A methodology for exploring emergence in learning communities

Learning communities are becoming increasingly complex in nature, often being used to drive multiple agendas. For example, there is an increasing move to develop learning cities which seek to draw on synergies to both improve citizen learning and skills as well as economic regeneration. Such synergy-driven learning communities, of which the learning cities are but one example, seek to utilise interaction to develop 'emergent products', be it at the individual level or the system-wide level, which could not be produced in isolation. Successfully enabling emergence is critical to their success. Designing for specific types of emergence is however difficult given the intrinsic unpredictability of complex systems. Insight into the intrinsic characteristics of these synergy-driven learning communities and how their interaction leads to emergence over time is required. This paper reports on the methodology developed to explore these highly complex learning communities. The approach adopted was to combine exploratory case studies which established the intrinsic characteristics of the learning communities with an exploration of emergence guided by a meta-level conceptual framework of emergence. This was augmented by secondary data to aid triangulation and provide rigour. As well as discussing the rationale for the adopted approach, implementation issues and the rich information set obtained are discussed using specific case examples. Findings from the investigations led to recommendations regarding future development of appropriate methods for seeding and managing such complex learning communities. The meta level framework means the approach may be readily adapted to other complex social system

Critical thinking and systems thinking: towards a critical literacy for systems thinking in practice

About the book: In reflective problem solving and thoughtful decision making using critical thinking one considers evidence, the context of judgment, the relevant criteria for making the judgment well, the applicable methods or techniques for forming the judgment, and the applicable theoretical constructs for understanding the problem and the question at hand. In this book, the authors present topical research in the study of critical thinking. Topics discussed include developing critical thinking through probability models; the promotion of critical thinking skills through argument mapping; an instructional model for teacher training in critical thinking; advanced academic literacy and critical thinking and critical thinking and higher education

Education as a Complex System: Conceptual and Methodological Implications

Education is a complex system, which has conceptual and methodological implications for education research and policy. In this article, an overview is first provided of the Complex Systems Conceptual Framework for Learning (CSCFL), which consists of a set of conceptual perspectives that are generally shared by educational complex systems, organized into two focus areas: collective behaviors of a system, and behaviors of individual agents in a system. Complexity and research methodologies for education are then considered, and it is observed that commonly used quantitative and qualitative techniques are generally appropriate for studying linear dynamics of educational systems. However, it is proposed that computational modeling approaches, being extensively used for studying nonlinear characteristics of complex systems in other fields, can provide a methodological complement to quantitative and qualitative education research approaches. Two research case studies of this approach are discussed. We conclude with a consideration of how viewing education as a complex system using complex systems’ conceptual and methodological tools can help advance education research and also inform policy

Community and Environmental OR: Towards a New Agenda

About the book: Community Operational Research: OR and Systems Thinking for Community Development sets out the current concerns of Community Operational Research (Community OR for short) and explores new possibilities for its continued development. Leading Community OR writers, with international reputations in operational research and systems thinking, have contributed chapters that illuminate different aspects of Community OR theory and practice. There is a focus on the value of systems approaches, and other significant perspectives are also represented. The result is a rich mix of theories, methodologies and case studies that will be a significant resource for both practitioners and academics engaged in community development

Randomised controlled trials of complex interventions and large-scale transformation of services

Complex interventions and large-scale transformations of services are necessary to meet the health-care challenges of the 21st century. However, the evaluation of these types of interventions is challenging and requires methodological development. Innovations such as cluster randomised controlled trials, stepped-wedge designs, and non-randomised evaluations provide options to meet the needs of decision-makers. Adoption of theory and logic models can help clarify causal assumptions, and process evaluation can assist in understanding delivery in context. Issues of implementation must also be considered throughout intervention design and evaluation to ensure that results can be scaled for population benefit. Relevance requires evaluations conducted under real-world conditions, which in turn requires a pragmatic attitude to design. The increasing complexity of interventions and evaluations threatens the ability of researchers to meet the needs of decision-makers for rapid results. Improvements in efficiency are thus crucial, with electronic health records offering significant potential

Why study movement variability in autism?

