Discovering Rules for Nursery Students to amplify nursery education in developing countries using Apriori Algorithm

Abstract

Over recent years there has been a rise on the number of students completing tertiary education in Bangladesh. With this development it was felt that now there is a need to reduce the dropout rate in education. As a result, we conducted a research where we worked on providing insights that would help to understand the possible causes of dropout from education. Since primary education is the starting point for every student, this research has been conducted on this part of education and used data obtained from Slovenia that were made during enrolling students in nursery. The reason for using data of an European country was to use their insights who were a part of a developed country, and use it to the benefit of a developing country like Bangladesh. The study was conducted using association rule mining where several mining rules were generated using Apriori algorithm. The rules obtained had a confidence of 0.95 and a support of 0.04.