Ethical use of learning analytics for student support, not surveillance - Geisel, Jayne; Warkentin, Hannah; Snow, Jessica (Canadian Perspectives on Academic Integrity, 2022)
The move to online education necessitated by the COVID-19 pandemic has greatly increased institutional use of learning management systems, contributing to vast amounts of educational data, ranging from information on admissions and retention, to the minutiae of course activities. These vast amounts of learner data are collected, measured, analyzed, and reported on to understand learning, learners and the learning environment and can be defined as learning analytics (LA). LA are intended to support students and assist with their success; however, most instructors and students are unaware of how learning analytics can be used in their courses and are consequently unfamiliar with the ethical implications arising from that use. Contributing to this gap is the lack of literature examining the use of LA at the instructor and course level, rather than at the level of the institution. This lack of familiarity with the use of, and ethical principles related to, LA has created, for many faculty, a default to using analytics for performance management, surveillance, and evidence of academic misconduct rather than to support learning. This presentation will address this gap by examining the ethical issues associated with the use of learning analytics specifically for instructors, and provide recommended best practices, resources, and tips to better support students, particularly in online or blended learning contexts. The intent of this research is to provide a guiding framework for the ethical use of LA to promote robust pedagogical practices, transparency between instructors and students so the focus is on academic integrity rather than misconduct.