WHEN THE CLASSROOM BECOMES DATAFIED: A BASELINE FOR BUILDING DATA ETHICS POLICY AND DATA LITERACIES ACROSS HIGHER EDUCATION

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Bonnie E Stewart
Erica Lyons

Abstract

This paper overviews a summer 2020 pilot survey of educators’ perspectives on the intersection of educational technology and datafication in higher education classrooms. The brief, international survey of university teachers used four proxy questions to frame a baseline snapshot of higher education teaching populations’ knowledge, practices, experience, and perspectives on data and online learning: this paper focuses specifically on the results of the knowledge and practice questions. The paper suggests that, in the Emergency Remote Education (ERE) context generated by the COVID-19 pandemic, higher education instructors teaching online demonstrate patterns of limited knowledge and practice surrounding the data aspects of their classroom tools. The paper posits an urgent need for institutional and sector-wide policy and faculty development around data and online classroom tools, and for data ethics to be addressed as part of institutions’ ERE transition online.

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References

Bates, A.W. (2019). Teaching in a digital age: Guidelines for designing teaching and learning. Victoria, BC: BCCampus. Retrieved from https://opentextbc.ca/teachinginadigitalage/

Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Cambridge, UK: Polity.

Braunack-Meyer, A.J., Street, J.M., Tooher, R., Feng, X., & Scharling-Gamba, K. (2020). Student and staff perspectives on the use of big data in the tertiary education sector: A scoping review and reflection on the ethical issues. Review of Educational Research, 90(6), 1-36. doi: 10.3102/0034654320960213

Brinkman, B. (2013). An analysis of student privacy rights in the use of plagiarism detection systems. Science and Engineering Ethics, 19(3), 1255-1266.

Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., ... & Rodes, V. (2020). A global outlook to the interruption of education due to COVID-19 Pandemic: Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1-126.

Chadwick, J. (2020, July 2). MIT apologises after a giant dataset it was using to teach AI how to recognise people and objects in images was found to be assigning racist and misogynistic labels. The Daily Mail. Retrieved from https://www.dailymail.co.uk/sciencetech/article-8483929/MIT-pulls-racist-misogynistic-dataset-offline.html

Erickson, K. (2018, July 17). The future of network effects: Tokenization and the end of extraction. Medium. Retrieved from https://medium.com/public-market/the-future-of-network-effects-tokenization-and-the-end-of-extraction-a0f895639ffb

Flaherty, C. (2020, May 11). Big proctor. Inside Higher Education. Retrieved from https://www.insidehighered.com/news/2020/05/11/online-proctoring-surging-during-covid-19

Gilliard, C. & Culik, H. (2016, May 24). Filtering content is often done with good intent, but filtering can also create equity and privacy issues. Common Sense. Retrieved from https://www.commonsense.org/education/articles/digital-redlining-access-and-privacy

Johnson, J.A. (2019). Constructing data ethically. New Directions for Institutional Research, 2019(182), 35-50. doi: 10.1002/ir.20306

Jones, W.D. (2020). Racial profiling goes high tech with facial recognition. IEEE Spectrum. Retrieved from https://spectrum.ieee.org/tech-talk/computing/software/do-you-have-the-right-complexion-for-facial-recognition

Kolowich, S. (2013, April 15). Behind the webcam’s watchful eye, online proctoring takes hold. The Chronicle of Higher Education. Retrieved from http://chronicle.com/article/Behind-the-Webcams-Watchful/138505/

Land, R. & Bayne, S. (2005). Screen or monitor. In Bayne, S., & Land, R. (Eds.), Education in Cyberspace (pp. 165-179). London, UK: RoutledgeFalmer. doi: 10.4324/9780203391068

Long, P. & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30-32. Retrieved from https://er.educause.edu/~/media/files/article-downloads/erm1151.pdf%20

MacCarthy, M. (2014). Student privacy: Harm and context. International Review of Information Ethics, 21, 11-24

Marachi, R., & Quill, L. 2020. The case of Canvas: Longitudinal datafication through learning management systems. Teaching in Higher Education 25(4), 418–434. doi: 10.1080/13562517.2020.1739641

Maybee, C., & Zilinski, L. (2015). Data informed learning: A next phase data literacy framework for higher education. Proceedings of the Association for Information Science and Technology, 52(1), 1-4.

