Using linked education administrative data to evaluate and extend traditional studies of school effects on student outcomes
Lead Research Organisation:
University of Bristol
Department Name: Education
Abstract
CONTEXT
School effectiveness researchers estimate individual school effects as a first step to identifying school policies and practices which might explain why some schools are more effective than others. The DfE estimates individual school effects to hold schools to account (Progress 8), to inform school inspections (Ofsted), to inform parents choosing schools (compare-school-performance.service.gov.uk), and to provide schools with information for self-improvement.
APPROACH
The standard approach is to use the NPD to fit school 'value-added' fixed or random effect linear regression models to student GCSE examination scores where student KS2 test scores and sociodemographics (age, gender, ethnicity, language, FSM, SEN, IDACI) are entered as covariates to attempt to adjust the resulting predicted school effects for school differences in the student body at intake which would otherwise bias the school comparisons.
TOPIC 1
We will use the Census 2011 student, household, and neighbourhood characteristics available in the Wave 1 GUIE data (2014/15 cohort) to extend the standard approach to make far richer adjustments for school differences in the student body at intake. We will study the importance of these additional adjustments and their impact on the predicted school effects and in doing so we will assess the adequacy or not of the standard approach to address the non-random assignment of students to schools.
TOPIC 2
We will use students' employment and earnings 1, 3, 5 and 10 years after graduation available in LEO to extend the standard approach to explore school differences on students' longer-term labour market outcomes. Specifically, we will change the dependent variable in the standard approach to different labour market outcomes and we will explore models with and without GCSE score entered as a covariate. We will study the resulting predicted school effects and how they change across the different outcomes to highlight the inequalities in the school system.
School effectiveness researchers estimate individual school effects as a first step to identifying school policies and practices which might explain why some schools are more effective than others. The DfE estimates individual school effects to hold schools to account (Progress 8), to inform school inspections (Ofsted), to inform parents choosing schools (compare-school-performance.service.gov.uk), and to provide schools with information for self-improvement.
APPROACH
The standard approach is to use the NPD to fit school 'value-added' fixed or random effect linear regression models to student GCSE examination scores where student KS2 test scores and sociodemographics (age, gender, ethnicity, language, FSM, SEN, IDACI) are entered as covariates to attempt to adjust the resulting predicted school effects for school differences in the student body at intake which would otherwise bias the school comparisons.
TOPIC 1
We will use the Census 2011 student, household, and neighbourhood characteristics available in the Wave 1 GUIE data (2014/15 cohort) to extend the standard approach to make far richer adjustments for school differences in the student body at intake. We will study the importance of these additional adjustments and their impact on the predicted school effects and in doing so we will assess the adequacy or not of the standard approach to address the non-random assignment of students to schools.
TOPIC 2
We will use students' employment and earnings 1, 3, 5 and 10 years after graduation available in LEO to extend the standard approach to explore school differences on students' longer-term labour market outcomes. Specifically, we will change the dependent variable in the standard approach to different labour market outcomes and we will explore models with and without GCSE score entered as a covariate. We will study the resulting predicted school effects and how they change across the different outcomes to highlight the inequalities in the school system.
Organisations
People |
ORCID iD |
| George Leckie (Primary Supervisor) | |
| Tomiris Gilazh (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| ES/P000630/1 | 01/10/2017 | 30/09/2027 | |||
| 2882727 | Studentship | ES/P000630/1 | 01/10/2023 | 30/09/2027 | Tomiris Gilazh |