Student Privacy in Learning Analytics: An Information Ethics Perspective
Alan Rubel and Kyle M. L. Jones
Higher education institutions have started using big data analytics tools. By gathering information about students as they navigate information systems, learning analytics employs techniques to understand student behaviors and improve instructional, curricular, and support resources and improve learning environments. However, learning analytics presents important moral and policy issues surrounding student privacy. We argue that there are five crucial questions about student privacy that we must address in order to ensure that whatever the laudable goals and gains of learning analytics, they are commensurate with respecting students’ privacy and associated rights, including (but not limited to) autonomy interests. We address information access concerns, the intrusive nature of information gathering practices, whether or not learning analytics is justified given the potential distribution of consequences and benefits, and issues related to student autonomy. Finally, we question if learning analytics advances the aims of higher education or runs counter to those goals.
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