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Introduction to Value-Added Data

Introduction to Value-Added Data. Dr Robert Clark. Theory and Stats bits…. . Measuring Value-Added – Terminology. Exam grade. - ve VA. + ve VA. Residuals. BASELINE SCORE. VA. Trend Line/Regression Line . A*. B. C. Aldwulf. Beowulf. Subject A. D. Result. Cuthbert. E.

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Introduction to Value-Added Data

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  1. Introduction to Value-Added Data Dr Robert Clark

  2. Theory and Stats bits…

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

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

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

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

  7. Value Added Charts Pre 16

  8. VA Score Performance above expectation Good Practice to Share ? Performance inline with expectation Performance below expectation Problem with Teaching & Learning ?

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

  10. Which subjects now cause most concern ?

  11. Business Studies

  12. Religious Studies

  13. Value Added Charts Post 16

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

  15. Subject Summary - Current Year Subject Summary - 3 Year Average

  16. A2-English Literature Statistical Process Control (SPC) Chart 2008 2009 2010 Year

  17. A2 – English Literature Student Level Residuals (SLR) Report Scatter Plot General Underachievement ?

  18. A2 – English Literature Student Level Residuals (SLR) Report Scatter Plot Too many U’s ?

  19. 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 ?

  20. 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 !

  21. Baseline Choice

  22. GCSE or Baseline Test ? • Do students with the same GCSE score from feeder schools with differing value-added have the same ability ? • How can you tell if a student has underachieved at GCSE and thus can you maximise their potential ? • Has a student got very good GCSE scores through the school effort rather than their ability alone ? • Does school GCSE Value-Added limit the ability to add value at KS5 ? • Can you add value at every Key Stage ? • How can you check for this ?

  23. Average GCSE = 6 Average GCSE = 6 Average GCSE = 6 The Effect of Prior Value Added Beyond Expectation +ve Value-Added In line with Expectation 0 Value-Added Below Expectation -ve Value-Added Do these 3 students all have the same ability ?

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

  25. National or School Type Specific ?

  26. Comparison to all schools Comparison to Independent Schools Only

  27. Comparison to FE Colleges Only Comparison to all schools

  28. 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 ?

  29. Thank You Robert Clark – robert.clark@cem.dur.ac.uk

  30. Definitions: • Residual – difference between thepoints 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 – averageof 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’

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