iStock_000017197781_FullUse data mining to reduce the school dropout rate.

Demographical data, test results and disciplinary measures are some examples of variables used to predict the results for certain courses or even the students’ overall performance. This data can then be used to predict the risk of dropping out, the probability of completing a diploma in the expected time or the probability of a student reapplying.

Advantages:

  • Keep your reputation by maintaining high registration and graduate rate
  • Optimize intervention strategies with limited budgets by applying programs that have a higher propensity for success

Typical organizations that would use these analyses:

  • Public and private schools
  • Vocational and secondary schools, CEGEPs and universities