Advancing data justice in education: some suggestions towards a deontological framework

References

• Alcoff, Linda Martín. 2007. “Fraser on Redistribution, Recognition, and Identity.” European Journal of Political Theory 6 (3): 255–265.
   Google Scholar
• Andreotti, Vanessa, Sharon Stein, Cash Ahenakew, and Dallas Hunt. 2015. “Mapping Interpretations of Decolonization in the Context of Higher Education.” Decolonization: Indigeneity, Education & Society 4 (1): 22–40.
   Google Scholar
• Bainbridge, Lisanne. 1983. “Ironies of Automation.” Automatica 19 (6): 775–779. doi:10.1016/0005-1098(83)90046-8.
   Web of Science ®Google Scholar
• Baker, Ryan Shaun, and Aaron Hawn. 2021. “Algorithmic Bias in Education.” International Journal of Artificial Intelligence in Education, doi:10.1007/s40593-021-00285-9.
   Web of Science ®Google Scholar
• Barocas, Solon, Kate Crawford, Aaron Shapiro, and Hanna Wallach. 2017. The problem with bias: Allocative versus representational harms in machine learning. Paper presented at the 9th Annual Conference of the Special Interest Group for Computing, Information and Society.
   Google Scholar
• Benjamin, Ruha. 2019. “Race After Technology: Abolitionist Tools for the new jim Code.” Social Forces.
   Web of Science ®Google Scholar
• Birhane, Abeba, and Vinay Uday Prabhu. 2021. Large image datasets: A pyrrhic win for computer vision? Paper presented at the 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
   Google Scholar
• Blackmore, Jill. 2016. Educational Leadership and Nancy Fraser. London: Routledge.
   Google Scholar
• Blodgett, Su Lin, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020. Language (technology) is power: A critical survey of” bias” in nlp. Paper presented at the 58th Annual Meeting of the Association for Computational Linguistics, Online.
   Google Scholar
• Blumenthal, Richard, Ron Wyden, Chris Van Hollen, Tina Smith, and Elizabeth Warren. 2020 “Open Letter to Examsoft” US Senate, Accessed 12/12/2021. https://www.blumenthal.senate.gov/imo/media/doc/2020.12.3%20Letter%20to%20Ed%20Testing%20Software%20Companies%20ExamSoft.pdf.
   Google Scholar
• Bozalek, Vivienne, and Chrissie Boughey. 2012. “(Mis)Framing Higher Education in South Africa.” Social Policy & Administration 46 (6): 688–703. doi:10.1111/j.1467-9515.2012.00863.x.
   Web of Science ®Google Scholar
• Callon, Michel, Pierre Lascoumes, and Yannick Barthe. 2011. Acting in an Uncertain World: An Essay on Technical Democracy. Cambridge, MA: MIT press.
   Google Scholar
• Cerratto Pargman, Teresa, and Cormac McGrath. 2021. “Mapping the Ethics of Learning Analytics in Higher Education: A Systematic Literature Review of Empirical Research.” Journal of Learning Analytics 8 (2): 123–139.
   Google Scholar
• Costanza-Chock, Sasha. 2020. Design Justice: Community-led Practices to Build the Worlds we Need. Cambridge, MA: The MIT Press.
   Google Scholar
• Danks, David, and Alex John London. 2017. Algorithmic Bias in Autonomous Systems. Paper presented at the IJCAI.
   Google Scholar
• Dencik, L., A. Hintz, J. Redden, and E. Treré. 2019. “Exploring Data Justice: Conceptions, Applications and Directions.” Information Communication and Society 22 (7): 873–881. doi:10.1080/1369118X.2019.1606268.
   Web of Science ®Google Scholar
• Dencik, Lina, Fieke Jansen, and Philippa Metcalfe. 2018. “A conceptual framework for approaching social justice in an age of datafication.” DATAJUSTICE project 30.
   Google Scholar
• Dixon-Román, Ezekiel, T. Philip Nichols, and Ama Nyame-Mensah. 2019. “The Racializing Forces of/in AI Educational Technologies.” Learning, Media and Technology, 1–15. doi:10.1080/17439884.2020.1667825.
   Web of Science ®Google Scholar
• Eubanks, Virginia. 2018. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York, NY: St. Martin's Press.
   Google Scholar
• EU Commission. 2022. “Proposal for a Directive of the European Parliament and of the Council on adapting non-contractual civil liability rules to artificial intelligence (AI Liability Directive).” In, edited by European Commission.
   Google Scholar
• Farías, Ignacio. 2016. “Devising Hybrid Forums: Technical Democracy in a Dangerous World.” City 20 (4): 549–562.
   Google Scholar
• Fraser, Nancy. 1998. “From Redistribution to Recognition?: Dilemmas of Justice in a ‘Postsocialist’ Age.” In In her Justice Interruptus: Critical Reflections on the “Postsocialist” Condition, 11–40. New York, NY: Routledge.
   Google Scholar
• Fraser, Nancy. 2001. “Recognition Without Ethics?” Theory, Culture & Society 18 (2-3): 21–42. doi:10.1177/02632760122051760.
