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Article
Publication date: 9 July 2021

Cheryl Desha, Savindi Caldera and Deanna Hutchinson

This study aims to explore the role of planned, sudden shifts in lived experiences, in influencing learner capabilities towards improved problem-solving for sustainable…

Abstract

Purpose

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.

Design/methodology/approach

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”.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

International Journal of Sustainability in Higher Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1467-6370

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Book part
Publication date: 20 September 2018

Olivia B. Newton, Travis J. Wiltshire and Stephen M. Fiore

Team cognition research continues to evolve as the need for understanding and improving complex problem solving itself grows. Complex problem solving requires members to…

Abstract

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.

Details

Building Intelligent Tutoring Systems for Teams
Type: Book
ISBN: 978-1-78754-474-1

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Article
Publication date: 16 March 2015

Guido Ellert, Guido Schafmeister, David Wawrzinek and Heike Gassner

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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

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.

Social implications

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.

Originality/value

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.

Details

International Journal of Event and Festival Management, vol. 6 no. 1
Type: Research Article
ISSN: 1758-2954

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Article
Publication date: 1 June 2001

Mie Augier, Syed Z. Shariq and Morten Thanning Vendelø

Organizations, especially those adapting to rapidly changing environments, face the challenge of being able to solve complex problems within highly constrained timeframes…

Abstract

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.

Details

Journal of Knowledge Management, vol. 5 no. 2
Type: Research Article
ISSN: 1367-3270

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Article
Publication date: 14 March 2016

Aleksey Martynov and Dina Abdelzaher

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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

Originality/value

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.

Details

Team Performance Management, vol. 22 no. 1/2
Type: Research Article
ISSN: 1352-7592

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Book part
Publication date: 4 August 2017

Stephen M. Fiore and Eleni Georganta

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…

Abstract

Purpose

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.

Methodology/approach

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.

Findings

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.

Social implications

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

Originality/value

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.

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Article
Publication date: 1 July 2006

G. Steiner and D. Laws

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.

Abstract

Purpose

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.

Design/methodology/approach

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

Findings

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.

Practical implications

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.

Originality/value

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.

Details

International Journal of Sustainability in Higher Education, vol. 7 no. 3
Type: Research Article
ISSN: 1467-6370

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Article
Publication date: 17 August 2020

Maarten de Laat, Srecko Joksimovic and Dirk Ifenthaler

To help workers make the right decision, over the years, technological solutions and workplace learning analytics systems have been designed to aid this process…

Abstract

Purpose

To help workers make the right decision, over the years, technological solutions and workplace learning analytics systems have been designed to aid this process (Ruiz-Calleja et al., 2019). Recent developments in artificial intelligence (AI) have the potential to further revolutionise the integration of human and artificial learning and will impact human and machine collaboration during team work (Seeber et al., 2020).

Design/methodology/approach

Complex problem-solving has been identified as one of the key skills for the future workforce (Hager and Beckett, 2019). Problems faced by today's workforce emerge in situ and everyday workplace learning is seen as an effective way to develop the skills and experience workers need to embrace these problems (Campbell, 2005; Jonassen et al., 2006).

Findings

In this commentary the authors argue that the increased digitization of work and social interaction, combined with recent research on workplace learning analytics and AI opens up the possibility for designing automated real-time feedback systems capable of just-in-time, just-in-place support during complex problem-solving at work. As such, these systems can support augmented learning and professional development in situ.

Originality/value

The commentary reflects on the benefits of automated real-time feedback systems and argues for the need of shared research agenda to cohere research in the direction of AI-enabled workplace analytics and real-time feedback to support learning and development in the workplace.

Details

The International Journal of Information and Learning Technology, vol. 37 no. 5
Type: Research Article
ISSN: 2056-4880

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Article
Publication date: 4 February 2020

Matin Mohaghegh and Andrea Furlan

This study aims at determining the factors that favor a systematic approach to deal with complex operational and strategic problems. Management literature on problem

Abstract

Purpose

This study aims at determining the factors that favor a systematic approach to deal with complex operational and strategic problems. Management literature on problem-solving makes a clear distinction between either fixing a problem temporarily by eliminating its symptoms or solving it by diagnosing and altering underlying causes. Adopting a cognitive perspective of the dual-processing theory, this study labels these two approaches intuitive problem-solving and systematic problem-solving (SPS). While the superior effectiveness of SPS in fostering organizational learning is widely documented, existing literature fails to provide an overview of the conditions that support the adoption of SPS.

Design/methodology/approach

This paper presents a systematic literature review to shed light on the main supporting factors of SPS in operational as well as strategic domains.

Findings

Seven supporting factors of SPS (namely, nature of the problem, time availability, information availability, collaborative culture, transformational leadership, organizational learning infrastructure and environmental dynamism) are first identified and then discussed in an integrative model.

Originality/value

This work is an original attempt to inclusively address organizational, environmental and problem nature-related factors that favor SPS adoption. By determining the SPS supporting factors, this study highlights why many organizations fail or struggle to implement and sustain SPS over time.

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Book part
Publication date: 20 September 2018

Arthur C. Graesser, Nia Dowell, Andrew J. Hampton, Anne M. Lippert, Haiying Li and David Williamson Shaffer

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a…

Abstract

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.

Details

Building Intelligent Tutoring Systems for Teams
Type: Book
ISBN: 978-1-78754-474-1

Keywords

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