953 resultados para cloud learning

em Queensland University of Technology - ePrints Archive


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In semisupervised learning (SSL), a predictive model is learn from a collection of labeled data and a typically much larger collection of unlabeled data. These paper presented a framework called multi-view point cloud regularization (MVPCR), which unifies and generalizes several semisupervised kernel methods that are based on data-dependent regularization in reproducing kernel Hilbert spaces (RKHSs). Special cases of MVPCR include coregularized least squares (CoRLS), manifold regularization (MR), and graph-based SSL. An accompanying theorem shows how to reduce any MVPCR problem to standard supervised learning with a new multi-view kernel.

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A patient-centric DRM approach is proposed for protecting privacy of health records stored in a cloud storage based on the patient's preferences and without the need to trust the service provider. Contrary to the current server-side access control solutions, this approach protects the privacy of records from the service provider, and also controls the usage of data after it is released to an authorized user.

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This paper reports an innovative and systemic approach to implementing ICT intervention to support enhancement of teaching and learning of STEM subjects in developing countries. The need for adopting ICT was 2 fold: a lack of availability of qualified STEM secondary teachers and a lack of quality teaching and learning resources to assist teachers and students. ICT was seen as being able to impact on both issues. The intervention involved developing sustainable network design including equipment choices, providing high quality e-learning resources and human resource development including teacher training. The intervention has gradually been accepted by teachers, students, and parents and institutionalized as a key feature of the secondary STEM education in the case study country.

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First year medical laboratory science students (up to 120) undertake a group e-poster project, based in a blended learning model Google Drive, encompassing Google’s cloud computing software, provides a readily accessible, transparent online space for students to collaborate with each other and realise tangible outcomes from their learning The Cube provides an inspiring digital learning display space for student ‘conference style’ presentations

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This article draws on the design and implementation of three mobile learning projects introduced by Flanagan in 2011, 2012 and 2014 engaging a total of 206 participants. The latest of these projects is highlighted in this article. Two other projects provide additional examples of innovative strategies to engage mobile and cloud systems describing how electronic and mobile technology can help facilitate teaching and learning, assessment for learning and assessment as learning, and support communities of practice. The second section explains the theoretical premise supporting the implementation of technology and promulgates a hermeneutic phenomenological approach. The third section discusses mobility, both in terms of the exploration of wearable technology in the prototypes developed as a result of the projects, and the affordances of mobility within pedagogy. Finally the quantitative and qualitative methods in place to evaluate m-learning are explained.