School value-added models for multivariate academic and non-academic outcomes: A more rounded approach to using student data to inform school accountability

Education systems around the world increasingly rely on school value-added models to hold schools to account. These models typically focus on a limited number of academic outcomes, failing to recognise the broader range of non-academic student outcomes, attitudes and behaviours to which schools contribute. 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 thereby can potentially provide a more rounded approach to using student data to inform school accountability. We jointly model student attainment, absence and exclusion data for schools in England. We find 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, recommending the consideration of non-academic outcomes in systems of school accountability.

[1]  H. Goldstein,et al.  Variance partitioning in multilevel models for count data , 2019, 1911.06888.

[2]  The implications of Labour's plan to scrap Key Stage 2 tests for Progress 8 and secondary school accountability in England , 2019, 1911.06884.

[3]  Feyisa Demie.  The experience of Black Caribbean pupils in school exclusion in England , 2019, Educause Review.

[4]  H. Goldstein,et al.  The importance of adjusting for pupil background in school value‐added models: A study of Progress 8 and school accountability in England , 2019, British Educational Research Journal.

[5]  S. Machin,et al.  Autonomous Schools and Strategic Pupil Exclusion , 2018, The Economic Journal.

[6]  S. Thomas,et al.  Educational effectiveness in Chilean secondary education: comparing different ‘value added’ approaches to evaluate schools , 2016, Educational Assessment in Latin America.

[7]  Michael A. Gottfried.  Chronic Absenteeism in the Classroom Context: Effects on Achievement , 2019 .

[8]  Emma García,et al.  Student Absenteeism: Who Misses School and How Missing School Matters for Performance. , 2018 .

[9]  L. Liebenberg,et al.  The impact of school exclusion on later justice system involvement: investigating the experiences of male and female students , 2018, Educational Review.

[10]  E. Fransson,et al.  School effectiveness and truancy: a multilevel study of upper secondary schools in Stockholm , 2018, International Journal of Adolescence and Youth.

[11]  C. Parsons.  The Continuing School Exclusion Scandal in England , 2018, FORUM.

[12]  G. Leckie.  Avoiding Bias When Estimating the Consistency and Stability of Value-Added School Effects , 2018 .

[13]  Sharon O'donnell,et al.  What Impact Does Accountability Have on Curriculum, Standards and Engagement in Education? A Literature Review. , 2018 .

[14]  S. Zubrick,et al.  Associations between school absence and academic achievement: Do socioeconomics matter? , 2017 .

[15]  Harvey Goldstein,et al.  The evolution of school league tables in England 1992-2016: ‘contextual value-added’, ‘expected progress’ and ‘progress 8’ , 2017 .

[16]  George Leckie,et al.  R2MLwiN: A Package to Run MLwiN from within R , 2016 .

[17]  S. Thomas,et al.  The impact of student composition on schools’ value-added performance: a comparison of seven empirical studies , 2015 .

[18]  Gary N. Marks,et al.  The size, stability, and consistency of school effects: evidence from Victoria , 2015 .

[19]  David A. Green,et al.  School Punishment in the US and England: Divergent Frames and Responses , 2015 .

[20]  Carla Rampichini,et al.  Exploiting TIMSS & PIRLS combined data: multivariate multilevel modelling of student achievement , 2014 .

[21]  Jordan Farrar,et al.  The persistent effect of race and the promise of alternatives to suspension in school discipline outcomes , 2014 .

[22]  A. Amrein-Beardsley.  Rethinking Value-Added Models in Education: Critical Perspectives on Tests and Assessment-Based Accountability , 2014 .

[23]  C. Teddlie,et al.  Educational effectiveness research (EER): a state-of-the-art review , 2014 .

[24]  R. Catalano,et al.  Student and school factors associated with school suspension: A multilevel analysis of students in Victoria, Australia and Washington State, United States. , 2014, Children and youth services review.

[25]  Christopher M J Charlton,et al.  runmlwin : A Program to Run the MLwiN Multilevel Modeling Software from within Stata , 2013 .

[26]  David A. Klingbeil,et al.  Beyond Behavior: Multilevel Analysis of the Influence of Sociodemographics and School Characteristics on Students' Risk of Suspension , 2013 .

[27]  Christopher M J Charlton,et al.  runmlwin: A Program to Run the MLwiN Multilevel Modeling Software within , 2013 .

[28]  H. Nordahl,et al.  Adolescent school absenteeism: modelling social and individual risk factors. , 2012, Child and adolescent mental health.

[29]  M. Ehren,et al.  Strategic data use of schools in accountability systems , 2012 .

[30]  Harvey Goldstein,et al.  Measuring Success: league tables in the public sector , 2012 .

[31]  Anne West,et al.  High stakes testing, accountability, incentives and consequences in English schools , 2010 .

[32]  Michael A. Gottfried.  Excused Versus Unexcused: How Student Absences in Elementary School Affect Academic Achievement , 2009 .

[33]  H. Goldstein,et al.  The limitations of using school league tables to inform school choice , 2009 .

[34]  George Leckie,et al.  The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement , 2009 .

[35]  S. West,et al.  The Analysis of Count Data: A Gentle Introduction to Poisson Regression and Its Alternatives , 2009, Journal of personality assessment.

[36]  Harvey Goldstein,et al.  Modelling the effect of pupil mobility on school differences in educational achievement , 2007 .

[37]  Harvey Goldstein,et al.  Partitioning variation in multilevel models , 2002 .

[38]  Sheldon Rothman,et al.  School absence and student background factors: A multilevel analysis , 2001 .

[39]  H. Goldstein,et al.  The use of value added information in judging school performance , 2000 .

[40]  E. Smyth.  Pupil Performance, Absenteeism and School Drop-out: A Multi-dimensional Analysis , 1999 .

[41]  C. Teddlie,et al.  The International Handbook of School Effectiveness Research , 1999 .

[42]  Harvey Goldstein,et al.  Methods in School Effectiveness Research , 1997 .

[43]  Jaap Scheerens,et al.  The Foundations of Educational Effectiveness , 1997 .

[44]  P. Mortimore,et al.  Stability and Consistency in Secondary Schools’ Effects on Students’ GCSE Outcomes over Three Years∗ , 1997 .

[45]  K. Howell,et al.  Suspension and Exclusion Rates for Aboriginal Students in Western Australia , 1995, The Aboriginal Child at School.