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Using CEM Data for Self-Evaluation and Improvement. Running Your School on Data 7 th June 2011. Peter.Hendry@cem.dur.ac.uk. Running your school on data. CEM data includes: School profile bands Baseline test acquired ability data, inc. IPRs Predictive data inc. chances graphs
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Using CEM Data for Self-Evaluation and Improvement Running Your School on Data 7th June 2011 Peter.Hendry@cem.dur.ac.uk
Running your school on data CEM data includes: • School profile bands • Baseline test acquired ability data, inc. IPRs • Predictive data inc. chances graphs • Value-added data • Attitudinal data • Curriculum assessments (Insight) • Software programmes (PARIS) with databases
So much data................................! Some key questions: • What data is needed? (What data is not needed?) 2. And for Whom is the data ? 3. What does the data mean? (What does the data not mean?)
1. What data do I need? A key first step! e.g. using MidYIS GCSE predictive data for target setting • Point and/or grade predictions? (e.g. 5.8/grade B) • Based on whole cohort? • Based on the 75th percentile? • Based on prior value-added? • The chances graphs?
Discussion: setting the targets........... • From your perspective, assess the merit of each type of predictive data and the associated chances graphs • Which type of predictive data would you use to set the targets, and why? • Would your students be involved as part of the target setting process? • Would parents be informed about the process and outcome? • How would you ensure that HoDs were involved to ensure overview the process?
2. CEM data: who is it for? For example: • SMT/SLT: summary data, attitudinal • HoDs: Subject VAD, predictive data • Subject teachers: • FormTutors: • Head of Learning/Year/House: • Parents: • Pupils: and not forgetting: • Governors: • Media:
3. What does the data mean? e.g. value-added data: • The difference between raw and standardised residuals • The use of confidence limits to distinguish between average and statistically significant data, and to allow for small entry subjects • Can ‘zero’ or even ‘negative value-added’ be acceptable?
Raw residual Bar chart (MIDYIS and YELLIS only)
Standardised Residual Bar Chart 99.7% confidence limit 95% confidence limit ANY VALUE IN THE INNER SHADED AREA IS CONSIDERED TO BE AVERAGE VALUE ADDED
Raw residual Bar chart (MIDYIS and YELLIS only)
Standardised Residual Bar Chart 99.7% confidence limit 95% confidence limit ANY VALUE IN THE INNER SHADED AREA IS CONSIDERED TO BE AVERAGE VALUE ADDED
Case study: Alis value-added data Four sets of VAD are available! From average GCSE baseline: • all Alis cohort • type of Institution • Syllabus From the baseline test • all Alis cohort
SPC Chart with confidence limits: WHOLE SCHOOL Institution All Alis Cohort: Syllabus
Using PARIS software: Baseline Test Whole School From your perspective, which set of VAD would you use for the different user groups? (Governors, HoDs, Media, Parents, SMT/SLT...)
A final thought.......... Is it possible to keep adding value at each key stage?
2010 A2 2009 A2
2009 2010
USE ONE YEARS DATA WITH CAUTION! • Better to use three years data as patterns over time are more significant.
CEM data is used for: • Teachers to help learners • Curriculum and staffing decisions • Target setting and monitoring pupil progress • Inspection evidence • Self-evaluation • Monitoring changes over time such as pupil ability intake profiles and VAD • Asking the question ‘can we do better?’ i.e. the data is used to aid and to support professional judgement
with due consideration to: • Ethos and tradition of ‘my’ institution • Accountability • Parental expectations • Staff training in use of, and ability to cope with, data (data overload) • Management of data: integrating the data into school procedures, storage, retrieval, distribution and access……policy? i.e. doing our best to help every pupil to at least achieve, if not exceed, their potential