Student data and learning analytics: Anonymity, confidentiality, privacy

Feedback from students is considered essential to continuous improvement in teaching at all levels, particularly in learner-centered education. This project looks at universities’ privacy and confidentiality policies and frameworks on the use of student feedback data, to inform decisions on program/curriculum enhancements and resource allocations for student success. Data can be from monitoring what students do online and what they expressed in their course evaluations. Data by itself, however, is not enough. An institution’s privacy and confidentiality policies influence how effectively such student feedback data can be used to inform decisions. This research will look at practices in universities and the state of the art research in this area in order to answer the question: How are universities providing a balance between collecting and using valuable student feedback with other student data such as online behavior and demographics, while at the same time ensuring that their privacy rights are being protected?

Faculty Supervisor:

Kimiz Dalkir


Rebecca Katz


Explorance Inc.








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