Morris, S., & Stommel, J. (2017). A guide for resisting edtech: The case against Turnitin. Hybrid Pedagogy, 15. Retrieved from https://hybridpedagogy.org/resisting-edtech/

Noble, S.U. (2018). Algorithms of oppression: How search engines reinforce racism. New York, NY, US: NYU Press.

Obar, J. & Oeldorf-Hirsch, A. (2020). The biggest lie on the Internet: Ignoring the privacy policies and terms of service policies of social networking services. Information, Communication & Society, 23(1), 128-147. doi: 10.1080/1369118X.2018.1486870

O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. London, UK: Allen Lane Penguin Books.

Pangrazio, L., & Selwyn, N. (2019). ‘Personal data literacies’: A critical literacies approach to enhancing understandings of personal digital data. New Media and Society, 21(2), 419–437. doi: 10.1177/1461444818799523

Perrotta, C., & Williamson, B. (2018). The social life of Learning Analytics: Cluster analysis and the ‘performance’ of algorithmic education. Learning, Media and Technology, 43(1), 3-6. doi: 10.1080/17439884.2016.1182927

Raffaghelli, J.E. (2017). Exploring the (missed) connections between digital scholarship and faculty development: a conceptual analysis. International Journal of Educational Technology in Higher Education, 14(20). doi: 10.1186/s41239-017-0058-x

Raffaghelli, J.E. (2020). Is data literacy a catalyst of social justice? A response from nine data literacy initiatives in higher education. Education Sciences, 10(9), 233-253. doi: 10.3390/educsci10090233

Raffaghelli, J., Manca, S., Stewart, B., Prinsloo, P, & Sangrà, A. (2020). Supporting the development of critical data literacies in higher education: building blocks for fair data cultures in society. International Journal of Educational Technology in Higher Education, 17(58), 1-22. doi: 10.1186/s41239-020-00235-w

Raffaghelli, J., & Stewart, B. (2020). Centering complexity in “educators’ data literacy:” A critical review of faculty development literature. Teaching in Higher Education, 25(4), 435-455. doi: 10.1080/13562517.2019.1696301

Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510-1529. doi: 10.1177/0002764213479366

Stewart, B. (2020). The Open Page Project: Putting digital learning principles into practice for pre-service educators. Journal of Teaching and Learning, 14(1), 59-70. doi: 10.22329/JTL.V14I1.6265

Swauger, S. (2020). Our bodies encoded: Algorithmic test proctoring in higher education. Hybrid Pedagogy. Retrieved from https://hybridpedagogy.org/our-bodies-encoded-algorithmic-test-proctoring-in-higher-education/

Tsai, Y.S., & Gašević, D. (2017). Learning analytics in higher education -- challenges and policies: A review of eight learning analytics policies. Proceedings of the Seventh International Learning Analytics & Knowledge Conference on LAK ’17. ACM Press, 233–42. Retrieved from http://dl.acm.org/citation.cfm?doid=3027385.3027400

Tufekci, Z. (2020, September 4). The pandemic is no excuse to surveil students. The Atlantic. Retrieved from https://www.theatlantic.com/technology/archive/2020/09/pandemic-no-excuse-colleges-surveil-students/616015/

Weber-Wulff, D. (2019). Plagiarism detectors are a crutch, and a problem. Nature, 567(7749), 435-436.

Webster-Wright, A. (2009). Reframing professional development through understanding authentic professional learning. Review of Educational Research, 79(2), 702-739. https://doi.org/10.3102/0034654308330970

Williamson, B. (2017). Big data in education: The digital future of learning, policy and practice. London, UK: SAGE.

Williamson, B. (2020). The Automatic University A review of datafication and automation in higher education. University and College Union. https://www.ucu.org.uk/media/10947/The-automatic-university/pdf/ucus_the-automatic-university_jun20.pdf

Williamson, B., Bayne, S., & Shay, S. (2020). The datafication of teaching in higher education: Critical issues and perspectives. Teaching in Higher Education, 25(4), 351-365. doi: 10.1080/13562517.2020.1748811

Willis, J., Slade, S., & Prinsloo, P. (2016). Ethical oversight of student data in learning analytics: A typology derived from a cross-continental, cross-institutional perspective. Educational Technology Research and Development, 64. doi: 10.1007/s11423-016-9463-4

Winter, R. (2009). Academic manager or managed academic? Academic identity schisms in higher education. Journal of Higher Education Policy and Management, 31(22), 121–131.