scholarly journals Classroom as Complex Adaptive System and the Emergence of Learning

2021 ◽  
Author(s):  
Ben Knight
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Teaching And Learning ◽  
Complex Adaptive System ◽  
Early Years ◽  
Non Linear ◽  
Complex Adaptive ◽  
Traffic Systems ◽  
Application Of Cas ◽  
Innovation And Change

Complex adaptive systems (CAS) theory is offering new perspectives on the nature of learning in school classrooms. In CAS such as social networks, city traffic systems and insect colonies, innovation, and change are occasioned through non-linear, bottom-up emergence rather than linear, top-down control. There is a growing body of evidence and discourse suggesting that learning in school classrooms, particularly in the early years and primary phases, has non-linear, emergent qualities and that teachers, school leaders, and educational researchers can gain valuable insights about the nature of interactive group learning by analyzing classrooms through a CAS lens. This chapter discusses the usefulness of a CAS framing for conceptualizing learning in primary school classrooms. It will explore key arguments, discuss relevant objections and draw on my own research to make the case for a measured application of CAS theory to primary classroom teaching and learning, explaining how it can support the development of innovative pedagogies.

Complex Adaptive Systems Thinking Approach for Intelligence Base in Support of Intellectual Capital Management

2013 ◽  
pp. 122-141 ◽  
Author(s):  
Marc Rabaey
Keyword(s):  
Systems Thinking ◽  
Intellectual Capital ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Organizational Design ◽  
Complex Adaptive System ◽  
Holistic Approach ◽  
Holistic View ◽  
Complex Adaptive ◽  
Systems Thinking Approach

This chapter introduces Complex Adaptive Systems Thinking (CAST) into the domain of Intellectual Capital (IC). CAST is based on the theories of Complex Adaptive System (CAS) and Systems Thinking (ST). It argues that the CAST, combined with Intelligence Base offers a potentially more holistic approach to managing the Intellectual Capital of an organization. Furthermore, the authors extend this IC management with additional dimensions proper to a social entity such as an organization. New organizational design methods are needed and the capability approach is such a method that supports IC in virtual and real organizations. The characteristics of Intellectual Capital are discussed in the iterative process of inquiry and the Cynefin Framework, guaranteeing a holistic view on the organization and its environment.

scholarly journals Holonic Handling the Unexpected in Project Management

2017 ◽  
Vol 2 (1) ◽  
pp. 137-143
Author(s):  
Levente Bakos ◽  
Dănuț Dumitrașcu
Keyword(s):  
Risk Assessment ◽  
Project Management ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Complex Adaptive System ◽  
Project Team ◽  
Abductive Reasoning ◽  
Multi Agent Systems ◽  
Complex Adaptive ◽  
Known Unknowns

Abstract Risk assessment is one the key activities of any project. The unexpected situations can have catastrophic consequences. Risk assessment tries to estimate to potential known unknowns, but there is no guarantee to foresee all circumstances around a project. In this situation the project team must be adaptive and find solutions by cooperation, creativity and abductive reasoning. In the paper we tried to analyse on what extent a project and a project team can be handled as a complex adaptive system. More precisely, how the scientific and practical achievements of the theory of complex adaptive systems (CAS) can be used in project management. More exactly, we analyse the applicability of the Holonic Multi-Agent Systems in risk management of the projects. We consider the way in which holons handle the unexpected situations can be a model in project management.

scholarly journals Next Generation Data Infrastructures: Towards an Extendable Model of the Asset Management Data Infrastructure as Complex Adaptive System

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Paul Brous ◽  
Marijn Janssen ◽  
Paulien Herder
Keyword(s):  
Complex Adaptive Systems ◽  
Asset Management ◽  
Adaptive Systems ◽  
New Technologies ◽  
Complex Adaptive System ◽  
Emergent Behavior ◽  
Data Infrastructure ◽  
Management Domain ◽  
Complex Adaptive ◽  
Data Infrastructures

