1. Introduction to Alis
Dr Robert Clark
ALIS Project Manager

2. Ensuring Fairness

3. Principles of Fair Analysis :
Compare ‘Like’ with ‘Like’
Appropriate Baseline
Reflect Statistical Uncertainty

4. The Analysis

5. Linear Least Squares Regression.
Linear Least Squares Regression
Subject X
A / B C

6. Linear Least Squares Regression.
Linear Least Squares Regression
Subject X
-ve VA
+ve VA
Residuals
Regression Line (…Trend Line, Line of Best Fit)
Outcome = gradient x baseline + intercept
Correlation Coefficient (~ 0.7)

7. The position of the national trend line is of critical importance
Measuring Value-Added – An Example
National Trend
‘Average’ Student A B
-ve
Alf
Bob C
Subject A
Subject B
Result
+ve
Chris D E U
Low Ability
Average Ability
High Ability
Baseline Score
The position of the national trend line is of critical importance

8. Some Subjects are More Equal than Others….
Grade
>1 grade C
Photography
Sociology
English Lit D
Psychology
Maths
Physics
Latin E C B A A*
Average GCSE
Principle of Fair Analysis No1 : Compare ‘Like’ with ‘Like’

9. Some Subjects are More Equal than Others …
Performance varies between subjects, thus analysing and predicting each subject individually is essential.
e.g. Student with Average GCSE = 6.0
Subject Choices
Predicted Grades
Maths, Physics, Chemistry, Economics
C, C, C/D, C/D
Sociology, Communication Studies, Drama, Media
B, B/C, B/C, B/C

10. Standardisation of Residuals
(Raw) Residuals can be used to examine an individual’s performance
Standardised Residuals are used to compare performance of groups
Standardised Residuals are independent of year or qualification type
For a class, subject, department or whole institution the Average Standardised Residual is the ‘Value-Added Score’
Standardised Residual = Residual / Standard Deviation (National Sample)
When using Standardised Residuals then for an individual subject
where N = number of results in the group
(for combinations of subjects consult the relevant project)
95% Confidence Limit = 2.0 x Standard Error
99% Confidence Limit = 2.6 x Standard Error
99.7% Confidence Limit = 3.0 x Standard Error

11. Subjects Covered… A / AS Levels
Applied A / AS levels (including dual award)
International Baccalaureate
BTec Nationals (Diploma, Certificate, Award)
CACHE DCE
OCR Nationals
ifs Diploma / Certificate in Financial Studies
Limited pool of level 2 (BTec First)

12. How to Administer the Project

13. Submit a registration form (Y11 May onwards….)
We need this before we can process any data
We need this even if you are registering as part of a consortium
Choose Basic / Full (Basic + Attitudinal surveys) and whether you wish to do baseline test
Submit student details – ‘Registration Spreadsheet’ (Y12 Mid Sept onwards….)
This gives us student name details, GCSE scores and the subjects they are studying
We always need this even if the students are sitting a baseline test
Send spreadsheet once students are confirmed on courses (i.e. not first day of term….)
Organise baseline testing – ‘Adaptive Test’ (End Y11 June 15th onwards….)
This can happen before, at the same time as or after sending us the registration spreadsheet (2 above)
Student details appear in ‘Check List’ on web site
Early prediction are available for students with Adaptive Test scores as soon as they appear in the Check List. This function is removed one Alis has generated offical predictions (pdf reports).
Don’t forget to click ‘Testing Complete’ once you have finished testing your students.

14. Prediction Reports Generated
Prediction reports, Intake Profiles, Adaptive Test data (IPR)
Reports created after receipt of Registration Spreadsheet
Guaranteed turnaround 4 weeks
Normal deliverable turnaround 2 weeks
When adaptive test data is ready (‘Testing Complete’ clicked), repots are updated.
Maintain Data
Keep reports up to date by using the Subject Editor on the Alis+ secure website to add and remove students from subject registrations and request updated feedback
Submit Entries Data (Y12 & Y13 March / April)
For institutions offering A / AS options, submit EDI entries files to Alis
Entries data Matched and Check lists issued (Y12 & Y13 May - July)
These need to be completed to ensure complete matching of candidate numbers to names held by Alis to ensure all EDI exam results are successfully processed in August

15. Results Collection (Y12 & Y13 August)
Submit A / AS results to Alis via EDI Results Files
Submit Other quals (IB, BTEc etc) to Alis using results spreadsheet (can opt to submit A / AS data in spreadsheet as well instead of EDI files)
Submit results as soon after results day as possible
Preliminary VA Feedback (Beginning of September)
Preliminary feedback generated by 1st Monday in September. Prompt return of results in August leads to early feedback
Trend data not fixed, values may be subject to change
Definitive VA Feedback (End of September)
Trend data locked and feedback generated. Letter & CD sent to schools / colleges.
Maintain Data
Update results data (missing grades, withdrawals, remarks, appeals etc) using the Results Editor on the Alis+ secure website and request updated feedback.

