While universities routinely use student data to monitor and predict student performance, there has been limited engagement with student and staff views, social and ethical issues, policy development, and ethical guidance. We reviewed peer-reviewed and grey-literature articles of 2007 to 2018 describing the perspectives of staff and students in tertiary education on the use of student-generated data in data analytics, including learning analytics. We used an ethics framework to categorize the findings. There was considerable variation but generally low awareness and understanding amongst students and staff about the nature and extent of data collection, data analytics, and use of predictive analytics. Staff and students identified potential benefits but also expressed concerns about misinterpretation of data, constant surveillance, poor transparency, inadequate support, and potential to impede active learning. This review supports the contention that consideration of ethical issues has failed to keep pace with the development of predictive analytics in the tertiary sector.