Search results

Team cognition research continues to evolve as the need for understanding and improving complex problem solving itself grows. Complex problem solving requires members to engage in a number of complicated collaborative processes to generate solutions. This chapter illustrates how the Macrocognition in Teams model, developed to guide research on these processes, can be utilized to propose how intelligent tutoring systems (ITSs) could be developed to train collaborative problem solving. Metacognitive prompting, based upon macrocognitive processes, was offered as an intervention to scaffold learning these complex processes. Our objective is to provide a theoretically grounded approach for linking intelligent tutoring research and development with team cognition. In this way, team members are more likely to learn how to identify and integrate relevant knowledge, as well as plan, monitor, and reflect on their problem-solving performance as it evolves. We argue that ITSs that utilize metacognitive prompting that promotes team planning during the preparation stage, team knowledge building during the execution stage, and team reflexivity and team knowledge sharing interventions during the reflection stage can improve collaborative problem solving.

The purpose of this paper is to analyse event management by using three value creation logics, value chain, value network and value shop. In event management, value is generated through intermediation where the dominant creation logic is a value network. However, the complexity of events and danger of unexpected problems is increasing, which, in the worst case, leads to event failure. This fact makes it necessary to change the general attitude towards this topic from risk management to uncertainty management and use the value shop in order to solve problems efficiently.

This paper is based on the methodology of phenomenological hermeneutics which analyzes the object of study by interpreting the facticity and provides basics to generate a conceptual model.

The dominant value creation logic must be changed to prevent the value network from failure in generating value, since only the value shop provides high quality problem solving. Trust not only in planning but also in the own problem-solving competence and available tools is a major part of the value shop. As a practical example of high quality problem solving, the performance of high reliability organisations can be used by event managers.

Using these hermeneutical gained logic, additional empirical research projects in event management, leadership and problem-solving competence of top managers, are promptly intended. Additionally, studies concerning competences and structures of the uncertainty management team have to be determined and developed as well as education and coaching has to be generated in order to achieve best results in problem solving.

Practical implications of this paper are: considering the value shop as the dominant value creation logic in uncertainty management; establishing a specially trained Complex Problem-Solving Team; and considering trust to be an essential element of the value shop.

The basic job requirements a successful value net (event-) manager has to provide in such a complex system are: acting as integrator, mediator and problem solver simultaneously. Additionally event managers need to be trained to rethink the value creation logic and use the value shop within the value net to stay flexible and work successfully during their events.

Derived from this new perspective the necessity of enhancing the implemented value creation logic according to uncertainties allows event managers to solve unexpected problems faster and more efficiently.

This study aims to explore the role of planned, sudden shifts in lived experiences, in influencing learner capabilities towards improved problem-solving for sustainable development outcomes. The authors responded to employers of engineering and built environment graduates observing limited “real-life” problem-solving skills, beyond using established formulae and methods, in spite of attempts over more than two decades, to train engineers and other built environment disciplines in areas such as whole system design and sustainable design.

A grounded theory approach was used to guide the analysis of data collected through ethnographic methods. The process involved reflecting on authors’ efforts to develop context appreciation within a course called “International Engineering Practice”, using two years of collected data (archived course information, including course profile; completed assessment; lecture and field visit evaluations; and focus groups). The study is built on the authors’ working knowledge of Bloom’s Taxonomy and Threshold Learning Theory, and the well-established role of “context appreciation” in complex problem-solving. After the first iteration of the course, the authors looked for additional theoretical support to help explain findings. The Cynefin framework was subsequently used to augment the authors’ appreciation of “context” – beyond physical context to include relational context, and to evaluate students’ competency development across the four domains of “clear”, “complicated”, “complex” and “chaotic”.

This study helped the authors to understand that there was increased capacity of the students to distinguish between three important contexts for problem-solving, including an increased awareness about the importance of factual and relevant information, increased acknowledgement of the varying roles of professional practitioners in problem-solving depending on the type of problem and increased appreciation of the importance of interdisciplinary teams in tackling complex and complicated problems. There were several opportunities for such courses to be more effective in preparing students for dealing with “chaotic” situations that are prevalent in addressing the United Nations’ 17 sustainable development goals (UNSDGs). Drawing on the course-based learnings, the authors present a “context integration model” for developing problem-solving knowledge and skills.

The research findings are important because context appreciation – including both physical context and relational context – is critical to problem-solving for the UNSDGs, including its 169 targets and 232 indicators. The research findings highlight the opportunity for the Cynefin framework to inform holistic curriculum renewal processes, enhancing an educator’s ability to design, implement and evaluate coursework that develops physical and relational context appreciation.

The study’s findings and context integration model can help educators develop the full range of necessary problem-solving graduate competencies, including for chaotic situations involving high degrees of uncertainty. Looking ahead, acknowledging the significant carbon footprint of global travel, the authors are interested in applying the model to a domestic and/or online format of the same course, to attempt similar learning outcomes.

Connecting Bloom’s taxonomy deep learning and threshold learning theory critical path learning insights with the Cynefin framework context domains, provides a novel model to evaluate competency development for problem-solving towards improved holistic physical and relational “context appreciation” outcomes.

