Last week I attended a one-day workshop led by Tony Bryk of the Carnegie Foundation called ‘Learning to Improve’. A condensed version of training that normally takes at least three days, the concept brings together threads from Improvement Science, Design Thinking and the power of networks to tackle difficult issues in rigorous, practical and innovative ways. Improving improvement? It’s educational problem-solving, Inception-style!
What if the improvement process itself is broken?
Education has its share of challenges across all different contexts. Student retention, teacher burnout, learning outcomes, language and literacy issues…the list goes on, from pre-school through to post-graduate. Educators have not been idle in trying to tackle these issues, and in the last decade in the US there appears to have been particular focus on three key approaches:
Education has its share of challenges across all different contexts. Student retention, teacher burnout, learning outcomes, language and literacy issues…the list goes on, from pre-school through to post-graduate. Educators have not been idle in trying to tackle these issues, and in the last decade in the US there appears to have been particular focus on three key approaches:
- Performance management (targets, incentives, data collection, individual accountability but little direction to form solutions);
- Evidence-based practice (proposed idea, controlled trials, ‘proven’ efficacy in one context, research added to a ‘what works’ list with 1,000+ other projects );
- Communities of practice (individuals learn from each other, but no real mechanism for accumulating and sharing more broadly).
Six Core Principles
The workshop structure of ‘Learning To Improve’ was underpinned by six core principles of improvement, which could be summarised as follows:
The workshop structure of ‘Learning To Improve’ was underpinned by six core principles of improvement, which could be summarised as follows:
- Be problem-focused and user-centred (what is the exact problem, and who is affected?);
- Accept and work with variability (it’s not what works, but rather what works, for whom and in what conditions)
- See the system behind the current outcomes (you need to understand it to improve it)
- Embrace measurement (you can’t improve what you can’t measure – qualitatively or quantitatively)
- Learn through disciplined inquiry (analyse, find patterns, test, learn from failures and repeat – or ‘Plan, Do, Study, Act’)
- Organise as networks (bring people’s skills together, accelerate testing and diffusion)
Super-charging networks
We’ve seen rising interest in crowdsourcing, the myths and realities of the wisdom of crowds and the impact of social networks on personal, study and work life, as well as fascinating research on the potential for greater innovation through networks of similar-but-different fields working on each other’s problems. Networked Improvement Communities pick up a number of these threads, working on the principle that you learn faster when you learn as a network; the harder the problem, the more you need to work in networks to solve it.
Bringing disparate individuals and groups together is no easy task, and requires focus and commitment to a common aim, at least for a period of time. A Networked Improvement Community has an explicit, user-centred problem to solve, measurable aims and a focus on understanding variability in how solutions are applied. It tests concepts and ideas through disciplined inquiry, prototyping and learning from failure, and commits to documenting and sharing activities, learnings and plans for next steps. It’s a compelling concept because it promises to get ideas into action and create change where previous approaches, including research, had disappointed. It won't be easy, but I can’t wait to see what we can do with it.
We’ve seen rising interest in crowdsourcing, the myths and realities of the wisdom of crowds and the impact of social networks on personal, study and work life, as well as fascinating research on the potential for greater innovation through networks of similar-but-different fields working on each other’s problems. Networked Improvement Communities pick up a number of these threads, working on the principle that you learn faster when you learn as a network; the harder the problem, the more you need to work in networks to solve it.
Bringing disparate individuals and groups together is no easy task, and requires focus and commitment to a common aim, at least for a period of time. A Networked Improvement Community has an explicit, user-centred problem to solve, measurable aims and a focus on understanding variability in how solutions are applied. It tests concepts and ideas through disciplined inquiry, prototyping and learning from failure, and commits to documenting and sharing activities, learnings and plans for next steps. It’s a compelling concept because it promises to get ideas into action and create change where previous approaches, including research, had disappointed. It won't be easy, but I can’t wait to see what we can do with it.