Types of School Value-Added Reports

Slides:



Advertisements
Similar presentations
C. D. Toliver AP Statistics
Advertisements

Hong Kong’s Changing Examination System 11 October 2008.
Introduction to Educational Statistics
Introduction to Value-Added Data Dr Robert Clark.
Quartiles + Box and Whisker Plots. Quartiles Step 1: Find the Median. This is called Q2, or the second quartile. Step 2: Split the first half into 2 equal.
FFT Data Analysis Project – Supporting Self Evaluation  Fischer Family Trust / Fischer Education Project Extracts may be reproduced for non commercial.
Statistics Used In Special Education
Working with one variable data. Spread Joaquin’s Tests Taran’s Tests: 76, 45, 83, 68, 64 67, 70, 70, 62, 62 What can you infer, justify and conclude about.
WEEK 2 ( SEPTEMBER 2013) Unit 1 Data and Technology.
12.4 – Measures of Position In some cases, the analysis of certain individual items in the data set is of more interest rather than the entire set. It.
Many times in statistical analysis, we do not know the TRUE mean of a population of interest. This is why we use sampling to be able to generalize the.
Using VAM Data to Determine Points (50 % of the Total) toward Unified Single Rating Draft Procedures 11/21/2012 DRAFT DOCUMENT.
1 Excursions in Modern Mathematics Sixth Edition Peter Tannenbaum.
SAT 10 (Stanford 10) 2013 Nakornpayap International School Presentation by Ms.Pooh.
Chapter 11 Descriptive Statistics Gay, Mills, and Airasian
Analyzing and Interpreting Quantitative Data
Thinking About Psychology: The Science of Mind and Behavior 2e Charles T. Blair-Broeker Randal M. Ernst.
Introduction to Value-Added Data Dr Robert Clark.
Percentiles and Box – and – Whisker Plots Measures of central tendency show us the spread of data. Mean and standard deviation are useful with every day.
Differential Effectiveness Report Estimates All Years Multi-Subject Estimate Table Multi-Subject Estimate Graph All Schools, Similar Intake, Same District.
3.3 – Percentiles & Box-and-Whisker Plots Mean and Standard Deviation deal with exact numbers to measure. Sometimes measuring position is important too.
AP Psychology September What is “Statistics”?  A common language for describing, organizing, and interpreting data  Aspects:  Distribution 
A tour of fundamental statistics introducing Basic Statistics.
4 th August 2008 (Monday) Release of HKCEE Results.
Descriptive Statistics Prepared by: Asma Qassim Al-jawarneh Ati Sardarinejad Reem Suliman Dr. Dr. Balakrishnan Muniandy PTPM-USM.
Dulwich College Beijing (I)GCSE Options Process. What are (I)GCSEs? The (International) General Certificate of Secondary Education Two year courses in.
Progress 8 – preparing for the new measure… Tuesday 23 rd September 2014.
Statistics: Mean, Median, Mode and Range Year 8 Advanced Maths class Statistics Lesson 2.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 CHEBYSHEV'S THEOREM For any set of data and for any number k, greater than one, the.
The Single-Sample t Test Chapter 9. The t Distributions >Distributions of Means When the Parameters Are Not Known >Using t distributions Estimating a.
Introduction to CEM Secondary Pre-16 Information Systems Nicola Forster & Neil Defty Secondary Systems Programme Managers London, June 2011.
Chapter 6: Analyzing and Interpreting Quantitative Data
CEM (NZ) Centre for Evaluation & Monitoring College of Education Dr John Boereboom Director Centre for Evaluation & Monitoring (CEM) University of Canterbury.
YEAR 9 OPTIONS INFORMATION EVENING 2nd December 2015
Statistics topics from both Math 1 and Math 2, both featured on the GHSGT.
Cumulative frequency Cumulative frequency graph
Standardized Testing. Basic Terminology Evaluation: a judgment Measurement: a number Assessment: procedure to gather information.
The value-added model: Multilevel Model. Currently available information for value-added measurement End of P6 AAI End of S5 HKCEE End of S7 HKALE S1-S5.
Statistics Josée L. Jarry, Ph.D., C.Psych. Introduction to Psychology Department of Psychology University of Toronto June 9, 2003.
CEM (NZ) Centre for Evaluation & Monitoring College of Education Dr John Boereboom Director Centre for Evaluation & Monitoring (CEM) University of Canterbury.
RAISEonline David Robinson & Martin Kaliszewski.
Data update Autumn Overview About the new targets progress attainment Raise On Line (ROL) data reports and analyses historic results future estimates.
Educational Research Descriptive Statistics Chapter th edition Chapter th edition Gay and Airasian.
Progress 8 The government will give every child an EXPECTED grade for every subject. VA is then the ACTUAL grade minus the EXPECTED grade. A pupil’s VA.
FFT Data Analysis Project Who wants to be in the top 1 percent?
A QUANTITATIVE RESEARCH PROJECT -
Analysing the Primary RAISE
Progress 8 and Attainment 8:
Box and Whiskers with Outliers
Who wants to be in the top 1 percent?
Attainment 8 & Progress 8 Mr Avoth – PVT.
AP Biology Intro to Statistics
Analyzing and Interpreting Quantitative Data
Shoe Sizes.
Options 2018.
Progress 8 and Attainment 8:
Progress 8: an explanation
Performance Measures 2016 and beyond
Introduction to Statistics
HEARTIEST CONGRATULATIONS! A LEVEL CLASS OF 2018!
Options 2019.
Ms. Saint-Paul A.P. Psychology
The MidYIS Test.
Myers Chapter 1 (F): Statistics in Psychological Research: Measures of Central Tendency A.P. Psychology.
Understanding Progress 8
HEARTIEST CONGRATULATIONS! A LEVEL CLASS OF 2018!
What Month Were You Born In?
Performance Measures 2016 and beyond
Review of 6th grade material to help with new Statistics unit
Tuesday.
Presentation transcript:

