The evolutionary design of a Knowledge Network to support knowledge management and sharing for lifelong learning

Knowledge Management (KM) and knowledge sharing are important factors that support lifelong learning, and enable people to continue developing throughout their careers. The concept of a Community of Practice (Wenger, 2000) is attractive in drawing together people whose work shares similar aspects, and consideration is given here to how technology can be used to develop and support such a community. In this paper, concepts from the Community of Practice literature are used to consider the development of a software environment for people working as a community in the area of lifelong learning. The intention was to design the system in an evolutionary way, using a minimal set of essential elements which would be elaborated according to user feedback. Three key design questions are considered: Who can contribute resources to such a system? What happens to existing practices? How is the community engaged? We conclude that, in lifelong learning, knowledge management supported by a software environment offers a good way to bring together communities, resources and experience, but to achieve these benefits, great care needs to be exerted in introducing the system and maintaining existing work practices

Smart labs and social practice: social tools for pervasive laboratory workspaces: a position paper

The emergence of pervasive and ubiquitous computing stimulates a view of future work environments where sharing of information, data and knowledge is easy and commonplace, particularly in highly interactive settings. Much of the work in this area focuses on tool development to support activities such as data collection, data recording and sharing, and so on. We are interested in this kind of technical development, which is both challenging and essential for science communities. But we are also interested in a broader interpretation of knowledge sharing and the human/social side of tools we develop to support this. We are keen to know more about how groups of different kinds of scientists can make their work understandable and shareable with each other in a multidisciplinary setting. This is a complex task because boundaries and barriers can emerge between disciplines engendered by differences in discourses and practices, which may not easily translate into other discipline areas. In the worst case, there may be some hostility between disciplines, or at least doubt and scepticism. Nevertheless, sharing approaches to research, research expertise, data and methods across disciplines can be a very fruitful exercise, and encouragement to engage in this activity is particularly pertinent in the digital era. Issues of privacy and security are also key aspects – knowing when and how to release data or information to other groups is crucial to providing a safe environment for people to work, and there are several sensitivities to be explored here. In this paper we describe an evolving situation that captures many of these issues, which we aim to track longitudinally

Collaborative learning: a connected community approach

Collaborative Learning in group settings currently occurs across a substantial portion of the UK Higher Education curriculum. This style of learning has many roots including: Enterprise in Higher Education, Action Learning and Action Research, Problem Based Learning, and Practice Based Learning. As such our focus on Collaborative Learning development can be viewed as an evolutionary. This collaborative and active group learning provides the foundation for what can be collectively called connectivist ‘Learning Communities’. In this setting a primary feature of a ‘Learning Community’ is one that carries a responsibility to promote one another’s learning. This paper will outline a developmental collaborative learning approach and describe a supporting software environment, known as the Salford Personal Development Environment (SPDE), that has been developed and implemented to assist in delivering collaborative learning for post graduate and other provision. This is done against a background of much research evidence that group based activity can enhance learning. These findings cover many approaches to group based learning and over a significant period of time. This paper reports on work-in-progress and the features of the environment that are designed to help promote individual and group or community learning that have been influenced by the broad base of research findings in this area

The evolution of pedagogic models for work-based learning within a virtual university

The process of designing a pedagogic model for work-based learning within a virtual university is not a simple matter of using ‘off the shelf’ good practice. Instead, it can be characterised as an evolutionary process that reflects the backgrounds, skills and experiences of the project partners. Within the context of a large-scale project that was building a virtual university for work-based learners, an ambitious goal was set: to base the development of learning materials on a pedagogic model that would be adopted across the project. However, the reality proved to be far more complex than simply putting together an appropriate model from existing research evidence. Instead, the project progressed through a series of redevelopments, each of which was pre-empted by the involvement of a different team from within the project consortium. The pedagogic models that evolved as part of the project will be outlined, and the reasons for rejecting each will be given. They moved from a simple model, relying on core computer-based materials (assessed by multiple choice questions with optional work-based learning), to a more sophisticated model that integrated different forms of learning. The challenges that were addressed included making learning flexible and suitable for work-based learning, the coherence of accreditation pathways, the appropriate use of the opportunities provided by online learning and the learning curves and training needs of the different project teams. Although some of these issues were project-specific (being influenced by the needs of the learners, the aims of the project and the partners involved), the evolutionary process described in this case study illustrates that there can be a steep learning curve for the different collaborating groups within the project team. Whilst this example focuses on work-based learning, the process and the lessons may equally be applicable to a range of learning scenarios

Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems

This paper was motivated by the problem of how to make robots fuse and transfer their experience so that they can effectively use prior knowledge and quickly adapt to new environments. To address the problem, we present a learning architecture for navigation in cloud robotic systems: Lifelong Federated Reinforcement Learning (LFRL). In the work, We propose a knowledge fusion algorithm for upgrading a shared model deployed on the cloud. Then, effective transfer learning methods in LFRL are introduced. LFRL is consistent with human cognitive science and fits well in cloud robotic systems. Experiments show that LFRL greatly improves the efficiency of reinforcement learning for robot navigation. The cloud robotic system deployment also shows that LFRL is capable of fusing prior knowledge. In addition, we release a cloud robotic navigation-learning website based on LFRL

Models of technology and change in higher education: an international comparative survey on the current and future use of ICT in higher education

The aim of this study is to investigate which scenarios are emerging with respect to the use of ICT in higher education and how future developments can be predicted and strategic choices can be based on that. It seeks to answer the following questions:\ud What strategic responses do institutions make with respect to the use of ICT; Which external conditions and developments influence these choices; Which external and internal conditions and measures are taken in order to achievestrategic targets; What are the implications for technology use, teaching and learning processes and staff? \ud The study applies an international comparative methodology and is carried out in the Netherlands, Germany, Norway, the United Kingdom, Australia, Finland and the USA. Data were collected through Web-based questionnaires tailored to three different response groups: decision makers, support staff and instructors. In total 693 persons responded to the questionnaire. This implies that between 20 and 50 percent of the institutions in the various countries responded (institutional data were also gathered), with the exception of the USA where the response was much lower