Learning analytics and its paternalistic influences

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Abstract

Learning analytics is a technology that employs paternalistic nudging techniques and predictive measures. These techniques can limit student autonomy, may run counter to student interests and preferences, and do not always distribute benefits back to students-in fact some harms may actually accrue. The paper presents three cases of paternalism in learning analytics technologies, arguing that paternalism is an especially problematic concern for higher education institutions who espouse liberal education values. Three general recommendations are provided that work to promote student autonomy and choice making as a way to protect against risks to student academic freedom.

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APA

Jones, K. M. L. (2017). Learning analytics and its paternalistic influences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10296 LNCS, pp. 281–292). Springer Verlag. https://doi.org/10.1007/978-3-319-58515-4_22

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