Using Data Mining in Educational Administration: A Case Study on Improving School Attendance
Metadatos
Afficher la notice complèteEditorial
MDPI
Materia
Educational data mining Association rule mining Improving school attendance Persistent absenteeism
Date
2020-04Referencia bibliográfica
Moodley, R., Chiclana, F., Carter, J., & Caraffini, F. (2020). Using Data Mining in Educational Administration: A Case Study on Improving School Attendance. Applied Sciences, 10(9), 3116. [doi:10.3390/app10093116]
Résumé
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.