difficulty. In the proposed framework of person, task, and situation (PTS), complexity is conceptualized as a quality that is determined by the cognitive demands that the characteristics of the task and the situation impose. Difficulty represents the quantifiable level of a person's success in dealing with such demands. We use the well-documented "semantic effect" as an exemplar for testing some of the conceptual assumptions derived from the PTS framework. We demonstrate how a differentiation between complexity and difficulty can help take beyond a potentially too narrowly defined psychometric perspective and subsequently gain a better understanding of the cognitive mechanisms behind this effect. In an empirical study a total of 240 university students were randomly allocated to one of four conditions. The four conditions resulted from contrasting the semanticity level of the variable labels used in the CPS system (high vs. low) and two instruction conditions for how to explore the CPS system's causal structure (starting with the assumption that all relationships between variables existed vs. starting with the assumption that none of the relationships existed). The variation in the instruction aimed at inducing knowledge acquisition processes of either (1) systematic elimination of presumptions, or (2) systematic compilation of a mental representation of the causal structure underpinning the system. Results indicate that (a) it is more complex to adopt a "blank slate" perspective under high semanticity as it requires processes of inhibiting prior assumptions, and (b) it seems more difficult to employ a systematic heuristic when testing against presumptions. In combination, situational characteristics, such as the semanticity of variable labels, have the potential to trigger qualitatively different tasks. Failing to differentiate between 'task' and 'situation' as independent sources of complexity and treating complexity and difficulty synonymously threaten the validity of performance scores obtained in CPS research.

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The strength of the strongest ties in collaborative problem solving.

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The strength of the strongest ties in collaborative problem solving.

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