We are still designing educational experiences for the average student, and have room to improve. Learning analytics provides a way forward. This commentary describes how learning analytics-based applications are well positioned to meaningfully personalize the learning experience in diverse ways. In so doing, learning analytics has the potential to contribute to more equitable and socially just educational outcomes for students who might otherwise be seen through the lens of the average student. Utilizing big data, good design, and the input of the stakeholders, learning analytics techniques aim to develop applications for the sole purpose of reducing the classroom size to 1. Over time, these digital innovations will enable us to do away with a model of education that teaches toward the non-existent average student, replacing it with one that is more socially just—one that addresses the individual needs of every student.
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The author would like to thank the University of Southern California’s Provost’s Postdoctoral Scholars Program for its support, as well as Dr. Stuart Karabenick, Dr. Steven Lonn, and Dr. Stephanie Teasley who nurtured an early interest in learning analytics applications.
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Aguilar, S.J. Learning Analytics: at the Nexus of Big Data, Digital Innovation, and Social Justice in Education. TechTrends 62, 37–45 (2018). https://doi.org/10.1007/s11528-017-0226-9
- Learning analytics
- Social justice
- Digital innovation
- Educational technology
- Personalized learning