Organizations are increasingly looking to adopt the Internet of Things (IoT) to collect the data required for data-driven decision-making. IoT might yield many benefits for asset management organizations engaged in infrastructure asset management, yet not all organizations are equipped to handle this data. IoT data is collected, stored, and analyzed within data infrastructures and there are many changes over time, resulting in the evolution of the data infrastructure and the need to view data infrastructures as complex adaptive systems (CAS). Such data infrastructures represent information about physical reality, in this case about the underlying physical infrastructure. Physical infrastructures are often described and analyzed in literature as CASs, but their underlying data infrastructures are not yet systematically analyzed, whereas they can also be viewed as CAS. Current asset management data models tend to view the system from a static perspective, posing constraints on the extensibility of the system, and making it difficult to adopt new data sources such as IoT. The objective of the research is therefore to develop an extensible model of asset management data infrastructures which helps organizations implement data infrastructures which are capable of evolution and aids the successful adoption of IoT. Systematic literature review and an IoT case study in the infrastructure management domain are used as research methods. By adopting a CAS lens in the design, the resulting data infrastructure is extendable to deal with evolution of asset management data infrastructures in the face of new technologies and new requirements and to steadily exhibit new forms of emergent behavior. This paper concludes that asset management data infrastructures are inherently multilevel, consisting of subsystems, links, and nodes, all of which are interdependent in several ways.

scholarly journals The class as a learning entity (complex adaptive system): An idea from complexity science and educational research

2008 ◽  
Vol 2 ◽  
Author(s):  
Craig Newell
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Adaptive System ◽  
Complex Adaptive System ◽  
Individual Student ◽  
Learning And Teaching ◽  
Complexity Thinking ◽  
The Social ◽  
Complex Adaptive ◽  
Social Collective

Educational theorists are making increasing use of the metaphors and concepts of complexity thinking in their discourses. In particular, Professors Brent Davis, Elaine Simmt, and Dennis Sumara have written extensively about using complexity thinking to shift attention from the individual student as the locus of learning (cognizing agent) to the social collective—the class—as the locus of learning. In this model, the class (students and teacher) is (potentially) a complex adaptive system. The students and teacher remain complex adaptive systems in their own right, but through dynamic local interactions there is the possibility of emergent behaviours indicative of learning that transcends that of the individuals within the class. The social collective we know as a class becomes an instance of the Aristotlean adage, “The whole is greater than the sum of its parts.” (With the coda that we cannot understand the whole by merely understanding the components.) Davis, Simmt, and Sumara have segued from complexity-informed descriptions of educational collectives to discussions about facilitating the self-organization of classes into complex adaptive systems – learning systems, in their language. In this paper, I discuss complex adaptive systems and look at how Davis, Simmt, and Sumara developed their thesis that the class collective, rather than individual student, is the appropriate level to investigate learning and teaching. We conclude by addressing some of the possibilities and challenges inherent in such a redescription of communities of learners.

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems

2014 ◽  
Vol 37 (6) ◽  
pp. 563-564 ◽  
Author(s):  
Tobias A. Mattei
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
System Analysis ◽  
Complex Adaptive System ◽  
Brain Structures ◽  
Human Cognition ◽  
Evolutionary Development ◽  
Complex Adaptive ◽  
Triggering Events ◽  
The Brain

AbstractIn self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

Price discovery by the market's mind: an investor's perspective on numerical archetypes

2013 ◽  
Vol 5 (2) ◽  
pp. 140-153
Author(s):  
Patrick Schotanus
Keyword(s):  
Complexity Theory ◽  
Complex Adaptive Systems ◽  
Intelligent Agents ◽  
Adaptive Systems ◽  
Price Discovery ◽  
Adaptive System ◽  
Complex Adaptive System ◽  
Modern Society ◽  
Necessary Condition ◽  
Complex Adaptive

The aim of this paper is to contribute to Jung's later work, with a particular focus on the numerical archetypes viewed from an investor's perspective. It attempts to achieve this via a three-pronged approach. First, placing complex psychology in the framework of complexity theory allows a robust acknowledgement and treatment of ‘elusive’ macroscopic properties, i.e. archetypal dynamics, involved in the ordering of a mind as a complex adaptive system. Second, modern insights in number sense (the direct intuition of what numbers mean) provide neuroscientific support for numerical archetypes and clarify their primacy. Third, this paper points to the empirical relevance of numerical archetypes in price discovery, the self-organizing principle of the capital markets (which allocate resources in modern society). The resulting proposition is that the (collective) mind's unconscious and conscious forces can be considered as ‘intelligent’ agents. The competition between these two domains provides the necessary condition to endogenously generate innovative outcomes, the essential capability of complex adaptive systems. According to this view producing such adaptive novelty is achieved in the form of intuitive insights and imagination, which result in a vast array of symbols, e.g. prices in the case of the market's mind.

scholarly journals Organizing Theories for Disasters into a Complex Adaptive System Framework

Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 61
Author(s):  
Annetta Burger ◽  
William G. Kennedy ◽  
Andrew Crooks
Keyword(s):  
Human Behavior ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Complex Adaptive System ◽  
Disaster Studies ◽  
The Social ◽  
Complex Adaptive ◽  
Interacting Systems ◽  
Individual Actor ◽  
The Individual

