“It’s like a double-edged sword”: Mentor Perspectives on Ethics and Responsibility in a Learning Analytics–Supported Virtual Mentoring Program

Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection uses of learner data. Considerations potential harm ethical implications have not kept pace, raising concerns about privacy issues (Holstein & Doroudi, 2019; Prinsloo Slade, 2018). This empirical study contributes to a growing critical conversation on fairness, equity, responsibility LA lending mentor voices in context an online mentorship program through which undergraduate students mentored secondary school students. Specifically, this responds phenomenon shared by four mentors who recounted hiding from mentees that they had seen their Interviews reveal convergent divergent ideas regarding terms 1) affordances constraints, 2) scope boundaries, 3) tensions dilemmas, 4) paradoxical demands, 5) what constitutes responsibility. The analysis integrates with Slade Prinsloo’s (2013) principles for framework LA, Hacking’s (1982, 1986) dynamic nominalism, Levinas’s (1989) ethics Design recommendations derived insights are extended discussion relationality, troubling learners as data-subjects, considering possibilities agency, transparency, choice system design.