Answer to "What are some of the ethical considerations involved in learning analytics?"

Topic Editor: Dr. Stefanie Sebok-Syer, Stanford University


Privacy is an obstacle when it comes to learning analytics. Concerns about who should be able to access data and how it should be used also get much attention in the literature. Data governance – which is who can access what, when, and why – can influence the utility and extent to which learning analytics can have a meaningful impact. This can be observed when there are limited leadership and management capabilities to ensure that learning analytic systems are thoughtfully developed and monitored. Issues surrounding data ownership and access, especially when individuals belong or move between various institutions and systems, can limit the value generated from educational data. Careful attention must be paid to deploying learning analytic systems that will operate with little to no human oversight less they reinforce existing biases. For example, learning analytics systems used for admissions purposes may use socioeconomic or demographic information to inform decision-making. This could inadvertently reinforce stereotypes and biases about various groups of individuals. To mitigate ethical issues related stemming from learning analytics, policies and guidelines should be developed to support appropriate data use. 



Avella J. T., Kebritchi, M., Dunn, S. G., Kanai T (2016) Learning analytics methods, benefits, and challenges in higher education: a systematic literature review. Online Learning, 20,13-29.

Ekowo, M., & Palmer, I. (2017). Predictive analytics in higher education: Five guiding practices for ethical use. Retrieved from

Kay, D., Korn, N., & Oppenheim, C. (2012). Legal, risk and ethical aspects of analytics in higher education. Retrieved from

Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 45, 438-450.

Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57, 1510-1529.

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