Footprints of emergence

It is ironic that the management of education has become more closed while learning has become more open, particularly over the past 10-20 years. The curriculum has become more instrumental, predictive, standardized, and micro-managed in the belief that this supports employability as well as the management of educational processes, resources, and value. Meanwhile, people have embraced interactive, participatory, collaborative, and innovative networks for living and learning. To respond to these challenges, we need to develop practical tools to help us describe these new forms of learning which are multivariate, self-organised, complex, adaptive, and unpredictable. We draw on complexity theory and our experience as researchers, designers, and participants in open and interactive learning to go beyond conventional approaches. We develop a 3D model of landscapes of learning for exploring the relationship between prescribed and emergent learning in any given curriculum. We do this by repeatedly testing our descriptive landscapes (or footprints) against theory, research, and practice across a range of case studies. By doing this, we have not only come up with a practical tool which can be used by curriculum designers, but also realised that the curriculum itself can usefully be treated as emergent, depending on the dynamicsbetween prescribed and emergent learning and how the learning landscape is curated

Towards a competency model for adaptive assessment to support lifelong learning

Adaptive assessment provides efficient and personalised routes to establishing the proficiencies of learners. We can envisage a future in which learners are able to maintain and expose their competency profile to multiple services, throughout their life, which will use the competency information in the model to personalise assessment. Current competency standards tend to over simplify the representation of competency and the knowledge domain. This paper presents a competency model for evaluating learned capability by considering achieved competencies to support adaptive assessment for lifelong learning. This model provides a multidimensional view of competencies and provides for interoperability between systems as the learner progresses through life. The proposed competency model is being developed and implemented in the JISC-funded Placement Learning and Assessment Toolkit (mPLAT) project at the University of Southampton. This project which takes a Service-Oriented approach will contribute to the JISC community by adding mobile assessment tools to the E-framework

Comparing instance-averaging with instance-saving learning algorithms

The goal of our research is to understand the power and appropriateness of instance-based representations and their associated acquisition methods. This paper concerns two methods for reducing storage requirements for instance-based learning algorithms. The first method, termed instance-saving, represents concept descriptions by selecting and storing a representative subset of the given training instances. We provide an analysis for instance-saving techniques and specify one general class of concepts that instance-saving algorithms are capable of learning. The second method, termed instance-averaging, represents concept descriptions by averaging together some training instances while simply saving others. We describe why analyses for instance-averaging algorithms are difficult to produce. Our empirical results indicate that storage requirements for these two methods are roughly equivalent. We outline the assumptions of instance-averaging algorithms and describe how their violation might degrade performance. To mitigate the effects of non-convex concepts, a dynamic thresholding technique is introduced and applied in both the averaging and non-averaging learning algorithms. Thresholding increases the storage requirements but also increases the quality of the resulting concept descriptions

Making space for proactive adaptation of rapidly changing coasts: a windows of opportunity approach

Coastlines are very often places where the impacts of global change are felt most keenly, and they are also often sites of high values and intense use for industry, human habitation, nature conservation and recreation. In many countries, coastlines are a key contested territory for planning for climate change, and also locations where development and conservation conflicts play out. As a “test bed” for climate change adaptation, coastal regions provide valuable, but highly diverse experiences and lessons. This paper sets out to explore the lessons of coastal planning and development for the implementation of proactive adaptation, and the possibility to move from adaptation visions to actual adaptation governance and planning. Using qualitative analysis of interviews and workshops, we first examine what the barriers are to proactive adaptation at the coast, and how current policy and practice frames are leading to avoidable lock-ins and other maladaptive decisions that are narrowing our adaptation options. Using examples from UK, we then identify adaptation windows that can be opened, reframed or transformed to set the course for proactive adaptation which links high level top-down legislative requirements with local bottom-up actions. We explore how these windows can be harnessed so that space for proactive adaptation increases and maladaptive decisions are reduced