School value-added models for multivariate academic and non-academic outcomes: exploring implications for performance monitoring and accountability

ABSTRACT

Education systems around the world increasingly rely on school value-added models to monitor school performance and hold schools to account. These models typically focus on a limited number of academic outcomes. We explore how the traditional multilevel modelling approach to school value-added models can be extended to simultaneously analyse multiple academic and non-academic outcomes and the implications of doing so for systems using student data to monitor schools and inform school accountability. We jointly model student attainment, absence, and exclusion data for schools in England. We find very different results across the three outcomes, in terms of the size and consistency of school effects, and the importance of adjusting for student and school characteristics. The results suggest the three outcomes are capturing fundamentally distinct aspects of school performance, all of which are therefore important for education systems to monitor and explore including in systems of school accountability.

KEYWORDS:

• School accountability
• value added
• multilevel model
• absenteeism
• exclusions

Acknowledgements

This work was produced using data from the Department for Education National Pupil Database, distributed by the Office for National Statistics (ONS), which is Crown Copyright. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Economic and Social Research Council under Grant number ES/R010285/1.

Notes on contributors

Lucy Prior

Lucy Prior is a Research Associate in Quantitative Methods in Education at the School of Education, University of Bristol, UK. Her research interests include multilevel modelling, school performance measures, league tables, health geography, and neighbourhood deprivation.

Harvey Goldstein

Harvey Goldstein was a Professor of Social Statistics at the School of Education, University of Bristol, UK. His research interests included the use of statistical modelling techniques in the construction and analysis of educational tests, educational (school) effectiveness, the methodology of multilevel modelling, and methods for handling missing data values and measurement errors using Bayesian modelling.

George Leckie

George Leckie is a Professor of Social Statistics and Co-director of the Centre for Multilevel Modelling at the School of Education, University of Bristol, UK. His methodological interests are in the development, application, and dissemination of multilevel and related models to analyse educational and other complex clustered and longitudinal data. His substantive interests focus on design, analysis, and communication issues surrounding school performance measures and league tables, especially the use of value-added models for estimating school effects on student achievement for accountability and choice purposes.