1. Introduction to Value-Added Data Robert Clark Neil Defty Nicola Forster

2. Theory and Stats bits…

3. . -ve VA +ve VA Trend Line/Regression Line Raw Residual Measuring Value-Added – Terminology Exam grade BASELINE SCORE

4. Measuring Value-Added – An Example Low AbilityAverage AbilityHigh Ability Baseline Score A* U B C D E F G Result Aldwulf Beowulf Cuthbert +ve (+ 2 grades) -ve (- 2 grades) National Trend ‘Average’ Student The position of the national trend line is of critical importance Subject A Subject B

5. Some Subjects are More Equal than Others…. A-Level >1 grade A*ABC A B C D E

6. Some Subjects are More Equal than Others…. BTec National Diploma BCE DDM DDD DMM MMM MMP MPP D PPP Average GCSE Score Grade

7. Some Subjects are More Equal than Others…. International Baccalaureate 4 5 6 7 CBAA* Average (I)GCSE Score Grade Biology Business and Management Chemistry Design Technology Economics English_A1 Film French_B Geography History Mathematics Music Philosophy Physics Psychology Spanish_B Theatre Arts Visual Arts

8. F E D C B A A* Test Score GCSE Grades Art & Design Biology Chemistry Economics English French Geography German History Ict Mathematics Media Studies Music Physical Education Physics Religious Studies Science (Double) Spanish Some Subjects are More Equal than Others…. GCSE

9. Definitions: Residual – difference between the points the student attains and points attained on average by students from the CEM cohort with a similar ability Standardised Residual – the residual adjusted to remove differences between qualification points scales and for statistical purposes Average Standardised Residual – this is the ‘Value Added Score’ for any group of results Subject VA – average of standardised residuals for all students’ results in the particular subject School VA – average of standardised residuals for all students’ results in all subjects for a school / college Confidence Limit – area of statistical uncertainity within which any variation from 0 is deemed ‘acceptable’ and outside of which could be deemed ‘important’

10. Burning Question : What is my Value-Added Score ? Better Question : Is it Important ?

11. SPC Chart 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Performance inline with expectation VA Score Performance below expectation Problem with Teaching & Learning ? Performance above expectation Good Practice to Share ?

12. Subject Summary Standardised Residual Graph

13. The Scatter Plot Baseline Score Grade Points Equivalent Look for Patterns… General Underachievement / over achievement ? Do any groups of students stand out ? – high ability vs low ability ? – male vs female ?

14. Other things to look for… Why did these students do so badly ? Why did this student do so well ? How did they do in their other subjects ?

15. Worked Example

17. Which Subjects Cause Most Concern ? Danger of Relying on Raw Residuals Without Confidence Limits

18. Which subjects now cause most concern ?

19. Business Studies

21. Religious Studies

22. Summary of Process Examine Subject Summary Determine ‘interesting’ (i.e. statistically significant) subjects Look at 3 year average as well as single year if available Look at trends in ‘Interesting Subjects’ Examine student data –Scatter graphs Identify students over / under achieving (student list or Paris) Any known issues ? Don’t forget to look at over achieving subjects as well as under achieving Phone / Email CEM when you need help understanding / interpreting the data / statistics !

23. Baseline Choice

24. Same School - Spot the Difference ? GCSE as Baseline Test as Baseline

25. GCSE as Baseline Test as Baseline

26. A2 Biology GCSE as Baseline Test as Baseline

27. A2 Biology GCSE as Baseline Test as Baseline Student A Student B

28. A2 Biology Student A BaselineBaseline Score GradePoints‘Predicted’ Points VA (Residual) GCSE7.8A120122.4-2.4 Test1.7A12090.629.4 Student B BaselineBaseline Score GradePoints‘Predicted’ Points VA (Residual) GCSE8.0A*140128.111.9 Test2.3A*140100.139.9 How well did these students perform ?

29. National or School Type Specific ?

30. Comparison to all schools Comparison to Independent Schools Only

31. Comparison to all schools Comparison to FE Colleges Only

32. Questions: → How does the unit of comparison used affect the Value-Added data and what implications does this have on your understanding of performance ? → Does this have implications for Self Evaluation ?

33. Thank You Robert Clark – robert.clark@cem.dur.ac.uk Neil Defty – neil.defty@cem.dur.ac.uk Nicola Forster – nicola.forster@cem.dur.ac.uk