Learning Change

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Learning Change Project

Written by learningchange

15/06/2012 at 09:19

Posted in Change, Learning

Tagged with ,

Thinking in Complexity about Learning and Education: A Programmatic View

In this contribution the focus is on sketching a programmatic view of thinking in complexity about learning and development. This kind of thinking goes beyond linear thinking. The new thinking in complexity about a dynamic complex reality may enable us to build a new science of learning and education, which does not take the nonlinear complex reality for granted, but regards it as “real”: a science with a framework that does not exist yet. A new vision on learning is presented which takes the concept of interaction as a key concept, which may be linked with the notion of dynamic complexity. Thinking in complexity has its focus on “that which is interwoven”. Learning and development through interaction may thus be viewed as a way of co‐creating ourselves within a web of reciprocal relationships with the other. This co‐creation may be described as a complex of self‐generative, self‐sustaining processes of mutual “bootstrapping” with potentially nonlinear effects over time. Modelling learning this way, may show learning to be a potentially nonlinear phenomenon within a new reality as the domain of possibilities and potentialities of learning. The modelling of such learning as “bootstrapping,” and the concomitant effects on both partners in the interaction, shows these very possibilities and potentialities of learning in their humanly connected spaces of possibility. It demonstrates the very truth of Vygotsky’s adage that “it is through others that we develop into ourselves.” Based on his thoughts, we are able to develop a new view of the complex nonlinear reality of learning and education, with learners as potentially nonlinear human beings.


Read also: Thinking in Complexity: A New Paradigm for Learning

Theorizing Learning through Complexity: An Educational Critique

Written by learningchange

24/04/2014 at 15:10

Chaos Theory and the Sciences of Complexity: Foundations for Transforming Education

An understanding of chaos theory and the sciences of complexity is crucial to systemic transformation of our educational systems to better meet the rapidly changing needs of our children and communities. Helpful concepts include co-evolution, disequilibrium, positive feedback, perturbance, transformation, fractals, strange attractors, self-organization, and dynamic complexity. These concepts can help us to understand (a) when a system is ready for transformation, and (b) the system dynamics that are likely to influence individual changes we try to make and the effects of those changes. Furthermore, chaos theory and the sciences of complexity can help us to understand and improve the transformation process as a complex system that educational systems use to transform themselves. Strange attractors and leverage points are particularly important to help our educational systems to correct the dangerous evolutionary imbalance that currently exists.


A Fresh Take on Democratic Education: Revisiting Rancière through the Notions of Emergence and Enaction

This paper aims at contributing to new ways of thinking about democratic education. We discuss how revisiting this concept may help raise fresh questions in relation to non-formal fora grappling with intricate sustainability issues that span international borders. Starting from Rancière’s ideas on democracy, we first examine a conception of democratic education derived from these ideas. Next, we turn to a complexity informed notion of education as proposed by the two strands of emergence and enaction. We discuss how, in introducing additional dimensions, these strands might fruitfully complement the Rancierian conception of education. We conclude our discussion by proposing to reposition democratic education as a process of (co)-emergence afforded by a series of critical moments which, we suggest, can call forth radically novel visions for governing the commons.

The present paper is structured as follows: After a brief overview of writings that we found relevant for the ensuing discussion, we introduce Rancière’s thinking on democracy and democratic practices. We show how this thinking informs recent theorizing on democratic education. We next compare what we shall call a Rancierian conception of education with one informed by complexity, more precisely, its two strands of emergence and enaction. We highlight how we see the two ways of thinking about education as complementary in several respects. Finally, we discuss implications of combining these approaches in relation to the notion of novelty. As the recent Occupy movements – along with transboundary environmental activism – illustrate, formal policies currently presented as democratic are increasingly contested. All too often, the logic to which national governments and their teams of experts adhere are found inappropriate for addressing intricate and uncertain problems, the scope of which tends to span national boundaries. Change seems instead to happen at the edge as collective experiments seek novel ways of tackling such problems.


Written by learningchange

24/04/2014 at 00:21

Curriculum Studies Based on Complexity Science

Complexity science is in the forefront of contemporary scientific development; its rise and development triggered the breakthrough and innovation of methodology in scientific research. Curriculum is a complex adaptive system. Complexity curriculum research also includes nonlinearity, uncertainty, self-organization and emergent properties.

To look at and examine the school curriculum from a complex scientific theory helps us understand, interpret, and handle complex curriculum issues, and helps us to master the complexity of the curriculum system during the practice of specific curriculum reform. At the same time, it also has some practical significance and inspiration value for our understanding and awareness of the current systemic reform of basic education: its curriculum, complexity, difficulties. Now, the complexity of curriculum studies is in the ascent, although its research mission still has a long way to go. We’re just on the road.


