CCK09 Open and closed systems thinking and Complex Adaptive System

When thinking about organisations it is necessary to distinguish between closed-system thinking and open-system thinking.
In closed-system thinking there is a tendency to regard the enterprise as sufficiently independent to allow most of its problems to be analysed with reference to its internal structure and without reference to its external environment.  This approach tends to lead to a static view which ignores imbalance caused by influences coming from the environment (and resulting change).
In open systems thinking, there is the logical implication that such systems may spontaneously re-organise towards state of greater heterogeneity and complexity and that they achieve a steady state at a level where they can still do work.
Organisational problems come from disturbances to regularity caused by (1) changing market environments, (2) changes affecting labour, materials and technology.
The flexibility of an organization’s technology affects its reaction to change.  Some organisations can simply change their internal technology in the face of change.  Others, with rigid technology, have to adapt by changing their structures.  Thus technology is an important boundary condition mediating between the organisation and its environment.  Because of its importance alongside the human factors it becomes useful to think of an organisation as an open socio-technical system (Emery 1969).
It is therefore imperative to understand the impact of ICT & Web 2.0 on organisations, the people and the systems.
A CAS is a complex, self-similar collection of interacting adaptive agents. The study of CAS focuses on complex, emergent and macroscopic properties of the system. Various definitions have been offered by different researchers:
A Complex Adaptive System (CAS) is a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents.[1]
A CAS behaves/evolves according to three key principles: order is emergent as opposed to predetermined (c.f. Neural Networks), the system’s history is irreversible, and the system’s future is often unpredictable. The basic building blocks of the CAS are agents. Agents scan their environment and develop schema representing interpretive and action rules. These schema are subject to change and evolution.[2]

From wikipedia (complex adaptive systems)


Under connectivism, it is trying to explain the learning under an open learning system (the informal and non-formal learning (PLN/PLE), and the formal learning (LMS), face-to-face, blended based on various connections, and learning due to the immersion in the networks (real and virtual).  So this is cutting across the open and closed system and their boundary, and in most cases, it would be covering both the open system with Web 2.0 – social media and the closed system with classroom and the blended learning when online learning is involved.
That also explains why I would like to apply connectivism on organisational learning.  However, I think the application of an open-system thinking on a closed or semi-closed-open systems (such as an organisation or educational institution) will need certain adjustment, in order to balance the self-organised local relationship that may exist in an open system and the structured functional relationship in a closed system.
Due to the fuzziness and often overlapping areas of social media of these open-closed systems, there would be emergent leadership and learning  arising from such media and networks interaction.  In this Community of Practice (COP):
Diverse approaches to supporting communities of practice have been adopted by different organizations: some see them as largely emergent phenomena, others have adopted more deliberate strategies to design and manage their shape and purpose. A community of practice is fundamentally a self-organizing collection of volunteers. Knowledge is shared within the community based on relationships with others, rather than direct transactions. Hence membership involves an emotional as well as an intellectual component
So, COP is trying to accommodate for the close-system thinking (geared towards both the organisation’s and network’s needs, though trying to accomodate individual’s autonomy), where community members could still practise in an open-system thinking (a hybrid of open-closed system thinking) in a network.  In many COPs, many participants still prefer to be the legitimate peripheral participants (lurkers) rather than active participants.  Also the voices raised by the COP would be a perfect  way of letting people to “release their emotions and speak their voices”.  It depends on the organisations’ leadership and culture in terms of responses to such voices…
Think about your networks.  Your friends, your colleagues, your social circle.  How new networks take shape through introductions at parties, over coffee breaks, via email.  How your connections have helped you, supported you and hindered you. 

They are all around us. We rely on them. We are threatened by them. We are part of them. Networks shape our world, but they can be confusing: no obvious leader or centre, no familiar structure and no easy diagram to describe them. Networks self-organise, morphing and changing as they react to interference or breakdown.

