Jeremy Knox
~ Technology, Culture, Education ~

Call for Chapters: Speculative Futures for Artificial Intelligence and Educational Inclusion

Springer Nature – AICFE Future Schools 2030 book series

Speculative Futures for Artificial Intelligence and Educational Inclusion

Call for chapters

We are inviting experts and practitioners from around the world to write chapters for a book that will help to advance our understanding of education. The book is an outcome of the Future School 2030 research project supported by the Advanced Innovation Centre for Future Education, Beijing Normal University. The publisher for the book will be Springer Nature, an international publisher.

This book seeks to bring together the fields of ‘artificial intelligence’ (often known as A.I.) and ‘inclusive education’ in order to speculate on the future of educational practice. Heretofore, there has been little in the way of direct association between research and practice in these domains: A.I. has been predominantly a technical field of research and development, and while intelligent computer systems and software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the idea of inclusion appears lacking. Inclusive education, the agenda of which has been addressed by the recent UN Sustainable Development Goal 4, concerns an education system’s ability to accept and celebrate student diversity (Armstrong et al. 2010). Pedagogically, it is to deliver quality educational provision for all learners, ‘regardless of any perceived difference, disability or other social, emotional, cultural or linguistic difference’ (Florian 2008, p202). While different kinds of technologies have been applied in various ways to support inclusive teaching and learning, the implications of the rapid development of A.I. seems to be much overlooked.

This book is motivated by the question of why this relationship between A.I. intelligence research and inclusive educational practice has not been more substantively formed. This position develops established work that has critiqued the often-simplistic ways that technology has been applied to education (Selwyn 2014), exposing deep-rooted assumptions of ‘solutionism’ in the increasingly powerful tech sector (Watters 2013), highlighting the alignment with neoliberal models of the university, and surfacing underlying conflicts between digital technologies and foundational ideas about the purpose of education (Selwyn & Facer 2013; Hoofd 2017). In a general sense, A.I. is grounded in disciplinary knowledge from computer science and psychology, and this combination tends towards methods that seek generalisations and models from data, and a world view that assumes a ‘normal’ human condition. Both these tendencies may seem at odds with an inclusive education that attempts to foreground and embrace diversity, and question the devaluing of difference in highly standardised and performative education systems (Wang 2016). In addition, the supposed ‘technology revolution’ in education is habitually framed as being driven from the ‘outside’ (DeMillo 2015), and this view has tended to overlook established educational expertise. Of course, these two positions are not completely contradictory, and A.I. systems may be put to work for one kind of ‘inclusion’ agenda, while at the same time underming other perspectives on equity or diversity. Reflecting on the global trends of inclusive education, Singal and Muthukrishna (2014) remind us to ask: ‘inclusion into what and for what purposes’ (p.300).

Moreover, A.I. offers exciting possibilities for education, including intelligent systems that are able to ‘personalise’ learning or adapt to specific contexts. Emerging fields that draw on machine learning techniques, such as learning analytics, offer tangible opportunities to develop A.I. that can support teachers and students to embrace diverse classrooms and varied ways of teaching and learning. As many education institutions appear to be seeking to attract more international students, widen access, increase the diversity of their populations, and to develop ways of scaling their provision, such A.I. systems may become essential parts of educational infrastructure, and key ways of achieving future visions for the education sector.


Contributions to this book may include the following:

Philosophy and Theory of A.I. and Inclusive Education – theoretical work that makes connections between philosophies of education and technology. For example: technological and social determinism and their relationship to educational A.I., focusing on inclusion; links between humanism and A.I. and implications for inclusive education; theories of learning (such as ‘social constructivism’ or ‘behaviourism’) and relationships to A.I. and inclusive education. These might also include historical analyses of the development of education and A.I. technology, or critical accounts of the relationships between the A.I. industry and the market-driven models of education. Work on the politics of education and A.I., and social justice critiques of, would be relevant here too, as would considerations of divides and equality, and global North/South differences. Ethical applications of A.I. and/or usage of data in the inclusive education context (for example, vulnerable learners) would be appropriate here too.

Developing A.I. technologies – empirical contributions that examine and analyse specific A.I. technologies employed in education, and their contribution (or lack of contribution) to inclusive education ideals and practices. For example, accounts of hardware (such as assistive technologies, or robotics) or software (such as digital assistants, personalised or adaptive systems, etc.) designed for classroom use. Analysis here could focus on technical design or interface. This can also include more speculative work, focused on future visions for technology. Scope should also be given here for work that considers A.I. technologies not necessarily designed for inclusion, but nevertheless used for inclusive education agendas.

