695 resultados para mobile learning technologies
Resumo:
Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.
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A number of Intelligent Mobile Robots have been developed at the University of Reading. They are completely autonomous in that no umbilical cord attaches to them to extra power supplies or computer station: further, they are not radio controlled. In this paper, the robots are discussed, in their various forms, and the individual behaviours and characteristics which appear are considered.
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The increasing importance of employability in Higher Education curricula and the prevalence of using mobile devices for fieldbased learning prompted an investigation into student awareness of the relationship between the use of mobile apps for learning and the development of graduate attributes (GAs) (and the link to employability). The results from post-fieldwork focus groups from four field courses indicated that students could make clear links between the use of a variety of mobile apps and graduate attribute development. The study suggests a number of mobile apps can align simultaneously with more than one graduate attribute. Furthermore, prior experience and the context of use can influence students’ perceptions of an app and its link with different GAs.
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This is a European Commission Leonardo da Vinci Reference Material project on the impact of new technology on distance learning students. It is known that all the Ministries of Education of the 27 European Union countries pay millions of Euros annually in the provision of educational technology for their schools, colleges and universities. A review of the literature of the impact of technology, however, showed that the research in this field was unacceptably fragile. What research there was focused on the impact of technology on children in American schools. The project set out, therefore, to measure the impact of technology on adult education, lifelong learning and distance education, with a particular focus on adult distance learning.
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In the last decade, multi-sensor data fusion has become a broadly demanded discipline to achieve advanced solutions that can be applied in many real world situations, either civil or military. In Defence,accurate detection of all target objects is fundamental to maintaining situational awareness, to locating threats in the battlefield and to identifying and protecting strategically own forces. Civil applications, such as traffic monitoring, have similar requirements in terms of object detection and reliable identification of incidents in order to ensure safety of road users. Thanks to the appropriate data fusion technique, we can give these systems the power to exploit automatically all relevant information from multiple sources to face for instance mission needs or assess daily supervision operations. This paper focuses on its application to active vehicle monitoring in a particular area of high density traffic, and how it is redirecting the research activities being carried out in the computer vision, signal processing and machine learning fields for improving the effectiveness of detection and tracking in ground surveillance scenarios in general. Specifically, our system proposes fusion of data at a feature level which is extracted from a video camera and a laser scanner. In addition, a stochastic-based tracking which introduces some particle filters into the model to deal with uncertainty due to occlusions and improve the previous detection output is presented in this paper. It has been shown that this computer vision tracker contributes to detect objects even under poor visual information. Finally, in the same way that humans are able to analyze both temporal and spatial relations among items in the scene to associate them a meaning, once the targets objects have been correctly detected and tracked, it is desired that machines can provide a trustworthy description of what is happening in the scene under surveillance. Accomplishing so ambitious task requires a machine learning-based hierarchic architecture able to extract and analyse behaviours at different abstraction levels. A real experimental testbed has been implemented for the evaluation of the proposed modular system. Such scenario is a closed circuit where real traffic situations can be simulated. First results have shown the strength of the proposed system.
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Though technology holds significant promise for enhanced teaching and learning it is unlikely to meet this promise without a principled approach to course design. There is burgeoning discourse about the use of technological tools and models in higher education, but much of the discussion is fixed upon distance learning or technology based courses. This paper will develop and propose a balanced model for effective teaching and learning for “on campus” higher education, with particular emphasis on the opportunities for revitalisation available through the judicious utilisation of new technologies. It will explore the opportunities available for the creation of more authentic learning environments through the principled design. Finally it will demonstrate with a case study how these have come together enabling the creation of an effective and authentic learning environment for one pre-service teacher education course at the University of Queensland.
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While mobile devices offer many innovative possibilities to help increase the standard of living for individuals with disabilities and other special needs, the process of developing assistive technology, such that it will be effective across a group of individuals with a particular disability, can be extremely challenging. This chapter discusses key issues and trends related to designing and evaluating mobile assistive technology for individuals with disabilities. Following an overview of general design process issues, we argue (based on current research trends) that individuals with disabilities and domain experts be involved throughout the development process. While this, in itself, presents its own set of challenges, many strategies have successfully been used to overcome the difficulties and maximize the contributions of users and experts alike. Guidelines based on these strategies are discussed and are illustrated with real examples from one of our active research projects.