Autism has been defined as a disorder of social cognition, interaction and communication where ritualistic, repetitive behaviors are commonly observed. But how should we understand the behavioral and cognitive differences that have been the main focus of so much autism research? Can high-level cognitive processes and behaviors be identified as the core issues people with autism face, or do these characteristics perhaps often rather reflect individual attempts to cope with underlying physiological issues? Much research presented in this volume will point to the latter possibility, i.e. that people on the autism spectrum cope with issues at much lower physiological levels pertaining not only to Central Nervous Systems (CNS) function, but also to peripheral and autonomic systems (PNS, ANS) (Torres, Brincker, et al. 2013). The question that we pursue in this chapter is what might be fruitful ways of gaining objective measures of the large-scale systemic and heterogeneous effects of early atypical neurodevelopment; how to track their evolution over time and how to identify critical changes along the continuum of human development and aging. We suggest that the study of movement variability—very broadly conceived as including all minute fluctuations in bodily rhythms and their rates of change over time (coined micro-movements (Figure 1A-B) (Torres, Brincker, et al. 2013))—offers a uniquely valuable and entirely objectively quantifiable lens to better assess, understand and track not only autism but cognitive development and degeneration in general. This chapter presents the rationale firstly behind this focus on micro-movements and secondly behind the choice of specific kinds of data collection and statistical metrics as tools of analysis (Figure 1C). In brief the proposal is that the micro-movements (defined in Part I – Chapter 1), obtained using various time scales applied to different physiological data-types (Figure 1), contain information about layered influences and temporal adaptations, transformations and integrations across anatomically semi-independent subsystems that crosstalk and interact. Further, the notion of sensorimotor re-afference is used to highlight the fact that these layered micro-motions are sensed and that this sensory feedback plays a crucial role in the generation and control of movements in the first place. In other words, the measurements of various motoric and rhythmic variations provide an access point not only to the “motor systems”, but also access to much broader central and peripheral sensorimotor and regulatory systems. Lastly, we posit that this new lens can also be used to capture influences from systems of multiple entry points or collaborative control and regulation, such as those that emerge during dyadic social interactions

Introspective physicalism as an approach to the science of consciousness

Most ‘theories of consciousness’ are based on vague speculations about the properties of conscious experience. We aim to provide a more solid basis for a science of consciousness. We argue that a theory of consciousness should provide an account of the very processes that allow us to acquire and use information about our own mental states – the processes underlying introspection. This can be achieved through the construction of information processing models that can account for ‘Type-C’ processes. Type-C processes can be specified experimentally by identifying paradigms in which awareness of the stimulus is necessary for an intentional action. The Shallice (1988b) framework is put forward as providing an initial account of Type-C processes, which can relate perceptual consciousness to consciously performed actions. Further, we suggest that this framework may be refined through the investigation of the functions of prefrontal cortex. The formulation of our approach requires us to consider fundamental conceptual and methodological issues associated with consciousness. The most significant of these issues concerns the scientific use of introspective evidence. We outline and justify a conservative methodological approach to the use of introspective evidence, with attention to the difficulties historically associated with its use in psychology

Interactive situation modelling in knowledge intensive domains

Interactive Situation Modelling (ISM) method, a semi-methodological approach, is proposed to tackle issues associated with modelling complex knowledge intensive domains, which cannot be easily modelled using traditional approaches. This paper presents the background and implementation of ISM within a complex domain, where synthesizing knowledge from various sources is critical, and is based on the principles of ethnography within a constructivist framework. Although the motivation for the reported work comes from the application presented in the paper, the actual scope of the paper covers a wide range of issues related to modelling complex systems. The author firstly reviews approaches used for modelling knowledge intensive domains, preceded by a brief discussion about two main issues: symmetry of ignorance and system behaviour, which are often confronted when applying modelling approaches to business domains. The ISM process is then characterized and critiqued with lessons from an exemplar presented to illustrate its effectiveness