Increasing information feed in the process of structural steel design

Research initiatives throughout history have shown how a designer typically makes associations and references to a vast amount of knowledge based on experiences to make decisions. With the increasing usage of information systems in our everyday lives, one might imagine an information system that provides designers access to the ‘architectural memories’ of other architectural designers during the design process, in addition to their own physical architectural memory. In this paper, we discuss how the increased adoption of semantic web technologies might advance this idea. We investigate to what extent information can be described with these technologies in the context of structural steel design. This investigation indicates significant possibilities regarding information reuse in the process of structural steel design and, by extent, in other design contexts as well. However, important obstacles and question remarks can still be outlined as well

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Designing for change: mash-up personal learning environments

Institutions for formal education and most work places are equipped today with at least some kind of tools that bring together people and content artefacts in learning activities to support them in constructing and processing information and knowledge. For almost half a century, science and practice have been discussing models on how to bring personalisation through digital means to these environments. Learning environments and their construction as well as maintenance makes up the most crucial part of the learning process and the desired learning outcomes and theories should take this into account. Instruction itself as the predominant paradigm has to step down. The learning environment is an (if not 'the�) important outcome of a learning process, not just a stage to perform a 'learning play'. For these good reasons, we therefore consider instructional design theories to be flawed. In this article we first clarify key concepts and assumptions for personalised learning environments. Afterwards, we summarise our critique on the contemporary models for personalised adaptive learning. Subsequently, we propose our alternative, i.e. the concept of a mash-up personal learning environment that provides adaptation mechanisms for learning environment construction and maintenance. The web application mash-up solution allows learners to reuse existing (web-based) tools plus services. Our alternative, LISL is a design language model for creating, managing, maintaining, and learning about learning environment design; it is complemented by a proof of concept, the MUPPLE platform. We demonstrate this approach with a prototypical implementation and a – we think – comprehensible example. Finally, we round up the article with a discussion on possible extensions of this new model and open problems

Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our technologies is still barely visible. McLuhan’s predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The combination of this expertise, and the time and space afforded the consortium by the IRC structure, suggested the opportunity for a concerted effort to develop an approach to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to the knowledge management services AKT tries to provide. As a medium for the semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing ontologies to create a third). Ontology mapping, and the elimination of conflicts of reference, will be important tasks. All of these issues are discussed along with our proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which semantic hygiene prevails interesting enough to reason in? These and many other questions need to be addressed if we are to provide effective knowledge technologies for our content on the web

Studie: A Domain Ontology Based Solution for Knowledge Discovery in Learning and Assessment

Continuous learning is a necessity in today’s organizations. With the ongoing technization, technology enhanced solutions are now supporting learners, especially in situations of non-formal and blended learning. Furthermore, where workers are forced to constantly adapt to new roles and skill-sets, adaptive support solutions are mandatory. Yet adaptive and flexible solutions for learning in and across domains in the scope and need of organizations are still a rare breed. The flexible and adaptive STUDIO system for adaptive learning and self-assessment demonstrates how a well-defined use of domain knowledge helps to discover the knowledge of the learner. This article will introduce the STUDIO system and discuss based on STUDIO how user models, cognitive traits and adaptive systems can act as enablers for further flexible solutions

Using the Internet to improve university education

Up to this point, university education has largely remained unaffected by the developments of novel approaches to web-based learning. The paper presents a principled approach to the design of problem-oriented, web-based learning at the university level. The principles include providing authentic contexts with multimedia, supporting collaborative knowledge construction, making thinking visible with dynamic visualisation, quick access to content resources via information and communication technologies, and flexible support by tele-tutoring. These principles are used in the MUNICS learning environment, which is designed to support students of computer science to apply their factual knowledge from the lectures to complex real-world problems. For example, students may model the knowledge management in an educational organisation with a graphical simulation tool. Some more general findings from a formative evaluation study with the MUNICS prototype are reported and discussed. For example, the students' ignorance of the additional content resources is discussed in the light of the well-known finding of insufficient use of help systems in software applications

The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research

Adaptive intelligent personalised learning (AIPL) environment

As individuals the ideal learning scenario would be a learning environment tailored just for how we like to learn, personalised to our requirements. This has previously been almost inconceivable given the complexities of learning, the constraints within the environments in which we teach, and the need for global repositories of knowledge to facilitate this process. Whilst it is still not necessarily achievable in its full sense this research project represents a path towards this ideal.In this thesis, findings from research into the development of a model (the Adaptive Intelligent Personalised Learning (AIPL)), the creation of a prototype implementation of a system designed around this model (the AIPL environment) and the construction of a suite of intelligent algorithms (Personalised Adaptive Filtering System (PAFS)) for personalised learning are presented and evaluated. A mixed methods approach is used in the evaluation of the AIPL environment. The AIPL model is built on the premise of an ideal system being one which does not just consider the individual but also considers groupings of likeminded individuals and their power to influence learner choice. The results show that: (1) There is a positive correlation for using group-learning-paradigms. (2) Using personalisation as a learning aid can help to facilitate individual learning and encourage learning on-line. (3) Using learning styles as a way of identifying and categorising the individuals can improve their on-line learning experience. (4) Using Adaptive Information Retrieval techniques linked to group-learning-paradigms can reduce and improve the problem of mis-matching. A number of approaches for further work to extend and expand upon the work presented are highlighted at the end of the Thesis

Using the Internet to improve university education: Problem-oriented web-based learning and the MUNICS environment

Up to this point, university education has largely remained unaffected by the developments of novel approaches to web-based learning. The paper presents a principled approach to the design of problem-oriented, web-based learning at the university level. The principles include providing authentic contexts with multimedia, supporting collaborative knowledge construction, making thinking visible with dynamic visualisation, quick access to content resources via Information and Communication Technologies (ICT), and flexible support by tele-tutoring. These principles are used in the Munich Net-based Learning In Computer Science (MUNICS) learning environment, which is designed to support students of computer science to apply their factual knowledge from the lectures to complex real-world problems. For example, students can model the knowledge management in an educational organisation with a graphical simulation tool. Some more general findings from a formative evaluation study with the MUNICS prototype are reported and discussed. E.g., the students' ignorance of the additional content resources is discussed in the light of the well-known finding of insufficient use of help systems in software applicationsBislang wurden neuere Ansätze zum web-basierten Lernen in nur geringem Maße zur Verbesserung des Universitätsstudiums genutzt. Es werden theoretisch begründete Prinzipien für die Gestaltung problemorientierter, web-basierter Lernumgebungen an der Universität formuliert. Zu diesen Prinzipien gehören die Nutzung von Multimedia-Technologien für die Realisierung authentischer Problemkontexte, die Unterstützung der gemeinsamen Wissenskonstruktion, die dynamische Visualisierung, der schnelle Zugang zu weiterführenden Wissensressourcen mit Hilfe von Informations- und Kommunikationstechnologien sowie die flexible Unterstützung durch Teletutoring. Diese Prinzipien wurden bei der Gestaltung der MUNICS Lernumgebung umgesetzt. MUNICS soll Studierende der Informatik bei der Wissensanwendung im Kontext komplexer praktischer Problemstellungen unterstützen. So können die Studierenden u.a. das Wissensmanagement in einer Bildungsorganisation mit Hilfe eines graphischen Simulationswerkzeugs modellieren. Es werden Ergebnisse einer formativen Evaluationsstudie berichtet und diskutiert. Beispielsweise wird die in der Studie festgestellte Ignoranz der Studierenden gegenüber den weiterführenden Wissensressourcen vor dem Hintergrund des häufig berichteten Befunds der unzureichenden Nutzung von Hilfesystemen beleuchte