Networks are the language of our times, but our institutions are not programmed to understand them.

As individuals, we have taken advantage of the new connections: to earn, learn, trade and travel. But collectively we don’t understand their logic. Our leaders and decision-makers have often failed to grasp their significance or develop adequate responses. We do not know how to avoid internet viruses or manage mass migration, structure urban communities, regulate global financial markets or combat networked terror.

So now we live in a world held together by networks, but lacking the language to solve its common problems. We’re left with a sense of unease – a governance gap that needs to be bridged.

In summary, I think using a complexity approach does help in identifying some of the aspects in organisation (when it comes to vision and mission statement development, strategic planning and action etc.  A COP may be an alternative approach to resolve some of the issues that arise from the impact of open systems (i.e organisational problems come from disturbances to regularity caused by (a) changing market environments, (b) changes affecting labour, materials and technology, and in case of education institution (changing needs of education (vision and mission), clients (learners), and employers).
So I think it is important to appreciate the differences between an open and closed systems thinking in order to ensure the proper application of connectivism or networked learning principles in education, business institutions and enterprises.
Networks are the language of our times.  We need to understand the language to solve problems.


1. Community of Practice

2. F.E. Emery (ed.) 1969. Systems Thinking, London, Penguin




5 thoughts on “CCK09 Open and closed systems thinking and Complex Adaptive System

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  3. Hi John,
    The discussion of open and closed systems is an important understanding- thanks! I also found some of the thinking on systems intelligence and complex responsive processes an interesting avenue to pursue. My understanding is that these concepts are more receptive to or able to accomodate emergent phenomena… although this is a pretty simplified statement and I’m still digesting it all! I started with “Systems Thinking in Complex Responsive Processes and Systems Intelligence” ( — might be worth a look!

  4. Hi Carmen,
    I am intrigued by the ideas behind this wonderful paper. Systems intelligence and complex responsive processes provide a rich concept on “system thinking”. I think it provides an alternative framework for thinking – and it highlights the importance of emergence, rather than the focus on the components of systems – a rather static view.

    I could relate to the MOOC – CCK and now PLENK experience, in that I would need to “participate” in it in order to make sense of the notion of emergence of networks and their behavior. I could see that the individuals (participants including the facilitators) and “organisation” (ie. PLENK) would co-evolve. One could not predict precisely what the outcomes would be, based on the system working model (the traditional course structure, learning outcomes, assessment etc.).

    Would this explain why so many participants find it hard to “believe” that PLENK would ever work in a formal institutional course basis? If we are trying to force an open system thinking (PLENK with loose structure, individualised learning “outcomes” and no assessment) into a closed system model (a predictive structural course, with defined learning outcomes), surely there would be great challenges (and issues) – like putting jigsaws together without a clear pattern. The pattern of PLENK is in fact EMERGENT.
    Based on the concept of system thinking, the “course – MOOC or MOON (Massive Open Online Network)” would need to co-evolve with individuals (participants, facilitators) and organisation (the institution) (and the networks so formed) through active participation in order to adapt to the changes resulting from the individuals (actors, agents) acts and responses (the gesture response concept).

    “systems intelligence sees systems as constructs and thus relative to the point of view. Systems intelligence highlights the role of the strong dependence of the assumptions held by individuals of systems they are a part of. On the negative side, such characteristic of human systems can be seen to drive systems towards repetitive and undesirable behavioural patterns. These systems are perpetually evolving wholes which are only seemingly fixed, yet they
    potentially give rise to illusions of command and fixedness” That is a wonderful explanation of why command and control in systems which are perpetually evolving could lead to failure.

    That also explains why so many strategic plans and actions, and the day to day controls often fail when one consider systems to be fixed and rigid, without consideration of the emergence arising out of the system.

    I still have to digest it more…
    Thanks Carmen for this stimulating piece and your comment.


  5. Pingback: Are MOOCs behaving like a Complex Adaptive System? | Learner Weblog

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