The use of digital technologies is now widespread and increasing, but is not always optimized for effective learning. Teachers in higher education have little time or support to work on innovation and improvement of their teaching, which often means they simply replicate their current practice in a digital medium. This paper makes the case for a learning design support environment to support and scaffold teachers' engagement with and development of technology‐enhanced learning, based on user requirements and on pedagogic theory. To be able to adopt, adapt, and experiment with learning designs, teachers need a theory‐informed way of representing the critical characteristics of good pedagogy as they discover how to optimize learning technologies. This paper explains the design approach of the Learning Design Support Environment project, and how it aims to support teachers in achieving this goal.
Traditional approaches to learning have often focused upon knowledge transfer strategies that have centred on textually-based engagements with learners, and dialogic methods of interaction with tutors. The use of virtual worlds, with text-based, voice-based and a feeling of 'presence' naturally is allowing for more complex social interactions and designed learning experiences and role plays, as well as encouraging learner empowerment through increased interactivity. To unpick these complex social interactions and more interactive designed experiences, this paper considers the use of virtual worlds in relation to structured learning activities for college and lifelong learners. This consideration necessarily has implications upon learning theories adopted and practices taken up, with real implications for tutors and learners alike. Alongside this is the notion of learning as an ongoing set of processes mediated via social interactions and experiential learning circumstances within designed virtual and hybrid spaces. This implies the need for new methodologies for evaluating the efficacy, benefits and challenges of learning in these new ways. Towards this aim, this paper proposes an evaluation methodology for supporting the development of specified learning activities in virtual worlds, based upon inductive methods and augmented by the four-dimensional framework reported in a previous study.The study undertaken aimed to test the efficacy of the proposed evaluation methodology and framework, and to evaluate the broader uses of a virtual world for supporting lifelong learners specifically in their educational choices and career decisions. The paper presents the findings of the study and considers that virtual worlds are reorganising significantly how we relate to the
This article focuses on gradient-based backpropagation algorithms that use either a common adaptive learning rate for all weights or an individual adaptive learning rate for each weight and apply the Goldstein/Armijo line search. The learning-rate adaptation is based on descent techniques and estimates of the local Lipschitz constant that are obtained without additional error function and gradient evaluations. The proposed algorithms improve the backpropagation training in terms of both convergence rate and convergence characteristics, such as stable learning and robustness to oscillations. Simulations are conducted to compare and evaluate the convergence behavior of these gradient-based training algorithms with several popular training methods.
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