AbstractThe challenges posed by a rapidly changing climate, associated uncertainties and complexities are leading to a greater recognition of the need to accelerate and enhance how learning occurs, in the field of climate change and associated practice. Whilst learning has an essential role in addressing environmental challenges, there is a lack of tools and understanding of processes of learning within current resilience research. Given the increasing need to learn more quickly and more effectively in light of growing challenges, this thesis aimed to explore learning across academic, practical and policy areas in an attempt to understand how learning occurs within the disaster risk reduction (DRR) sector.
This research aims to advance perspectives and knowledge in understanding how to enhance multi-actor learning in Disaster Risk Reduction contexts. It has done this by focusing on the complexity of multi-actor learning in the DRR sector in Scotland across two related studies. The first study provides a review of learning processes across Integrated Emergency Management across Scotland. The second study then explores role of learning journeys and the processes which occur within them through the Scottish Borders Climate Resilient Communities (SBCRC) project.
A total of 89 in-depth semi structured interviews were completed with participants across different stakeholder groups from both organisations and community settings. This supported the development of a theoretical and methodological innovation through the form of Visually Augmented Elicited Metaphor Analysis (VAEMA) which helps to explore the experience of learning and the wider processes which emerge using the concept learning as a journey. This research therefore provides a rich description through the development of a framework explaining how multi-actor learning both across and within different stakeholder groups occurs. The research finds that learning in DRR contexts relies on varied interactive and social processes which are underpinned by various structural, political and cultural contexts. The framework recognises that learning in complexity is rooted in problem-based situated learning whereby new learning occurs through the process of interacting as a hyper extensive network (Engeström, 1987). Therefore, in order to create more inclusive and equitable learning opportunities as well as reduce environmental hazard risks and underlying causes of vulnerability, the role of context and culture and its relationship with learning must be better understood.
There are four findings in total. Firstly, this research provides a review of 15 distinct tools and processes identified for learning in the DRR sector, which can be appraised on their co-benefits and contribution toward wider DRR efforts. Such processes tend to tackle structural or cultural challenges which are responsive to the learning needs of a rapidly changing world. In contrast, some processes for learning can be considered to deliver less profound change which in turn reinforces existing systems. Secondly, processes of learning are highly interactive social experiences which are enabled through a variety of supportive cultures, structures and motivations.
Thirdly, the research highlights that when people learn through complex social processes that this experience enhances other adaptive expertise needed for future initiatives. These include the development of capacities, changes in underlying relationships of governance and the development of new relationships, partnerships and collaborations. This demonstrates that such interventions are not only important for initial learning, but might contribute to the development of future initiatives which may lead onto deeper learning experiences.
Thus problem-based situated learning is a valuable process for enhancing resilience. Lastly, an integrated framework is provided which recognises six key factors for effective learning in DRR contexts, these are: time, scale, depth, reflexivity, design and facilitation. This framework highlights not only what factors for learning are important, but illustrates how learning in DRR contexts can be further enhanced.
|Date of Award||2019|
|Sponsors||Economic and Social Research Council & Scottish Government|
|Supervisor||Ioan Fazey (Supervisor) & Fiona Smith (Supervisor)|
- Disaster Risk Reduction
- Learning Process
- Multi-Actor Learning