Disability, Data, and Design: Toward a Critical Framework for Evaluating AI in Inclusive Education

References

[1] Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim code. Polity Press. [ISBN 978-1-509526390]

[2] Campbell, F.K. (2009). Contours of ableism: The production of disability and abledness. Palgrave Macmillan. https://doi.org/10.1057/9780230245181

[3] Crompton, H. & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), Article 22. https://doi.org/10.1186/s41239-023-00392-8

[4] du Boulay, B. (2016). Recent meta-reviews and meta-analyses of AIED systems. International Journal of Artificial Intelligence in Education, 26, 536–537. https://doi.org/10.1007/s40593-015-0060-1

[5] Eccles, S., Hutchings, M., Hunt, C. & Heaslip, V. (2018). Disclosure of 'disability' in higher education: A qualitative study of student perceptions. Widening Participation and Lifelong Learning, 20(4), 191–208. https://doi.org/10.5456/WPLL.20.4.191

[6] Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police and punish the poor. St. Martin's Press. [ISBN 978-1-250074317]

[7] Fawns, T. (2019). Postdigital education in design and practice. Postdigital Science and Education, 1(1), 132–145. https://doi.org/10.1007/s4243 8-0180021-8

[8] Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198237907.001.0001

[9] Goode, J. (2007). 'Managing' disability: Early experiences of university students with disabilities. Disability & Society, 22(1), 35–48. https://doi.org/101080/09687590601056204

[10] Goodley, D. (2014). Dis/ability studies: Theorising disablism and ableism. Routledge. https://doi.org/10.4324/9780203366974

[11] Hamraie, A. & Fritsch, K. (2019). Crip technoscience manifesto. Catalyst: Feminism, Theory, Technoscience, 5(1), 1–34. https://doi.org/10.28968/cftt.v5i1.29607

[12] Holmes, W., Bialik, M. & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. [ISBN 978-1-794293700]

[13] Jabareen, Y. (2009). Building a conceptual framework: Philosophy, definitions, and procedure International Journal of Qualitative Methods, 8(4), 49–62. Https://doi.org/10.1177/160940690900800406

[14] Jandrić, P., Ryberg, T., Knox, J., Lacković, N., Hayes, S., Suoranta, J., Smith, M., Steketee, A., Peters, M.A., McLaren, P., Ford, D.R., Asher, G., McGregor, C., Stewart, G., Williamson, B. & Gibbons, A. (2019). Postdigital dialogue. Postdigital Science and Education, 1(1), 163–189. https://doi.org/10.1007/s42438-018--x

[15] Kafer, A. (2013). Feminist, queer, crip. Indiana University Press. [ISBN 978-0-253-00934-5]

[16] Knox, J. (2019). What does the 'postdigital' mean for education? Three critical perspectives on the digital, with implications for educational research and practice. Postdigital Science and Education, 1(2), 357–370. https://doi.org/10.1007/-019-00045-y

[17] Madriaga, M. (2007). Enduring disablism: Students with dyslexia and their pathways into UK higher education and beyond. Disability & Society, 22(4), 399–412. https://doi.org/10.1080/09687590701337942

[18] Noble, S.U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press. [ISBN 978-1-479837243]

[19] Nussbaum, M.C. (2011). Creating capabilities: The human development approach. Harvard University Press. [ISBN 978-0-674-05054-9]

[20] Oliver, M. (1990). The politics of disablement. Macmillan. [ISBN 0-333-43293-0]

[21] Selwyn, N. (2022). The future of AI and education: Some cautionary notes. European Journal of Education, 57, 620–631. https://doi.org/10.1111/ejed.12532

[22] Sen, A. (1999). Development as freedom. Oxford University Press. [ISBN 0-19-829758-0]

[23] Shakespeare, T. (2014). Disability rights and wrongs revisited (2nd ed.). Routledge. https://doi.org/10.4324/9781315887456

[24] Terzi, L. (2005). Beyond the dilemma of difference: The capability approach to disability and special educational needs. Journal of Philosophy of Education, 39(3), 443–459. https://doi.org/10.1111/j.1467-9752.2005.00447.x

[25] Thomas, C. (2007). Sociologies of disability and illness: Contested ideas in disability studies and medical sociology. Palgrave Macmillan. https://doi.org/10.1007/978-1-137-02019-2

[26] Whittaker, M., Alper, M., Bennett, C.L., Hendren, S., Kaziunas, L., Mills, M., Morris, M.R., Rankin, J., Rogers, E., Salas, M. & West, S.M. (2019). Disability, bias, and AI. AI Now Institute. https://ainowinstitute.org/publications/disabilitybiasai-2019

[27] Williamson, B. (2017). Big data in education: The digital future of learning, policy and practice. SAGE Publications. https://doi.org/10.4135/9781529714920

[28] Zawacki-Richter, O., Marín, V.I., Bond, M. & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education — where are the educators? International Journal of Educational Technology in Higher Education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0

@article{1719101,
      author = {Nicki James Shepherd},
      title = {Disability, Data, and Design: Toward a Critical Framework for Evaluating AI in Inclusive Education},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {12},
      pages = {2218-2230},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719101.pdf},
      abstract = {In today's digital landscape, artificial intelligence (AI) is significantly influencing higher education by driving adaptive learning platforms, automated assessment, predictive analytics, and generative AI tools.From adaptive learning systems to predictive analytics and automated assessment, AI is transforming higher education in today's digital era. The developments bring up some significant issues relating to the impact these will have on disabled learners. Though the issues of equity and inclusion are common to both fields, AI in Education (AIED) and critical disability studies have developed separately for the most part. This paper presents a critical evaluative approach to evaluate the impacts of AI systems in education on reinforcing, challenging or changing ableist structures. The framework centres on four aspects: (1) the range of assumptions of a normed nondisabled learner that may be found in system design and training data; (2) whose ability can be facilitated by AI adaptations; (3) the politics of disclosure, personalisation and surveillance; and (4) whose knowledge and perspectives inform system development. It summarizes existing research on both sides, proposes theoretical links, and illustrates its applicability in three educational AI scenarios, providing a basis for empirical and critical research.},
      keywords = {Artificial Intelligence in Education, Critical Disability Studies, Ableism, Capability Approach},
      month = {June},
      doi = {https://doi.org/10.64388/IREV8I12-1719101}
  }