16. Typical Timeline Y11 Sept Nov Jan March May July Oct Dec Feb April
June
Aug
Registration Form
15th
CABT
Early Preds
Prediction Reports (+Y13)
Sept
Nov
Jan
March
May
July
Oct
Dec
Feb
April
June
Aug
Y12
Registration Form
Entries Collection & Matching R
CABT (+ Early Preds)
Matching Checklists
Registration SSheet
Value Added Feedback
Sept
Nov
Jan
March
May
July
Oct
Dec
Feb
April
June
Aug
Y13
Results Collection
Entries Collection & Matching R
Matching Checklists
Value Added Feedback
Sept
Nov
Jan
March
May
July
Oct
Dec
Feb
April
June
Aug
Y14
Results Collection

17. Baseline Assessment

18. Choice of Baseline Why 2 Baselines ? Average GCSE Score
CABT (Computer Adaptive Baseline Test)
Why 2 Baselines ?

19. Why 2 Baselines ?
Average GCSE correlates very well to A-level / IB etc, but by itself is not sufficient….
What is a GCSE ?
Students without GCSE ?
Years out between GCSE & A-level ?
Reliability of GCSE ?
Prior Value-Added ?
Principle of Fair Analysis No2 : Appropriate Baseline

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

21. Appropriate Baseline
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 v.good GCSE scores through the school effort rather than their ability alone ?
How will this affect expectation of attainment in the Sixth Form ?
Can you add value at every Key Stage ?
Baseline testing provides a measure of ability that (to a large extent) is independent of the effect of prior treatment.

22. Computer Adaptive Baseline Test (CABT)
Test performed online – results automatically transmitted to CEM.
Minimal installation / setup required - if any.
Adaptive – difficulty of questions changes in relation to ability of student.
Efficient – no time wasted answering questions that are far too easy or difficult.
Wider range of ability
Less stressful on students – more enjoyable experience than paper test.
Less demanding invigilation.
Test designed to be completed in 1 hour or less.
No materials to courier
In 2010 / 2011 over 68,000 students sat this test in Alis
To try it out…

23. Understanding Your Students: Baseline & Predictive Feedback

24. Intake Profiles

25. Intake Profiles (Historical)

26. IPR... ? Studying : Maths Physics Chemistry Biology Banana, Brian
Full Alis 2009 Demo School (999)
Banana, Brian
IPR...
Studying :
Maths
Physics
Chemistry
Biology ?

27. Probability of achieving
Prediction Reports
Probability of achieving
each grade
Expected Grade

28. Which predicted grades are the most appropriate for this student ?

29. What is this Student’s ability ?
Predictions Based on GCSE
(7.0) B C
Predictions Based on Test
(106) C B D
What is this Student’s ability ?
What Grades should we expect her to get ?
If she gets C’s instead of B’s, is this a problem ?

30. Why is the predicted grade not always equal to the highest bar ?
Predicted (‘expected’) grade
Most likely grade

31. Prediction Reports
Subject Report

32. A2 vs AS predictions and the impact of the A* Grade

35. Baseline Data & Predictions
Worked Examples:
Baseline Data & Predictions

36. Refer to the Intake Data on the next 2 slides
For each school what deductions might you make ?
What implications are there (if any) for teaching & learning ?

37. School A

38. School B

39. Refer to the Y12 data on the next 2 slides.
What impact might there be on the pupil’s learning ?
What subjects would you be worried about them studying ?
Note : Non Verbal section includes Perceptual Speed and Accuracy, Pattern Matching, logical reasoning and dice folding

40. Y12 - Pupil D

41. Y12 – Pupil E

42. Refer to the data on the next 3 slides.
Does the data show any ‘warnings’ about future potential achievement?
Based only on the information provided, what would be realistic subject targets for the students, and why?

43. Student 1

44. Student 2

45. Student 3

46. Worked Examples:
Target Setting

47. Basing Targets on Prior VA – One Methodology from an Alis School
Discuss previous value added data with each HoD
Start with an agreed REALISTIC representative figure based, if available on previous (3 years ideally) of value added data
add to each pupil prediction, and convert to grade (i.e. in-built value added)
Discuss with students, using professional judgment and the chances graphs, adjust target grade
calculate the department’s target grades from the addition of individual pupil’s targets

50. Discussion
Assess the merits and concerns you may have with this value- added model of setting targets

51. Alis
Value Added Feedback

52. Principle of Fair Analysis No3 : Reflect Statistical Uncertainty
Burning Question :
What is my Value-Added Score ?
Better Question :
Is it Important ?
Principle of Fair Analysis No3 : Reflect Statistical Uncertainty

53. Value Added Feedback… SPC Chart
Year

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

55. A2-English Literature Statistical Process Control (SPC) Chart
Year

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

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

58. 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 ?

