Answer to "What are preSCRIPtive learning analytics?"

Topic Editor: Dr. Brent Thoma, University of Saskatchewan

















Prescriptive analytics are better defined in the business world than the academic literature. They are defined as "Any combination of analytics, math, experiments, simulation, and/or artificial intelligence used to improve the effectiveness of decisions made by humans or by decision logic embedded in applications." [1] Stated more simply, they are analytics that are designed to guide decisions. Within the context of education, prescriptive analytics leverage descriptive, diagnostic, and predictive models and guide the collection of missing data to help institutions make better decisions.[2] Prescriptive analytics are not well described at the level of the learner, however, applications of these techniques are beginning to be described. For example, Pusic et al [3] have described the development of individual learning curves in the interpretation of pediatric radiographs  that could be used to guide the need for additional practice or instructor intervention. We anticipate that the use of this type of learning analytics will increase with the development of large datasets containing competency-based assessment information.[4]




  1. Gualtieri M. What exactly are prescriptive analytics? Forrester Blog. Published February 20, 2017 and retrieved from on June 22, 2018.

  2. Daniel B. Big Data and analytics in higher education: Opportunities and challenges. British journal of educational technology. 2015 Sep 1;46(5):904-20.

  3. Pusic M, Pecaric M, Boutis K. How much practice is enough? Using learning curves to assess the deliberate practice of radiograph interpretation. Academic Medicine. 2011 Jun 1;86(6):731-6.

  4. Chan T, Sebok‐Syer S, Thoma B, Wise A, Sherbino J, Pusic M. Learning Analytics in Medical Education Assessment: The Past, the Present, and the Future. AEM Education and Training. 2018 Apr;2(2):178-87.




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