Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices

Knox, Jeremy (Edited by)/ Wang, Yuchen (Edited by)/ Gallagher, Michael (Edited by)

ISBN 10: 9811381607 ISBN 13: 9789811381607

Verlag: Springer, 2019

Sprache: Englisch

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222 pages. 9.25x6.10x0.79 inches. In Stock.

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Bibliografische Details

Titel

Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices

Verlag

Springer

Erscheinungsjahr

2019

Sprache

Englisch

ISBN-10

9811381607

ISBN-13

9789811381607

Einband

Hardcover

Zustand

Brand New

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Inhaltsangabe

This book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologies and the necessity of developing inclusive teaching and learning.

To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and 'smart' software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to 'personalise' learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by 'big data'.

�ber die Autorin bzw. den Autor

Jeremy Knox is a Lecturer in Digital Education at the University of Edinburgh, UK, and Co-Director of the Centre for Research in Digital Education. His research interests include critical posthumanism, open education, and data-intensive technologies in teaching and learning. His published work includes critical perspectives on open educational resources, massive open online courses, and learning analytics.
Yuchen Wang is a Research Associate & Tutor at the Institute for Education, Community and Society at the University of Edinburgh, UK. Her research focuses on inclusive education development, and in particular, the implications of student voice for transforming practice.
Michael Gallagher is a Research Associate at the Centre for Research in Digital Education at the University of Edinburgh, UK, and Director and Co-Founder of a digital education and ICT4D consultancy. His research interests include teacher training, digital education, open learning, mobile learning, critical theory, cultural heritage, and ethical design.

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