Deep learning design for sustainable innovation within shifting learning landscapes

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Abstract

This paper describes a new approach to designing Technology Enhanced Learning (TEL) in the contemporary, or Web 2.0, landscape and beyond. This embraces the new possibilities that emerging technologies provide for learning, and the pace of change in the development and application of these technologies. In addressing this challenge we outline the framework of Deep Learning Design (DLD) and summarise how it has been developed from, and mapped to, four different TEL initiatives. We argue that this adoption of DLD has led to relatively large-scale and sustainable innovations. It also outlines clear directions for near-future emphases in TEL design and related methodology. © 2010 Springer-Verlag Berlin Heidelberg.

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Ravenscroft, A., Boyle, T., Cook, J., & Schmidt, A. (2010). Deep learning design for sustainable innovation within shifting learning landscapes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6383 LNCS, pp. 578–583). https://doi.org/10.1007/978-3-642-16020-2_57

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