The LAB@FUTURE Project - Moving Towards the Future of E-Learning

This paper presents Lab@Future, an advanced e-learning platform that uses novel Information and Communication Technologies to support and expand laboratory teaching practices. For this purpose, Lab@Future uses real and computer-generated objects that are interfaced using mechatronic systems, augmented reality, mobile technologies and 3D multi user environments. The main aim is to develop and demonstrate technological support for practical experiments in the following focused subjects namely: Fluid Dynamics - Science subject in Germany, Geometry - Mathematics subject in Austria, History and Environmental Awareness – Arts and Humanities subjects in Greece and Slovenia. In order to pedagogically enhance the design and functional aspects of this e-learning technology, we are investigating the dialogical operationalisation of learning theories so as to leverage our understanding of teaching and learning practices in the targeted context of deployment

Addressing the learners' needs for specific and constructive feedback

This paper discusses an on-going project which proposes to make feedback to students more personal, explicit and more useful as a method of further engaging students. It addresses an issue that has recently been identified by the researchers where students on an Engineering programme were not recognising the presence of feedback on their assessed work. Feedback is central to the process of learning. However it has been widely accepted, through tools such as the UK National Student Survey, that students are still relatively dissatisfied with the feedback they have received. There is therefore a need to ensure that feedback given to students is specific and constructive in terms of helping them move their own learning forward. A pilot is being carried out with two Engineering classes, offering students the option to request specific feedback on their class tests. The students are asked to identify the areas of their work they require feedback on through the completion of a ‘feedback request label’. Staff can then respond to the feedback requests and issue students with personal and relevant feedback. Initial findings from the project have shown students to have clear expectations regarding the type of feedback they want. Students identified that they expect clear and legible feedback, which draws together feedback comments from throughout their work and provides a summary of how they could move forwards. Findings have also identified some differences in expectations and perceptions of feedback between the Level 3 and Level 4 students involved in the project

“Wave-Packet Reduction” and the quantum character of the actualization of potentia

Werner Heisenberg introduced the notion of quantum potentia in order to accommodate the indeterminism associated with quantum measurement. Potentia captures the capacity of the system to be found to possess a property upon a corresponding sharp measurement in which it is actualized. The specific potentiae of the individual system are represented formally by the complex amplitudes in the measurement bases of the eigenstate in which it is prepared. All predictions for future values of system properties can be made by an experimenter using the probabilities which are the squared moduli of these amplitudes that are the diagonal elements of the density matrix description of the pure ensemble to which the system, so prepared, belongs. Heisenberg considered the change of the ensemble attribution following quantum measurement to be analogous to the classical change in Gibbs’ thermodynamics when measurement of the canonical ensemble enables a microcanonical ensemble description. This analogy, presented by Heisenberg as operating at the epistemic level, is analyzed here. It has led some to claim not only that the change of the state in measurement is classical mechanical, bringing its quantum character into question, but also that Heisenberg held this to be the case. Here, these claims are shown to be incorrect, because the analogy concerns the change of ensemble attribution by the experimenter upon learning the result of the measurement, not the actualization of the potentia responsible for the change of the individual system state which—in Heisenberg’s interpretation of quantum mechanics—is objective in nature and independent of the experimenter’s knowledge

Synchronous Online Philosophy Courses: An Experiment in Progress

There are two main ways to teach a course online: synchronously or asynchronously. In an asynchronous course, students can log on at their convenience and do the course work. In a synchronous course, there is a requirement that all students be online at specific times, to allow for a shared course environment. In this article, the author discusses the strengths and weaknesses of synchronous online learning for the teaching of undergraduate philosophy courses. The author discusses specific strategies and technologies he uses in the teaching of online philosophy courses. In particular, the author discusses how he uses videoconferencing to create a classroom-like environment in an online class

Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

MODES OF INNOVATION & UNCERTAINTIES IN THE CAPITAL GOODS INDUSTRY

Product innovation is a subtle process, frequently leading to shifts in the competitiveness of firms. Developing products in an environment undergoing technological change is given to frequent failure, even in well-established and sophisticated organizations. In order to tackle competitiveness and to deal with innovation uncertainty, firms develop diverse innovation processes. Two modes of innovation are suggested in recent literature: 1) Science, Technology and Innovation (STI) mode, which is based on the production and use of codified scientific and technical knowledge; and 2) Doing, Using and Interacting (DUI) mode, which relies on informal processes of learning and experience-based know-how. In this paper we analyse product innovation at firm level. We perform an exploratory analysis in four leading equipment and machinery producers from the Aveiro region, in Portugal. Doing so, we explore the main features of the capital goods’ industry with implications for innovation, and analyse the dominant uncertainties associated to the innovation process. and modes of innovation. Key findings include the complete absence of DUI mode in the cases studied, and even a low learning characteristic in one company. The paper concludes by considering the implications for firms’ competitiveness and for innovation policy.modes of innovation, uncertainties, R&D, capital goods, SME

Certainty and Uncertainty in Quantum Information Processing

This survey, aimed at information processing researchers, highlights intriguing but lesser known results, corrects misconceptions, and suggests research areas. Themes include: certainty in quantum algorithms; the "fewer worlds" theory of quantum mechanics; quantum learning; probability theory versus quantum mechanics.Comment: Invited paper accompanying invited talk to AAAI Spring Symposium 2007. Comments, corrections, and suggestions would be most welcom