Organizations, especially those adapting to rapidly changing environments, face the challenge of being able to solve complex problems within highly constrained timeframes. Complex problem solving has been addressed by theories of bounded rationality. However, these theories focus on solving complex but structured problems, and thus, context and how it emerges and transforms is not a central issue. More recently, theories of the firm as a knowledge‐creating entity have focused on how organizations solve complex unstructured problems. These theories suggest that context and contextualization are central elements in problem solving. Yet, no understanding of how context emerges and transforms emerges from these theories. The present paper focuses on the emergence and transformation of context in solving complex unstructured problems, attempts to remedy the shortcomings of the theories described above and investigates the nature of context. Concludes by explaining its role in tacit knowledge sharing.

This paper aims to evaluate the effect of knowledge overlap, search width and problem complexity on the quality of problem-solving in teams that use the majority rule to aggregate heterogeneous knowledge of the team members.

The paper uses agent-based simulations to model iterative problem-solving by teams. The simulation results are analyzed using linear regressions to show the interactions among the variables in the model.

We find that knowledge overlap, search width and problem complexity interact to jointly impact the optimal solution in the iterative problem-solving process of teams using majority rule decisions. Interestingly, we find that more complex problems require less knowledge overlap. Search width and knowledge overlap act as substitutes, weakening each other’s performance effects.

The results suggest that team performance in iterative problem-solving depends on interactions among knowledge overlap, search width and problem complexity which need to be jointly examined to reflect realistic team dynamics.

The findings suggest that team formation and the choice of a search strategy should be aligned with problem complexity.

This paper contributes to the literature on problem-solving in teams. It is the first attempt to use agent-based simulations to model complex problem-solving in teams. The results have both theoretical and practical significance.

In a variety of domains, teams represent the main mechanism for dealing with change, complexity, and uncertainty in organizations. Consequently, teams need to be able to adapt and effectively use shared and complementary cognitive processing while collaborating to deal with these challenges.

A conceptual review is provided that addresses this type of complex collaborative cognition via discussion of macrocognition and the processes contributing to effective team problem-solving.

Despite extensive research on problem-solving, research and theories regarding how problem-solving changes over time as teams develop is missing. With this review, we extend research on team problem-solving and team development through integration of existing theory and concepts from the team literature.

This review provides a theoretical foundation for understanding and studying the developmental dynamic of team problem-solving.

A team problem-solving development model is described which outlines the degree to which the primary elements of team development are likely to affect macrocognitive processes within problem-solving phases. A set of propositions is offered in order to guide research on team development in collaborative problem-solving.

The main focus of this paper is to discuss appropriate forms of higher education for building up students' competence for working on complex real‐world problems.

Within this paper the Harvard approach is accurately compared with the ETH approach by discussing theoretical and practical implications as well.

It is argued that the Harvard case study approach is a sensible approach to bridging the gap between the academic and the practical world, but it has important limits in preparing students to cope with complex real‐world problems. In some important respects, the ETH case study approach goes further by exposing students directly to the multi‐faceted and complex character of real‐world problems.

The ETH approach puts additional demands on students and teachers to bridge the gap between university and society with a high degree of responsibility. Consequently, a combination of both the Harvard and the ETH approach might be interesting.

The comparison of the Harvard case study approach with the ETH case study approach is novel. The discussion of educational together with practical implications provides insight to the peculiarities of each single approach together with an orientation for their implementation within higher education. Guidance is given to universities who are deciding what educational means have to be implemented in order to prepare their students for the task of solving complex real‐world problems in an inter but also transdisciplinary manner.

Organizations are faced with solving increasingly complex problems. Addressing these issues requires effective leadership that can facilitate a collaborative problem solving approach where multiple perspectives are leveraged. In this conceptual paper, we critique the effectiveness of earlier leadership models in tackling complex organizational issues. We then examine one promising model, adaptive leadership, in detail and propose that this model provides a leadership approach for addressing current organizational realities. The model, proposed and developed over the last two decades, fundamentally supports the assumption of leadership by multiple stakeholders, with the formulation of the leadership dependent on the emergent problem. Adaptive leadership, with its focus on collaborative problem-solving utilizing multiple perspectives, is especially applicable to large organizations faced with solving complex problems involving many stakeholders.

This study aims to explore the conditional relationships between supplier involvement and financial performance. From a problem-solving perspective, this study takes the focal firm as a problem-solving system. It is postulated that supplier involvement enhances financial performance by helping solve complex problems of new product development. Furthermore, product modularity and smartness are considered contingent factors to clarify the boundary conditions.

The ordinary least squares regression was conducted to test the hypotheses based on survey data from 136 high-tech firms in China.

Supplier involvement is positively related to financial performance. Product modularity weakens the impact of supplier involvement on financial performance. Furthermore, product smartness strengthens the negative influence of product modularity on the relationship between supplier involvement and financial performance.

This study combines supplier involvement with product attributes. It takes a problem-solving perspective to rethink suppliers’ roles in new product development as problem-solvers rather than resource holders. Furthermore, this study advances the encapsulation effects of product modularity and smartness to influence the supplier involvement–financial performance link.

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.