Guide to Predictive Analytics in Education:

the benefits and practical applications

The concept of predictive analytics is quickly becoming a key driver of change within the education sector. The approach uses historical student data to create models that help forecast future problems or opportunities. Educational organisations can use these models to understand and improve both the student experience and performance. 

Although the data can seem complex, the process is simple.

This guide introduces predictive analytics, tackles common myths and explores big data analytics across education. We also consider:

  • the benefits in higher and further education
  • the tools for predictive analytics in education
  • the practical applications for your institution (including improving student outcomes, completion rates of apprenticeships, quality of education, supporting recruitment and enrolment, monitoring remote delivery, and identifying areas for efficiency savings)
  • how to prepare for the future of predictive analytics

"In a world of tightened resources, predictive analytics can be used to improve attendance, performance and enrolment."