Using Data Mining in Educational Administration: A Case Study on Improving School Attendance

Raymond Moodley, Francisco Chiclana, Jenny Carter, Fabio Caraffini

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Pupil absenteeism remains a significant problem for schools across the globe with negative impacts on overall pupil performance being well-documented. Whilst all schools continue to emphasize good attendance, some schools still find it difficult to reach the required average attendance, which in the UK is 96%. A novel approach is proposed to help schools improve attendance that leverages the market target model, which is built on association rule mining and probability theory, to target sessions that are most impactful to overall poor attendance. Tests conducted at Willen Primary School, in Milton Keynes, UK, showed that significant improvements can be made to overall attendance, attendance in the target session, and persistent (chronic) absenteeism, through the use of this approach. The paper concludes by discussing school leadership, research implications, and highlights future work which includes the development of a software program that can be rolled-out to other schools.

Original languageEnglish
Article number3116
Number of pages20
JournalApplied Sciences
Issue number9
Early online date29 Apr 2020
Publication statusPublished - 1 May 2020


Dive into the research topics of 'Using Data Mining in Educational Administration: A Case Study on Improving School Attendance'. Together they form a unique fingerprint.

Cite this