Student and teacher perspectives – engagement with educational practice: teachers and students working with or experiencing inclusive education issues and challenges, or indeed A.I. support or interventions. This might include interviews with teachers or students, ethnographic accounts of inclusive classrooms with A.I. technologies. Given the emerging and often speculative nature of A.I., particularly that specifically designed for inclusive education, this theme can include speculative accounts that envision educational futures from the perspective of teachers and students.

Speculative futures and creative writing on A.I. education

In the spirit of speculative methods in education (Ross 2017) and ‘design fictions’, we also welcome creative writing pieces that address A.I. and inclusive education. These contributions will be an important part of any book that seeks to speculate and envision possible educational futures, and in so doing, reveal and examine the concerns, challenges, and beliefs that underpin our contemporary relationships with technology. How we foresee and anticipate the future can also have a profound influence on the creative practices and technical developments that eventually build it.



Armstrong, A.C., Armstrong, D, and Spandagou, I. 2010. Inclusive Education: International Policy & Practice. London: Sage

DeMillo, R.A. 2015. Revolution in Higher Education: How a Small Band of Innovators Will Make College Accessible and Affordable. Cambrige: MIT Press.

Florian, L. 2008. Inclusion: special or inclusive education: furture trends. British Journal of Special Education, 35(4), 202-208.

Hall, R. 2016. Technology-enhanced learning and co-operative practice against the neoliberal university. Interactive Learning Environments, 24(5), 1004-1015.

Hoofd, Ingrid M. 2017. Higher Education and Technological Acceleration: The Disintegration of University Teaching and Research. New York: Palgrave Macmillan.

Ross J.  2017.  Speculative method in digital education research. Learning, Media and Technology, 42(2), 214-229.

Selwyn, N., & Facer, K. 2013. The Politics of Education and Technology: Conflicts, Controversies, and Connections. New York: Palgrave Macmillan.

Selwyn, N. 2014. Distrusting Educational Technology: Critical Questions for Changing Times. Oxon: Routledge.

Singal, N. & Muthukrishna, N. (2014) Education, childhood and disability in countries of the South – Re-positioning the debates. Childhood, 21(3): 293-307.

Wang, Y. 2016. Imagining Inclusive Schooling: An Ethnographic Inquiry into Disabled Children’s Learning and Participation in Regular Schools in Shanghai. PhD thesis. Edinburgh: University of Edinburgh.

Watters, A. 2013. Click Here to Save Education: Evgeny Morozov and Ed-Tech Solutionism. Hack Education. Available at:


Important completion dates

Abstract submission – asap

Feedback on abstract – April 30, 2018

Submission of full chapter – September 30, 2018

Feedback from chapter reviewers – November 30, 2018

Submission of revised chapter – January 31, 2019

Submit book manuscript to publisher – February 28, 2019

Expected publication date – May, 2019



Please email a one-page abstract (500 words) to Xuanwei (Ada) Ma at with a copy to Dr Yuchen Wang The due date for the abstract is March 30, 2018.

Full Chapter

Please email your chapter to Xuanwei (Ada) Ma at with a copy to Dr Yuchen Wang The length of the chapter should be between 5,000 and 6,000 words. The due date for the chapter is September 30, 2018.


Chapter Guidelines

Speculative Futures for Artificial Intelligence and Educational Inclusion

Below are some useful guidelines regarding the format and the style of your Chapter.

The following elements should be included in each Chapter:

  • Title
  • Author’s name (or Authors’ names and of Co-Authors if applicable)
  • A short biographies of each contributor (max 200 words each)
  • Abstract (200- 250 words)
  • Introduction
  • Body of chapter
  • Conclusion
  • References
  • Glossary of Terms
  • Appendices
  • List of terms to be used in the Index

The Chapter should follow and conform to APA style.  The length of the Chapter should be between 5,000 – 6,000 words including the references. Please email your chapter to Xuanwei (Ada) Ma at with a copy to Dr Yuchen Wang at

The length of the chapter should be between 5,000 and 6,000 words. The due date for the chapter is September 30, 2018.

For more information on APA writing style, please visit

Please do not hesitate to contact us if you have questions.



Xuanwei (Ada) Ma

Beijing Normal University





Dr Jeremy Knox – The University of Edinburgh

Dr Yuchen Wang – The University of Edinburgh

Dr Michael Gallagher – The University of Edinburgh