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

Raymond Moodley Orcid Logo, Francisco Chiclana Orcid Logo, Jenny Carter, Fabio Caraffini Orcid Logo

Applied Sciences, Volume: 10, Issue: 9, Start page: 3116

Swansea University Author: Fabio Caraffini Orcid Logo

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DOI (Published version): 10.3390/app10093116

Abstract

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...

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Published in: Applied Sciences
ISSN: 2076-3417
Published: MDPI AG 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa60957
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Abstract: 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.
Keywords: educational data mining; association rule mining; improving school attendance; persistent absenteeism
College: College of Science
Funders: This research received no external funding.
Issue: 9
Start Page: 3116