8,538 research outputs found

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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    Virtual learning environments – help or hindrance for the ‘disengaged’ student?

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    The introduction of virtual learning environments (VLEs) has been regarded by some as a panacea for many of the problems in today’s mass numbers modular higher education system. This paper demonstrates that VLEs can help or hinder student engagement and performance, and that they should be adapted to the different types of learner. A project is described that aimed to investigate whether the introduction of a VLE can assist ‘disengaged’ students, drawing on click count tracking data and student performance. The project took place in the context of two very large undergraduate modules (850 and 567 students) in a Business School of a new university in the UK. In an adaptation of a model of learner engagement in Web-enhanced environments, four distinct learner types have emerged: model, traditionalist, geek and disengaged. There was evidence that use of the VLE exacerbated, rather than moderated, the differences between these learner types

    Innovative learning in action (ILIA) issue five: Learning technologies in the curriculum

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    Consideration of the papers and snapshots in this edition of Innovative Learning in Action, focused on learning technology, will provide the reader with insights into a range of excellent and innovative approaches to the application of learning technologies to enhance learning both in the classroom and at a distance. It also provides us with examples of how learning technologies can both stimulate and support partnership with staff and students and collaborative learning and working. This edition is particularly timely given the aim of the University’s 2005-2008 Learning Technologies Implementation Plan (LTIP), which is to enhance the quality of, and access to, learning, teaching and assessment by supporting and developing the curriculum through the appropriate and effective use of learning technologies. The LTIP is designed to help us to reach a situation where the effective use of appropriate learning technologies becomes part of our normal teaching, research and enterprise activities, and enhances access to our programmes by all our students whether they are learning on campus, at a distance, or in the workplace. The emphasis at the University of Salford has consistently been on the identification and creative application of the appropriate blends of ICT and traditional methods, shaped by pedagogical, rather than technological drivers, and acknowledging and reflecting different academic contexts and professional and vocational requirements. We have some excellent examples of how this has been achieved here, ILIA once again providing us with an opportunity to reflect on practice and student learning, to share experience and hopefully to identify future areas for collaboration in a key area of curriculum development

    MILO: Models of innovation in learning online at Key Stage 3 and 14-19: Final report appendices

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    This document contains the appendices to the main report, which presents case studies, which reflect a wide range of models of online learning, each of which has been developed for specific reasons, largely in relation to visions of how technology can transform learning, but also to solve practical problems such as re-engaging disaffected learners and coping with rising pupil numbers

    A Multi Hidden Recurrent Neural Network with a Modified Grey Wolf Optimizer

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    Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are needed to imitate this mechanism. A hybrid system (a modified Recurrent Neural Network with an adapted Grey Wolf Optimizer) is used to forecast students' outcomes. This proposed system would improve instruction by the faculty and enhance the students' learning experiences. The results show that a modified recurrent neural network with an adapted Grey Wolf Optimizer has the best accuracy when compared with other models.Comment: 34 pages, published in PLoS ON

    Every student counts: promoting numeracy and enhancing employability

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    This three-year project investigated factors that influence the development of undergraduates’ numeracy skills, with a view to identifying ways to improve them and thereby enhance student employability. Its aims and objectives were to ascertain: the generic numeracy skills in which employers expect their graduate recruits to be competent and the extent to which employers are using numeracy tests as part of graduate recruitment processes; the numeracy skills developed within a diversity of academic disciplines; the prevalence of factors that influence undergraduates’ development of their numeracy skills; how the development of numeracy skills might be better supported within undergraduate curricula; and the extra-curricular support necessary to enhance undergraduates’ numeracy skills
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