Opportunities and challenges in predictive modelling for student retention

Predictive modelling — the analysis of large data sets to predict future outcomes — remains a small but growing practice among higher education institutions as a means of identifying students who are at risk and putting in place targeted interventions to improve student retention and success. A survey of Canadian universities and colleges found that 36% of respondents used predictive modelling as a means of improving student retention and almost 40% indicated that they were considering doing so, according to a new report, Opportunities and Challenges in Predictive Modelling for Student Retention, published by the Higher Education Quality Council of Ontario.