Increasingly urbanized populations and climate change have shifted the focus of decision makers from economic growth to the sustainability and resilience of urban infrastructure and communities, especially when communities face multiple hazards and need to recover from recurring disasters. Understanding human behavior and its interactions with built environments in disasters requires disciplinary crossover to explain its complexity, therefore we apply the lens of complex adaptive systems (CAS) to review disaster studies across disciplines. Disasters can be understood to consist of three interacting systems: (1) the physical system, consisting of geological, ecological, and human-built systems; (2) the social system, consisting of informal and formal human collective behavior; and (3) the individual actor system. Exploration of human behavior in these systems shows that CAS properties of heterogeneity, interacting subsystems, emergence, adaptation, and learning are integral, not just to cities, but to disaster studies and connecting them in the CAS framework provides us with a new lens to study disasters across disciplines. This paper explores the theories and models used in disaster studies, provides a framework to study and explain disasters, and discusses how complex adaptive systems can support theory building in disaster science for promoting more sustainable and resilient cities.

scholarly journals Multiscale Modeling in Smart Cities: A Survey on applications, Current Trends, and Challenges

2021 ◽  
Author(s):  
Asif Khan ◽  
Khursheed Aurangzeb ◽  
Sheraz Aslam ◽  
Musaed Alhussein
Keyword(s):  
Multiscale Modeling ◽  
Complex Adaptive Systems ◽  
Smart City ◽  
Adaptive Systems ◽  
Complex Adaptive System ◽  
Smart Cities ◽  
Health Issues ◽  
Complex Adaptive ◽  
Key Issues ◽  
City Model

Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor governance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dynamic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost. In this paper, we present an overview of MM in smart cities. First, this study discusses megacities, their current challenges, and their emergence to smart cities. Then, we discuss the need of MM in smart cities and its emerging applications. Finally, the study highlights current challenges and future directions related to MM in smart cities, which provide a roadmap for the optimized operation of smart city systems.

scholarly journals Navigating the Turbulent Waters of School Reform Guided by Complexity Theory

2016 ◽  
Vol 13 (1) ◽  
Author(s):  
David G. White ◽  
James A. Levin
Keyword(s):  
School Reform ◽  
Complexity Theory ◽  
Low Income ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Adaptive System ◽  
Complex Adaptive System ◽  
Design Experiment ◽  
Underrepresented Minority ◽  
Complex Adaptive

The goal of this research study has been to develop, implement, and evaluate a school reform design experiment at a continuation high school with low-income, low-performing underrepresented minority students. The complexity sciences served as a theoretical framework for this design experiment. Treating an innovative college preparatory program as a nested complex adaptive system within a larger complex adaptive system, the school, we used features of complex adaptive systems (equilibrium, emergence, self-organization, and feedback loops) as a framework to design a strategy for school reform. The goal was to create an environment for change by pulling the school far from equilibrium using a strategy we call “purposeful perturbations” to disrupt the stable state of the school in a purposeful way. Over the four years of the study, several tipping points were reached, and we developed agent-based simulation models that capture important dynamic properties of the reform at these points. The study draws upon complexity theory in multiple ways that have supported improved education for low-achieving students.

scholarly journals FISHERMEN ECOLOGICAL KNOWLEDGE AND COMPLEX ADAPTIVE SYSTEMS: AN INTERPRETATIVE MODEL FOR SMALL-SCALE FISHERIES

2019 ◽  
Vol 22 ◽  
Author(s):  
Luciana Loto ◽  
Ronaldo Lobão ◽  
Edson Pereira Silva ◽  
Cassiano Monteiro-Neto
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Biology ◽  
Complex Adaptive System ◽  
Small Scale ◽  
Ecological Knowledge ◽  
Small Scale Fisheries ◽  
Complex Adaptive ◽  
Definition Of ◽  
Interpretative Model

Abstract The fishermen ecological knowledge (FEK) encompasses information on biology of species and climatic and oceanographic changes, all related with schools of fish and its capture. It incorporates a complex set of codes and signs, which are constantly updated and transmitted orally thorough generations. In this sense, FEK presents characteristics such as diversity and ability to learn from experience, which are in conformity with the definition of a complex adaptive system (CAS). Based on this assumption, this work proposes to structure and interpret FEK as a CAS. It is supported that such approach can promote the exchange of information among areas, which are other way considered incommensurable (anthropology, oceanography, marine biology, meteorology etc.), and also among formal sciences and the FEK. However, CAS is a structure designed with heuristic goals associated with mathematical modeling what is beyond the aims of this work, which uses CAS only as a structuring metaphor.

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