This document summarizes a presentation about establishing an ethics framework for predictive analytics using student data in higher education. It discusses how technology has enabled more data collection and predictive modeling of student behavior. However, few guidelines exist for these practices. The presentation advocates developing an ethics framework that safeguards student privacy, promotes transparency, considers unintended consequences, and involves consultation. It also examines existing principles and discusses challenges like opaque predictive models that work against students' interests. The presenter argues universities should internalize norms of respecting trust and serving students, not just avoiding legal issues.
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