Written by learningchange

24/04/2014 at 00:04

Fitting Teacher Education in/to/for an Increasingly Complex World

Oriented by complexity thinking and informed by a selection of “game-changing” research findings in the educational literature, we describe a set of innovations to a teacher education program. These innovations include broad awareness of theories of learning, specialization across levels, integration of pre-service and in-service offerings, a developmental curriculum, and deep partnerships with schools.

Across the sort of teacher education initiatives we have described, a central goal is to dislodge public education from its rut of common sense – that is, unquestioned structures, uninterrogated practices, unnoticed simplifications. What might happen when differences in theoretical perspective are framed in terms of productive conversation rather than reductive argument? Our guess is that such shifts in emphasis will help to move the cultural project of education to a new place, away from an ethos of segregated action and separated interests into a space of mutual challenge, joint interest, collective production. Importantly, the principal site of this cultural project is teacher education.


Written by learningchange

23/04/2014 at 23:54

Schools and Complexity

In order for complex systems to change sustainably, agents at various levels of those systems must interact with each other, and control must be distributed in such a way as to “promote individual autonomy and enrich communication” amongst the systems’ various levels. The practical implication of this is that each school system implementing an effort at instructional improvement must establish and maintain a common direction while also allowing individual actors – principals, teachers, and other educators – to make decisions that are appropriate for them and their local constituencies.

As schools, districts, and the overall education system are complex entities, both the approaches taken to improve them and the methods used to study them must be similarly complex. Simple solutions imposed with no regard for schools’ or districts’ unique contexts hold little promise, while seemingly insignificant differences between those contexts affect in seemingly disproportionate ways the quality and success with which they implement the same programs. Context must be taken very much into account when initiatives are planned and implemented, as well as when their impacts are investigated.


Improving Online Deliberation with Argument Network Visualization

Social media are increasingly used to support online debate and facilitate citizens’ engagement in policy and decision-making. Nevertheless the online dialogue spaces we see on the Web today typically provide flat listings of comments, or threads that can be viewed by ‘subject’ line. These are fundamentally chronological views which offer no insight into the logical structure of the ideas, such as the coherence or evidential basis of an argument. This hampers both quality of users’ participation and effective assessment of the state of the debate. We report on an exploratory study in which we observed users interaction with a collective intelligence tool for online deliberation and compared network and threaded visualizations of arguments. We contend that animated argument networks enhance online debate reading when data complexity increases, improve understanding of the argumentation data model and promote users engagement by improving users emotional reactions to the online discussion tool.


The Evidence Hub: Harnessing the Collective Intelligence of Communities to Build Evidence-Based Knowledge

Conventional document and discussion websites provide users with no help in assessing the quality or quantity of evidence behind any given idea. Besides, the very meaning of what evidence is may not be unequivocally defined within a community, and may require deep understanding, common ground and debate. An Evidence Hub is a tool to pool the community collective intelligence on what is evidence for an idea. It provides an infrastructure for debating and building evidence-based knowledge and practice. An Evidence Hub is best thought of as a filter onto other websites — a map that distills the most important issues, ideas and evidence from the noise by making clear why ideas and web resources may be worth further investigation. This paper describes the Evidence Hub concept and rationale, the breath of user engagement and the evolution of specific features, derived from our work with different community groups in the healthcare and educational sector.

The Evidence Hub is a contested collective intelligence tool for communities to gather and debate evidence for ideas and solutions to specific community issues. By aggregating and connecting single contributions the Evidence Hub provides a collective picture of what is the evidence for different ideas, which have been shared by an online community.


Towards a Global Participatory Platform – Democratising Open Data, Complexity Science and Collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate ´elites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including, but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of  self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.


Managing systemic risk using systems thinking in practice

Managing uncertainties associated with, say, water security, toxic wastes, or biotechnology, invites growing relevance from the field of complexity sciences that everything is connected. Systems ideas such as complex adaptive systems or the ecosystems approach have consequently gained attention in recent years for promoting more joined-up thinking. But such ideas of systems have limited currency. Issues about interconnections – and calls for joined-up thinking – ought not to be seen in isolation from related systems issues of multiple values and different stakeholder perspectives. Moreover, such issues are related to political issues of partiality and selectivity – that is, system boundary judgements that circumscribe perspectives. A practical dimension of systems thinking using the metaphor of conversation and creative space prompts a more systemic appreciation of real world interconnections in relation to multiple perspectives and boundary judgements. Systems thinking in practice provides a more appropriate systemic space for managing systemic risk.


Written by learningchange

23/04/2014 at 22:22


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