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

60. Attitudinal Surveys

61. Self Evaluation (Every Child Matters)
There is more to school / college than exams….
Student attitudes
Student Welfare & Safety
Non-academic activities
Support
Social and personal development
Self Evaluation (Every Child Matters)
Full ALIS

62. Attitude to Institution
I like school / college this year
I like the classes
I like the teachers / lecturers
I would advise others to do their studies here
In this school / college, you are treated like an adult
The general atmosphere is good for students
Response
Score
Not true at all 1
Not True 2
Not sure 3
Fairly true 4
Very true 5

63. Attitude to Subject I find it hard to get down to work in this subject
I find the work challenging
I like exams and tests in this subject
I look forward to lessons in this subject
I regret taking this subject
I think about this subject a lot, even in my spare time
I would advise others to take this subject here
Response
Score
Not true of me at all 1
Not really true of me 2
Occaisionally true of me 3
This is fairly true of me 4
This is very true of me 5

64. Use of Private Tutors
% used at least once a term

65. Extended Attitudes – Attitude to Institution

66. Extended Attitudes – Resources

67. Extended Attitudes
Aspirations

68. Extended Attitudes
Pastoral Care

69. Extended Attitudes
Extra Curricula

70. Teaching and Learning Processes
(In Class)

71. Teaching and Learning Processes
(Out of Class)

72. SEF Survey To try it out… www.intuproject.org/demos Extent of Bullying
Extent of Racism
Extent of Sectarianism
Healthy Lifestyles
How Well do Learner's Make a Positive Contribution to the Community
How Well do Learner's Prepare for Their Future Economic Well Being
Other Health and Safety Issues
School's/College's Action on Bullying
School's/College's Action on Racism
School's/College's Action on Sectarianism
School's/College's Action on Sexual Harassment
Spiritual, Moral, Emotional and Cultural Development
To try it out…

73. School’s / College’s Action on Sexual Harassment

74. Summary

75. Alis History : Alis began in 2003 (started life called COMBSE)
Developed in partnership with schools by professional educational researchers
After spreading locally in the North East, Alis grew rapidly nationwide, largely through decisions by individual schools and colleges to subscribe
Alis is part of CEM which is affiliated to the School of Education at Durham University.
Research by CEM acknowledged by Durham in contributing significantly to the international research reputation of the School of Education.
Alis – developed in an educational context, by educational professionals for use by educational professionals.

76. Alis Provides… Baseline Tests :
Alis Coverage :
Approx 1700 school / colleges anually
> 50% UK A-levels anually
A/AS; IB; BTec National; OCR National; Cache DCE
Developing BTec First; GCSE Resit
Alis Provides… Baseline Tests :
GCSE not always an appropriate or reliable measure of ability
GCSE Scores depend on KS4 value-added performance
Alternative baseline test available
Provides predictions and value-added analysis independent of performance at prior key stage

77. Alis Provides… Predictions :
Predictions targeted at the individual subject (on average, students with similar GCSE scores get different grades in different A-level subjects)
Predictions from GCSE and Alis baseline test (how reliable is GCSE as a measure of ability ? Does the student have GCSE’s ?)
Predictions at 50th and 75th percentile
Chances Data (what is the probability of achieving grades different to those predicted?)
Standardised Scores from the baseline tests including section breakdown (IPR Report) – what are the student’s strengths & weaknesses ?

78. Alis Provides… Value Added :
All VA scores are specific to the student and each individual subject
Reports at school, subject and student level.
Current and historical trend data
Three sets of reports available:-
Subject Level (Whole cohort)
Syllabus Level (Whole Cohort)
Subject Level (Specific to your school type)
VA available from GCSE and from the Alis baseline test
All data shown against appropriate confidence limits
Analysis available from beginning of September
Consortia / area / LA analysis available

79. Alis Provides… Attitudes :
In depth subject related attitudinal survey
In depth student welfare survey covering:
Extent of Bullying
Extent of Racism
Extent of Sectarianism
Healthy Lifestyles
How well do learners make a positive contribution to the community
How well do learners prepare for their future economic well being
School / College action on bullying
School / College action on racism
School / College action on sectarianism
School / College action on sexual harassment
Spiritual, moral, emotional and cultural development
Can provide evidence to use in Self Evaluation
To them out…

80. Alis data can be used: To support teaching and learning
School Band Profile Graphs
IPR Data
‘Predictive’ data for target setting and monitoring
Paris software for data analysis and on course monitoring
To aid target setting and monitoring
Use reliable predictive data (e.g. Alis data)
Use professional judgment, including knowledge of the student
Consider school/department expectations and ethos
Give consideration to previous value added data where it is available (e.g. Alis data)
For Value Added analysis
For Self Evaluation
Inset provision is available on any aspect of Alis to support any of the above issues.

81. Dr Robert Clark
Alis Project Manager