Ethical considerations of using learning analytics in medical education: a critical review

Learning analytics are increasingly used in medical education to analyze data and make decisions about learners' abilities. While there are many potential benefits of using learning analytics to drive improvement in medical education, there are also ethical concerns surrounding how this may affect learners and their patients. We conducted a critical review of studies that use learning analytics and big data within medical education. Using guidelines established by Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), relevant articles were identified in MEDLINE (PubMed) and SocINDEX databases from inception to April 2021. Detailed data abstraction was performed across studies to identify current uses of learning analytics and identify potential ethical concerns. Eighteen articles met the search criteria. Our analysis identified the use of learning analytics and big data in four aspects of medical education: (1) the learning process and pedagogy; (2) retrospective assessment; (3) prospective assessment; and (4) improvement of education. We identified some ethical concerns surrounding the use of learning analytics and big data, including the (1) trustworthiness of data; (2) reliability of methodology; (3) privacy, confidentiality, and management of data; and (4) labeling of learners as "problematic." Using Beauchamp and Childress's biomedical ethics as a framework, we identified potential consequences of using learning analytics for learners within the principles of beneficence, nonmaleficence, autonomy, and justice. As learning analytics becomes more widespread in medical education, examining and mitigating potential harm towards learners is imperative.