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This response to Neil Selwyn’s paper, ‘What’s the problem with learning analytics?’, relates his work to the ethical challenges associated with learning analytics and proposes six ethical challenges for the field.
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Albuquerque, J., Bittencourt, I. I., Coelho, J. A. P. M., & Silva, A. P. (2017). Does gender stereotype threat in gamified educational environments cause anxiety? An experimental study. Computers & Education, 115, 161–170. https://dx.doi.org/10.1016/j.compedu.2017.08.005
Alhadad, S. S. J. (2018). Visualizing data to support judgement, inference, and decision making in learning analytics: Insights from cognitive psychology and visualization science. Journal of Learning Analytics, 5(2), 60–85. http://dx.doi.org/10.18608/jla.2018.52.5
Arroyo, I., Ferguson, K., Johns, J., Dragon, T., Meheranian, H., Fisher, D., Barto, A., Mahadevan, S. & Woolf, B. P. (2007). Repairing disengagement with non-invasive interventions. Artificial Intelligence in Education, 158, 195–202. https://scholarworks.umass.edu/cs_faculty_pubs/326
Diakopoulos, N. (2014). Algorithmic accountability reporting: On the investigation of black boxes. Tow Center for Digital Journalism, Columbia Journalism School. https://dx.doi.org/10.7916/D8ZK5TW2
Echeverria, V., Martinez-Maldonado, R., & Buckingham Shum, S. (2019). Towards collaboration translucence: Giving meaning to multimodal group data. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19), 4–9 May 2019, Glasgow, Scotland, UK, Paper No. 39. New York: ACM. http://dx.doi.org/10.1145/3290605.3300269
Evrard, A. E., & Teplovs, C. (2017). Community building around a shared history: Rebooting academic reporting tools at the University of Michigan. Paper presented at the 7th International Conference on Learning Analytics and Knowledge (LAK ’17), 13–17 March 2017, Vancouver, BC, Canada (practitioner track).
Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317. https://dx.doi.org/10.1504/IJTEL.2012.051816
Ferguson, R., Brasher, A., Clow, D., Cooper, A., Hillaire, G., Mittelmeier, J., Rienties, B., Ullmann, T. & Vuorikari, R. (2016). Research evidence on the use of learning analytics: Implications for education policy. Joint Research Centre Science for Policy Report, EUR 28294 https://dx.doi.org/10.2791/955210
Ferguson, R., Hoel, T., Scheffel, M., & Drachsler, H. (2016). Ethics and privacy in learning analytics. Journal of Learning Analytics, 3(1), 5–15.
García, R. C., Pardo, A., Delgado Kloos, C., Niemann, K., Scheffel, M., & Wolpers, M. (2012). Peeking into the black box: Visualising learning activities. International Journal of Technology Enhanced Learning, 4(1/2), 99–120. http://dx.doi.org/10.1504/IJTEL.2012.048313
Knight, S., Buckingham Shum, S., Ryan, P., Sándor, Á., & Wang, X. Designing academic writing analytics for civil law student self-assessment. International Journal of Artificial Intelligence in Education, 28(1), 1–28. doi: https://dx.doi.org/10.1007/s40593-016-0121-0
Knox, J. (2017). Playing with student data: The Learning Analytics Report Card (LARC). Paper presented at the 7th International Conference on Learning Analytics and Knowledge (LAK ’17), 13–17 March 2017, Vancouver, BC, Canada (practitioner track).
Liu, D. Y.-T., Rogers, T., & Pardo, A. (2015). Learning analytics: Are we at risk of missing the point? In T. Reiners, B. R. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds.), Globally Connected, Digitally Enabled: Proceedings of the 32nd Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE 2015), 29 November–2 December 2015, Perth, Western Australia (pp. 684–687). Australasian Society for Computers in Learning in Tertiary Education.
Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 31–40.
Murray, P. M. (1990). The history of informed consent. The Iowa Orthopaedic Journal, 10, 104–109.
Pardo, A., Jovanovic, J., Dawson, S., Gašević, D., & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalised feedback. British Journal of Educational Technology, 50(1), 128–138. doi: https://dx.doi.org/10.1111/bjet.12592
Richardson, J. T. E. (2009). The academic attainment of students with disabilities in UK higher education. Studies in Higher Education, 34(2), 123–137. https://dx.doi.org/10.1080/03075070802596996
Richardson, J. T. E. (2015). The under-attainment of ethnic minority students in UK higher education: What we know and what we don’t know. Journal of Further and Higher Education, 39(2), 278–291. doi: https://dx.doi.org/10.1080/0309877X.2013.858680
Roll, I., & Winne, P. H. (2015). Understanding, evaluating, and supporting self–regulated learning using learning analytics. Journal of Learning Analytics, 2(1), 7–12. https://dx.doi.org/10.18608/jla.2015.21.2
Saltelli, A. (2017). International PISA tests show how evidence-based policy can go wrong. The Conversation, 12 June 2017. https://theconversation.com/international-pisa-tests-show-how-evidence-based-policy-can-go-wrong-77847
Selwyn, N. (2019). What’s the problem with learning analytics? Journal of Learning Analytics, 6(3), 11–19. http://dx.doi.org/10.18608/jla.2019.63.3
Slade, S., & Prinsloo, P. (2015). Student perspectives on the use of their data: Between intrusion, surveillance and care. European Journal of Open, Distance and E-learning, 18(1). https://www.eurodl.org/?p=special&sp=articles&inum=7&article=679
Slade, S., Prinsloo, P., & Khalil, M. (2019). Learning analytics at the intersections of student trust, disclosure and benefit. Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK ’19), 4–8 March 2019, Tempe, Arizona, USA (pp. 235–244). New York: ACM. http://dx.doi.org/10.1145/3303772.3303796
Wallen, J. (2019). Over twenty Indian students commit suicide after inaccurate university admission results. The Telegraph, April 30, 2019. https://www.telegraph.co.uk/news/2019/04/30/twenty-indian-students-commit-suicide-inaccurate-university/
Williamson, B. (2018, March 17). 10 definitions of datafication (in education). https://codeactsineducation.wordpress.com/2018/03/17/10-definitions-datafication/