Big Data in Education: New Efficiencies for Recruitment, Learning, and Retention of Students and Donors

Predictive analytics with Big Data in education will improve educational programs for students and fund-raising campaigns for donors ( Siegel, 2013 ). Research in both educational data mining (EDM) and data analytics (LA) continues to increase ( Siemens, 2013 ; Baker and Siemens, 2014 ). The key elements of recruitment, learning, and retention can be tracked and increased over time in both cases for administrators and donor development. A few early examples of Big Data programs in these key areas of formal education will be reviewed. The paradigms of educational psychology can inform the construction of systems that maximize “engagement.” Contemporary educational technology enables the personalization of education whether face to face or at a distance. More responsive evaluation systems will allow the school to demonstrate the effectiveness of its services. There is more opportunity for education as a sustainable enterprise with the implementation of Big Data, both locally and globally.