Forays into complexity theory with students at the centre of data actions and decisions – Heidi Swak | The Amaryllis | A learning journey …


Source: Forays into complexity theory with students at the centre of data actions and decisions. | The Amaryllis | A learning journey …


Forays into complexity theory with students at the centre of data actions and decisions.

A constant education question for over 100 years has been:

What are the knowledge, skills, and dispositions students need in an age of rapid technological, environmental, social, and political change and where the future of work is unknown?

My own work with middle school students in relation to this question and prior to a 3 year secondment to government, focused on equipping students with thinking and problem-solving skills to take on the really difficult, messy problems that we humans are so good at creating.  That work involved introducing students to the principles of inquiry by developing driving questions to anchor our learning. We explored tools, processes, and the principles of design and integrative thinking to uncover tensions and prototype a range of options out of those tensions. This work involved many post-it notes and a great deal of experimentation as we tested ideas, explored assumptions, and considered the implications of various problem-solving models to our identities as learners, learners in knowledge building communities, and participants in a complex world that extended beyond the classroom. I am grateful to my students and colleagues who contributed to this work.

My role at a provincial level – and which I have just left – allowed me to build on that work. For the past three years I’ve been a member of a unit supporting Innovation in Learning in a jurisdiction with about 2 million students across a wide geography and with different sub-systems. I’ve had a bird’s eye view of how different districts think about and approach innovation in learning, grounded in their local contexts. I’ve also gotten a sense of the wide range of practices and the challenges districts experience when engaged in this work. District innovation projects focused on deeper learning and developing global competencies in learners and some of that work can be seen here.

For the past year I’ve been preparing for a career transition and because of that have been deeply immersed in complexity theory and decision making in complex adaptive systems.  Part of this involved taking  an online course in decision-making in complex adaptive systems offered through Cognitive Edge.  and flying to UK this fall for a 2 day component in October to experience some of the theory and processes in person. I was able to combine the course with a two week holiday in London – something that a classroom teacher NEVER gets to do in the autumn. I savoured the moment!

As I prepare to re-enter the classroom for 6 months, I am thinking deeply about how to introduce complexity theory and decision-making in CASs to middle school students as I firmly believe students need to be working with theories and approaches to problem solving as the theories are developing so they can contribute to the knowledge base particularly as children are so adept at grappling with novel practices and ideas – in ways that adults aren’t.

From this foray into complexity theory, I’d like to share a few things that I will be inroducing to students:

The first is the Cynefin framework for understanding problem domains. David Snowden’s Cynefin Framework will help students decide which problem solving approach to take by first identifying the domains in which problems are situated. A word of caution – there is a technique to this which must be learned so that one doesn’t end up misusing the framework or using it in a very limited way which could result in students becoming stuck in old thinking. Students will not get the full benefit of Cynefin if they merely use it to categorize problems.   I highly recommend Snowden’s Ted Talk as a starting point for learning.

A second thing Snowden offers, and what drew me to his work in the first place, is a way to think differently about data. I don’t know anyone who isn’t alarmed by the intrusions data analytics seem to be making into our lives – the exploitative, stealthy, and threatening way analytic companies appear to be tightening their grip particularly as AI – whatever that is, gains prominence and the malicious way data analytics are being used for such things as inciting fear and destabilizing democracies.

Snowden offers an alternative way to engage with data.  He shows that it is possible to turn away from the dehumanizing and destabilizing data culture created by Silicon Valley-style tech companies such as Facebook, Cambridge Analytica, or the ‘personalized learning’ platforms like the one students in Brooklyn recently walked out in protest over.

Snowden’s Sensemaker®  is based on research from neuroscience,  complexity theory, and years of experience trying to make sense and make decisions in very difficult contexts (the refugee crisis, understanding terrorist networks, gender-based violence, understanding resilience and how to foster it, identifying disruptions and opportunities in business …). His tool and methodology allows humans to remain in control of the meaning of their data and to participate in decisions on how that data gets used. Data is gathered and visualized in ways that allow humans to remain the experts of their own experiences. What is really interesting is that data can be gathered in real time and at scale. One Sensemaker project involved gathering 50 000 micro-narratives over a two week period in different countries that helped decision-makers understand how radicalization was occurring and how it might be addressed.

It is incumbent upon us as educators to help students think critically about data and also point them towards tools and practices that offer more than stealth and exploitative analytics as they learn to take on complex problems such as those identified in the SDGs, or in any of the many other inquiries, projects, and problems they are drawn to.

Here is a thorough example  of what human-centered data gathering looks like, where Sensemaker was used to understand the experience of smallhold farmers in supply chains.

Over the next few months I will continue to share my learning and resources that I come across that might be helpful to advancing how students think and develop solutions to difficult problems. In January, I re-enter teaching and will document key points in practice and learning.