Under the name of Excellent Areas ("Excellente Gebieden"), a number of Dutch home construction companies and municipalities are engaged in an experiment to use the building standards of 2015 and 2020, today. By the nature of these future building standards, there is much to learn for these actors before they can profitably apply them.
AgentschapNL is the facilitator of the Exemplary Neighborhoods project, and they asked us to evaluate the instruments they have set up for the learning trajectory.
The most important programme of this experiment centres around learning. What are the issues that these actors – home owners, construction companies, municipalities, energy companies, advisors – run into? And how does everyone deal with them?
We used the three steps of transition learning to structure this research, namely: deepening, broadening and scaling up. Deep learning is about applying a specific new solution to a particular problem. Broad learning involves applying that new solution to other cases of the same or a similar problem. Learning to scale up, finally, means that these new solutions can become more standardised and can be applied by many more actors.
Our evaluation process of Excellent Areas started with establishing what we could hope to learn about the programme. In which areas could its functioning be assessed? And how? Based on the trichotomy of deepening, broadening and learning, we organised a series of semi-open questions on the one hand and a series of interviews on the other. The outcome of the 18 interviews was structured and then analysed for patterns.
We concluded that the instruments so far developed deal very well with deepening and broadening learning, but that there is a still underdeveloped attention for scaling up learning. Since the programme started in 2010, it is not too late to further develop this.