   Web of Science ®Google Scholar
• Fraser, Nancy. 2005. “Reframing Justice.” New Left Review 36 (Nov-Dec): 1–19.
   Google Scholar
• Fraser, Nancy. 2007a. “Feminist Politics in the age of Recognition: A two-Dimensional Approach to Gender Justice.” Studies in Social Justice 1 (1): 23–35.
   Google Scholar
• Fraser, Nancy. 2007b. “Identity, Exclusion, and Critique: A Response to Four Critics.” European Journal of Political Theory 6 (3): 305–338.
   Google Scholar
• Fraser, Nancy. 2013. Fortunes of Feminism: From State-Managed Capitalism to Neoliberal Crisis. Reframing Justice, NY: Verso Books.
   Google Scholar
• Gajane, Pratik, and Mykola Pechenizkiy. 2017. “On formalizing fairness in prediction with machine learning.” arXiv preprint arXiv:1710.03184.
   Google Scholar
• Gewirtz, Sharon. 1998. “Conceptualizing Social Justice in Education: Mapping the Territory.” Journal of Education Policy 13 (4): 469–484.
   Google Scholar
• Gianfrancesco, Milena A., Suzanne Tamang, Jinoos Yazdany, and Gabriela Schmajuk. 2018. “Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data.” JAMA Internal Medicine 178 (11): 1544–1547. doi:10.1001/jamainternmed.2018.3763.
   PubMed Web of Science ®Google Scholar
• Gulson, Kalervo, Claire Benn, Kirsty Kitto, Simon Knight, and Teresa Swift. 2021. “Algorithms can decide your marks, your work prospects and your financial security. How do you know they’re fair?” The Conversation.
   Google Scholar
• Hoffmann, Anna Lauren. 2019. “Where Fairness Fails: Data, Algorithms, and the Limits of Antidiscrimination Discourse.” Information, Communication & Society 22 (7): 900–915. doi:10.1080/1369118X.2019.1573912.
   Web of Science ®Google Scholar
• Hummel, Patrik, Matthias Braun, and Peter Dabrock. 2021. “Own data? Ethical Reflections on Data Ownership.” Philosophy and Technology 34 (3): 545–572.
   Google Scholar
• Jandrić, Petar, and Derek R. Ford. 2022. “Postdigital Ecopedagogies: Genealogies, Contradictions, and Possible Futures.” Postdigital Science and Education 4 (3): 692–710. doi:10.1007/s42438-020-00207-3.
   Google Scholar
• Johnson, Khari. 2020. “ExamSoft’s remote bar exam sparks privacy and facial recognition concerns.” Venturebeat.com, Accessed 10/12/2021. https://venturebeat.com/2020/09/29/examsofts-remote-bar-exam-sparks-privacy-and-facial-recognition-concerns/.
   Google Scholar
• Keddie, Amanda. 2012. “Schooling and Social Justice Through the Lenses of Nancy Fraser.” Critical Studies in Education 53 (3): 263–279.
   Web of Science ®Google Scholar
• Keuning, Hieke, Johan Jeuring, and Bastiaan Heeren. 2018. “A Systematic Literature Review of Automated Feedback Generation for Programming Exercises.” ACM Transactions on Computing Education (TOCE) 19 (1): 1–43.
   Web of Science ®Google Scholar
• Kizilcec, René F, and Hansol Lee. 2020. “Algorithmic fairness in education.” arXiv preprint arXiv:2007.05443.
   Google Scholar
• Kurzweil, Martin, and D. Derek Wu. 2015. “Building a pathway to student success at Georgia State University.”.
   Google Scholar
• Le Bui, Matthew, and Safiya Umoja Noble. 2020. “We’re Missing a Moral Framework of Justice in Artificial Intelligence.” In The Oxford Handbook of Ethics of AI, edited by Markus Dirk Dubber, Frank Pasquale, and Sunit Das, 163–180. New York, NY: Oxford University Press.
   Google Scholar
• Mannell, Kate, Robbie Fordyce, and Suneel Jethani. 2022. “Oaths and the Ethics of Automated Data: Limits to Porting the Hippocratic Oath from Medicine to Data Science.” Cultural Studies, 1–22. doi:10.1080/09502386.2022.2042577.
   Web of Science ®Google Scholar
• Maslow, Abraham H. 1948. ““Higher” and “Lower” Needs.” The Journal of Psychology 25 (2): 433–436.
   PubMed Web of Science ®Google Scholar
• Mehrabi, Ninareh, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan. 2021. “A Survey on Bias and Fairness in Machine Learning.” ACM Computing Surveys (CSUR) 54 (6): 1–35.
   Web of Science ®Google Scholar
• Mills, Martin, Glenda McGregor, Aspa Baroutsis, Kitty Te Riele, and Debra Hayes. 2016. “Alternative Education and Social Justice: Considering Issues of Affective and Contributive Justice.” Critical Studies in Education 57 (1): 100–115.
