Where has creativity gone?

Findings from this post on creativity sounds too good for me.  Thanks to Ana Cristina for the link.

For all the talk of creativity in business, industry and academia, there’s evidence that it’s implicitly discouraged in these areas as well. Although leaders of organisations say they want creative ideas, the evidence suggests creativity gets rejected in favour of conformity and uniformity (Staw, 1995 cited in Mueller et al., 2011).

I shared this in my post.  Here in Creativity and creative learning, how is it valued in community, and schools?

So really, what we are being told is, “be creative, but not TOO creative”. Any creative ideas that attempt to shift the current paradigm or reject a paradigm completely are usually driven by extreme passion, and almost always met with some type of resistance from society. We are left with the choice of (1) give up on our ideas, or (2) put up a hell of a fight to defend them.  Those who decide to stand their ground and fight for their creative ideas are the ones who are generally seen as “rule-breakers”, “rebels”, “trouble-makers”, or simply, “obnoxious”. And the ideas generated by those individuals are generally the most creative, innovative, and necessary ideas to support.

That may be the protocols and norms set by our community, society, as part of the cultures.  How to be creative, yet be perceived as constructive, as a valued citizen (a worker, an educator, a researcher, an artist, a learner) could be interesting for me to re-visit.

What we need would be renewed ways of supporting and developing ours’ and our fellow students’ creativity in their search and exploration of knowledge, whilst constructing and navigating through the networks and communities, and  the teaching and learning activities and tasks in classes, networks and communities.

These need to be based on creative learning principles where strategies could be developed ranging from different pedagogies – including peer-to-peer learning (peeragogy, as espoused by Howard Rheingold), and peer learning with active learning, participatory pedagogy,participatory action research, and online conversation as part of the learning pedagogy etc.  These aligned with some of the elements of networked principles and Connectivism as discovered in MOOC, as elaborated here by Stephen Downes.

You may find this interesting to watch:

I will come back to reflect and comment.

How about you?

Postscript: Another video on Creative Genius.

 

Chaos Theory, Fractals, knowledge and learning – Part 2

Fractals are indeed also embedded in curation, and in subsequent conversation, by the agent (learner) through internal conversation with him/herself, and that with others in a complex learning environment, social networks, and community of networks.

Such fractals are part of the phenomena associated with the Chaos Theory.  It seems nearly impossible to make long-term predictions about online conversation where large number of agents are interacting with each others, as in the case of MOOCs.  Such conversations are highly sensitive to small initial perturbations (Fractals and Chaos Theory).  This also explains the often difficult to predict and control sort of conversation in open spaces, where constraints over what and how conversation is based on moderation by the agents (the professors, educators, and certain participants in the case of MOOCs).

How would fractals and Chaos Theory help in understanding more about the changes and transformation of our education system?

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.  (Reigeluth, 2004)

How have strange attractors impacted on MOOCs, in particular on xMOOCs?

The most powerful strange attractors are core ideas and beliefs like those described earlier: ownership and empowerment, customization and differentiation, and shared decision making and collaboration.

How is Chaos Theory used in lesson planning and delivery?

The use of Chaos Theory in lesson planning and delivery is discussed in this paper. The author argues that planning for a lesson needs to take into account any changes in the lesson, building in elements of interests, and responding to the chaos in a dynamic way so as to make order out of chaos, especially when there are always strange attractors changing the stability of the equilibrium of the system.

Chaos Theory, Fractals, Knowledge and Learning – Part 1

This post is devoted to explore and reflect on Chaos Theory, Fractals, Knowledge and Learning.

How to describe knowledge and learning at this digital age?

One way is to describe knowledge as a network phenomena, under Connectivism.

How is learning achieved in MOOCs?

If people want to learn simple factual information (and content and procedural knowledge), best practice, go to school, or attend the xMOOCs.  In this xMOOC movement:

The potential is boundless, according to some educational specialists, they see it as a way of providing students in the developing world with access to the international educational ladder.

But while they also allow students to interact with each other, is this online experience a step too far and is there an opportunity for universities to try more for a mix of teaching methods?

If people want to learn complex, emergent knowledge and practice, they could join the online community, and immerse in the open, digital, vibrant cMOOCs.  In a connectivist MOOC, the best interactive lectures are un-lecture (through shifting preaching or “one-way lecturing” to dialogues, critiques, and conversation), and best learning comes from networked learning action, reflection cycle, with focus on metacognition integrated and embedded in each learning experience. Best practice is contingent to the actual needs of the engaging agents, to collaborate and cooperate in solving problems, where each one’s interests are catered for.  This is where complex pattern could be boiled down to simple heuristics, easy to understand and mutually agreeable language patterns.

What I have been thinking of is the use of Fractals in understanding knowledge and learning.

If we were to conceive knowledge as conversation, & that a set of connections (the engagement), I could also interpret this as a development like the fractals, where such fractal would repeat itself but its shape would be based on initial conditions of agents, with “spirals” & re-birth or re-configuration of different fractals (patterns) emerging in different forms.  Such fractal formation would be dependent on feedback and looping back into other posts, via the linkage, and thus could be amplified or dampened as the pattern developed.

Another application of fractals would be to conceive the footprint of emergence as a pattern that relates to fractal development in emergent knowledge and learning development.

The role of organising emergent learning ‘scapes is an engaged curatorial role, rather than a teaching, facilitating, or even moderating one. Curating the topography of learning requires the course convenor to step back at times; it not only invites but requires self-organization, self-motivation, and creativity.

Refer to Learning across Cultures (R Williams, J Mackness, S Gumtau – researchgate.net)

Emergent learning is likely to occur when many self-organising agents interact frequently and openly, with considerable degrees of freedom, but within specific constraints; no individual can see the whole picture; and agents and system co-evolve (3).

The properties of emergent learning – based on interaction would then form the basis of fractals, where such interactions repeat in various forms, as in the case of rhizomatic learning, or in connectivist learning all based on interaction and connectivity.