Buried treasure or Ill-gotten spoils: the ethics of data mining and learning analytics in online instruction

Abstract

This paper considers the practical applications of the article, Ethical Oversight of Student Data in Learning Analytics: A Typology Derived from a Cross-continental, Cross-institutional Perspective by Willis et al. (Educ Technol Res Dev 64: 881–901, 2016). Students engaging in online learning leave behind vast quantities of data. In 2020, the rapid shift to online learning during the global pandemic allowed virtual data collection to outpace procedures and policies that promote ethical analysis. The mere availability of data does not confer ethical collection of data. Further, analysis of data under the assumption of learning outcomes does not necessarily ensure justice or learning for students. This article offers possible applications of the heuristic by Willis et al. (Educ Technol Res Dev 64: 881–901, 2016) for ethical learning analytics in order to mitigate harm to students. It extends their work by suggesting educators consider the racialized encoding of data themselves, and argues that every act of surveillance during the pandemic creates norms for future surveillance.