   Web of Science ®Google Scholar
• Mitchell, Shira, Eric Potash, Solon Barocas, Alexander D'Amour, and Kristian Lum. 2021. “Algorithmic Fairness: Choices, Assumptions, and Definitions.” Annual Review of Statistics and Its Application 8 (1): 141–163. doi:10.1146/annurev-statistics-042720-125902.
   Google Scholar
• Noble, Safiya Umoja. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. New York, NY: NYU Press.
   Google Scholar
• Nyuon, Nyadol. 2021. “Anti-vaxxers hide privilege behind language of oppression.” The Age, Accessed 17/12/2021. https://www.theage.com.au/national/anti-vaxxers-hide-privilege-behind-language-of-oppression-20211013-p58zix.html.
   Google Scholar
• Pangrazio, L., and J. Sefton-Green. 2020. “The Social Utility of ‘Data Literacy’.” Learning, Media and Technology 45 (2): 208–220. doi:10.1080/17439884.2020.1707223.
   Web of Science ®Google Scholar
• Pardo, Abelardo, Jelena Jovanovic, Shane Dawson, Dragan Gašević, and Negin Mirriahi. 2019. “Using Learning Analytics to Scale the Provision of Personalised Feedback.” British Journal of Educational Technology 50 (1): 128–138.
   Web of Science ®Google Scholar
• Peña Gangadharan, Seeta, and Jędrzej Niklas. 2019. “Decentering Technology in Discourse on Discrimination.” Information, Communication & Society 22 (7): 882–899. doi:10.1080/1369118X.2019.1593484.
   Web of Science ®Google Scholar
• Power, Sally, and Daniel Frandji. 2010. “Education Markets, the new Politics of Recognition and the Increasing Fatalism Towards Inequality.” Journal of Education Policy 25 (3): 385–396.
   Web of Science ®Google Scholar
• Sahlgren, Otto. 2021. “The Politics and Reciprocal (re) Configuration of Accountability and Fairness in Data-Driven Education.” Learning, Media and Technology, 1–14. doi:10.1080/17439884.2021.1986065.
   Web of Science ®Google Scholar
• Savage, Leonard J. 1972. The Foundations of Statistics (Second Edition). New York, NY: Dover.
   Google Scholar
• Selbst, Andrew D. 2021. “An Institutional View Of Algorithmic Impact Assessments.” Harvard Journal of Law & Technology (Forthcoming) 35 (UCLA School of Law, Public Law Research Paper No. 21-25).
   Google Scholar
• Selwyn, Neil. 2021. “Ed-Tech Within Limits: Anticipating Educational Technology in Times of Environmental Crisis.” E-Learning and Digital Media 18 (5): 496–510.
   Google Scholar
• Skitka, Linda J, Kathleen Mosier, and Mark D Burdick. 2000. “Accountability and Automation Bias.” International Journal of Human-Computer Studies 52 (4): 701–717.
   Web of Science ®Google Scholar
• Slade, S., P. Prinsloo, and M. Khalil. 2019. Learning analytics at the intersections of student trust, disclosure and benefit. Paper presented at the ACM International Conference Proceeding Series.
   Google Scholar
• Taylor, Linnet. 2017. “What is Data Justice? The Case for Connecting Digital Rights and Freedoms Globally.” Big Data & Society 4 (2): 2053951717736335.
   Web of Science ®Google Scholar
• Thompson, Greg, Kalervo N. Gulson, Teresa Swist, and Kevin Witzenberger. 2022. “Responding to Sociotechnical Controversies in Education: A Modest Proposal Toward Technical Democracy.” Learning, Media and Technology, 1–13. doi:10.1080/17439884.2022.2126495.
   Web of Science ®Google Scholar
• US Congress. 2021. “H.R.2231 - Algorithmic Accountability Act of 201.” Accessed 17/12/2021. https://www.congress.gov/bill/116th-congress/house-bill/2231/text.
   Google Scholar
• Viljoen, Salomé. 2020. “Democratic data: A relational theory for data governance.” Available at SSRN 3727562.
   Google Scholar
• Vincent, Carol. 2020. Nancy Fraser, Social Justice and Education. Abingdon: Routledge.
   Google Scholar
• Whitman, Madisson. 2020. ““We Called That a Behavior”: The Making of Institutional Data.” Big Data & Society 7 (1): 2053951720932200. doi:10.1177/2053951720932200.
   Web of Science ®Google Scholar
• Zeide, Elana. 2020. “Robot Teaching, Pedagogy, and Policy.” In The Oxford Handbook of Ethics of AI, edited by Markus D. Dubber, Frank Pasquale, and Sunit Das, 789–803. New York, NY: Oxford University Press.
   Google Scholar
• Zembylas, Michalinos. 2021. “A Decolonial Approach to AI in Higher Education Teaching and Learning: Strategies for Undoing the Ethics of Digital Neocolonialism.” Learning, Media and Technology, 1–13. doi:10.1080/17439884.2021.2010094.
   Web of Science ®Google Scholar