Networked learning ten years on: the rise of the virtual graduate school

The aim of this paper is to reflect on how conceptions of networked learning have changed, particularly in relation to educational practices and uses of technology, that can nurture new ideas of networked learning to sustain multiple and diverse communities of practice in institutional settings. Our work is framed using two theoretical frameworks: Giddens's (1984) structuration theory and Callon & Latour's (1981) Actor Network Theory as critiqued by Fox (2005) in relation to networked learning. We use these frameworks to analyse and critique ideas of networked learning embodied in both cases. We investigate three questions: (a) the role of individual agency in the development of networked learning; (b) the impact of technological developments on approaches to supporting students within institutional infrastructures; and (c) designing networked learning to incorporate Web 2.0 practices that sustain multiple communities and foster engagement with knowledge in new ways. We use an interpretivist approach by drawing on experiential knowledge of the Masters programme in Networked Collaborative Learning and the decision making process of designing the virtual graduate schools. At this early stage, we have limited empirical data related to the student experience of networked learning in current and earlier projects. Our findings indicate that the use of two different theoretical frameworks provided an essential tool in illuminating, situating and informing the process of designing networked learning that involves supporting multiple and diverse communities of practice in institutional settings. These theoretical frameworks have also helped us to analyze our existing projects as case studies and to problematize and begin to understand the challenges we face in facilitating the participation of research students in networked learning communities of practice and the barriers to that participation. We have also found that this process of theorizing has given us a way of reconceptualizing communities of practice within research settings that have the potential to lead to new ideas of networked learning.

designing + (dis)assembling disputes: an ethnography of disputes & lawyers in the construction industry

The UK construction industry is notorious for the sheer amount of disputes which are likely to arise on each building and engineering project. Despite numerous creative attempts at “dispute avoidance” and “dispute resolution”, this industry is still plagued with these costly disputes. Whilst both academic literature and professional practices have investigated the causes of disputes and the mechanisms for avoidance/resolution of these disputes, neither has studied in any detail the nature of the construction disputes and why they develop as they do once a construction lawyer is engaged. Accordingly, this research explores the question of what influences the outcome of a construction dispute and to what extent do construction lawyers control or direct this outcome? The research approach was ethnographic. Fieldwork took place at a leading construction law firm in London over 18 months. The primary focus was participant observation in all of the firm’s activities. In addition, a database was compiled from the firm’s files and archives, thus providing information for quantitative analysis. The basis of the theoretical framework, and indeed the research method, was the Actor‐Network Theory (ANT). As such, this research viewed a dispute as a set of associations – an entity which takes form and acquires its attributes as a result of its relations with other entities. This viewpoint is aligned with relational contract theories, which in turn provides a unified platform for exploring the disputes. The research investigated the entities and events which appeared to influence the dispute’s identity, shape and outcome. With regard to a dispute’s trajectory, the research took as its starting point that a dispute follows the transformation of “naming, blaming, claiming…”, as identified by Felstiner, Abel and Sarat in 1980. The research found that construction disputes generally materialise and develop prior to any one of the parties approaching a lawyer. Once the lawyer is engaged, we see the reverse of the trajectory “naming, blaming, claiming…” this being: “claiming, blaming, naming…” The lawyers’ role is to identify or name (or rename) the dispute in the best possible light for their client in order to achieve the desired outcome – the development of which is akin to the design process. The transformation of a dispute and the reverse trajectory is by no means linear, but rather, iterative and spatial as it requires alliances, dependencies and contingencies to assemble and take the shape it does. The research concludes that construction disputes are rarely ever completely “resolved” as such. Whilst an independent third party may hand down a judgment, or the parties may reach a settlement agreement, this state is only temporal. Some construction disputes dissipate whist others reach a state of hibernation for a period of time only to pick up momentum and energy some years later. Accordingly, this research suggests that the concept of “dispute resolution” does not exist in the UK construction industry. The ultimate goal should be for parties to reach this ultimate and perpetual state of equilibrium as quickly and as cost effectively as possible: “dispute dissolution”, the slowing down of the dispute’s momentum. Rather than focusing on the design and assemblage of the dispute, the lawyers’ role therein is, or should be, to assist with the “disassembling” of the dispute.

Learning Environments in Design Studio Culture

The paper reports on a study of design studio culture from a student perspective. Learning in design studio culture has been theorised variously as a signature pedagogy emulating professional practice models, as a community of practice and as a form of problem-based learning, all largely based on the study of teaching events in studio. The focus of this research has extended beyond formally recognized activities to encompass the student’s experience of their social and community networks, working places and study set-ups, to examine how these have contributed to studio culture and how there have been supported by studio teaching. Semi-structured interviews with final year undergraduate students of architecture formed the basis of the study using an interpretivist approach informed by Actor-network theory, with studio culture featured as the focal actor, enrolling students and engaging with other actors, together constituting an actor-network of studio culture. The other actors included social community patterns and activities; the numerous working spaces (including but not limited to the studio space itself); the equipment, tools of trade and material pre-requisites for working; the portfolio enrolling the other actors to produce work for it; and the various formal and informal events associated with the course itself. Studio culture is a highly charged social arena: The question is how, and in particular, which aspects of it support learning? Theoretical models of situated learning and communities of practice models have informed the analysis, with Bourdieu’s theory of practice, and his interrelated concepts of habitus, field and capital providing a means of relating individually acquired habits and modes of working to social contexts. Bourdieu’s model of habitus involves the externalisation through the social realm of habits and knowledge previously internalised. It is therefore a useful model for considering whole individual learning activities; shared repertoires and practices located in the social realm. The social milieu of the studio provides a scene for the exercise and display of ‘practicing’ and the accumulation of a form of ‘practicing-capital’. This capital is a property of the social milieu rather than the space, so working or practicing in the company of others (in space and through social media) becomes a more valued aspect of studio than space or facilities alone. This practicing-capital involves the acquisition of a habitus of studio culture, with the transformation of physical practices or habits into social dispositions, acquiring social capital (driving the social milieu) and cultural capital (practicing-knowledge) in the process. The research drew on students’ experiences, and their practicing ‘getting a feel for the game’ by exploring the limits or boundaries of the field of studio culture. The research demonstrated that a notional studio community was in effect a social context for supporting learning; a range of settings to explore and test out newly internalised knowledge, demonstrate or display ideas, modes of thinking and practicing. The study presents a nuanced interpretation of how students relate to a studio culture that involves a notional community, and a developing habitus within a field of practicing that extends beyond teaching scenarios.

Applying complexity science to air traffic management

Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

On the multi-dimensionality and sampling of air transport networks

Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.

Asynchronous distributed parallelization of mobile network optimization algorithms

It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.