Design For All @ eInclusion: Best Practice In Education And Training.

Whitney, Gill and Keith, Suzette and Wilson, Judy (2009) Design For All @ eInclusion: Best Practice In Education And Training. In: Assistive technology from adapted equipment to inclusive environments. Emiliani, Pier Luigi and Burzagli, Laura and Como, Andrea and Gabbanini, Francesco and Salminen, Anna-Liisa, eds. Assistive technology research series, 25 . IOS Press, Amsterdam, Netherlands, pp. 837-841. ISBN 9781607500421

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Abstract

The Information Society is bringing about radical changes in the way we communicate and share information, and in the services that we use, for example: fixed and mobile systems, the internet, digital tv and the next generation of ambient intelligent systems. Digital inclusion policies are drawing attention to the ‘missing 30%’ who are currently excluded and the need to ensure the rights of all citizens to participate in and benefit from these new opportunities. This missing 30% embraces social, economic and political disadvantage as well as issues of ageing and disability. The established principles and practices of Design for All offers an opportunity to ensure that designers and developers working in ICT related fields are able to respond to the challenge of creating new systems, services and technologies that meet these broad demands of digital inclusion. As yet there are few teaching programmes within ICT related education that offer the core topics of Design for All in ICT, as either a named module or integrated within other modules. However, our recent survey was able to identify a number of instances of small elements, seminars and single modules. These examples have contributed to the development of curriculum guidelines which aim to stimulate the creation of new specialist programmes – both at Bachelor level and Masters level in order to encourage full integration within current mainstream ICT education and training.

Item Type: Book Section
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 4457
Useful Links:
Depositing User: Mrs Sue Black
Date Deposited: 09 Mar 2010 10:36
Last Modified: 06 Oct 2015 11:00
URI: http://eprints.mdx.ac.uk/id/eprint/4457

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