Types of School Value-Added Reports Differential Effectiveness Report Estimates All Years Multi-Subject Estimate Table Graph All Schools, Similar Intake, Same District Report

All Schools, Similar Intake & Same District Comparisons Report

Distribution of schools’ value-added estimate shown by a box-and-whisker plot School with the highest value-added 75 percentile The box encloses the estimates of middle 50% of schools median 25 percentile School with the lowest value-added

This school has value-added slightly above 75% of all schools

This school has value-added well above 75% of similar intake schools

This school has value-added above average among schools from the same district

Differential Effectiveness Report This School All Schools e.g. HKCEE e.g. AAI

Simple Regression Method: The concept of Residuals 200 above average value-added HK schools 7 HKCEE 78 100 average value-added 100 below average value-added 70 80 90 100 110 120 130 AAI

Multilevel Modelling Method: The concept of Residuals 200 value-added at student level above average value-added HK schools 7 School A value-added at school level HKCEE 78 100 average value-added 100 below average value-added 70 80 90 100 110 120 130 AAI

The absolute performance of school A in Chinese Language HKCEE 180 A 160 B 140 C 120 D 100 E 80 F 60 U 40 20 Grade A B C D E % 20 14.7 26 21.3 18

The value-added performance of school A in Chinese Language HKCEE 180 A 160 The School B 140 C 120 Below average value-added D 100 E 80 F 60 U 40 HK Schools 20 AAI 70 85 100 115 130 Grade A B C D E % 20 14.7 26 21.3 18

The absolute performance of school B in Chinese Language HKCEE 180 A 160 B 140 C 120 D 100 E 80 F 60 U 40 20 Grade A B C D E % 20 14.7 26 21.3 18

The value-added performance of school B in Chinese Language HKCEE 180 A HK Schools 160 The School B 140 C 120 Above average value-added D 100 E 80 F 60 U 40 20 AAI 70 130 85 100 115 Grade A B C D E % 20 14.7 26 21.3 18

The absolute performance of school C in Chinese Language HKCEE 180 A 160 B 140 C 120 D 100 E 80 F 60 U 40 20 Grade A B C D E % 20 14.7 26 21.3 18

The value-added performance of school C in Chinese Language HKCEE 180 A HK Schools 160 The School B 140 C Average value-added 120 D 100 E 80 F 60 U 40 20 AAI 70 130 85 100 115 Grade A B C D E % 20 14.7 26 21.3 18

The value-added performance in Mathematics HKCEE 2000 180 A HK Schools 160 The School B 140 C 120 Above average value-added D 100 E 80 F 60 U 40 20 AAI 70 130 85 100 115 Grade A B C D E % 18.4 14.2 25.5 24.8 17.1

The value-added performance in Mathematics HKCEE 2001 180 A HK Schools 160 The School B 140 C 120 Average value-added D 100 E 80 F 60 U 40 20 AAI 70 130 85 100 115 Grade A B C D E % 21 17.4 24.6 20.3 16.7

The value-added performance in Mathematics HKCEE 2002 180 A 160 The School B 140 C Below average value-added 120 D 100 E 80 F 60 U 40 HK Schools 20 AAI 70 85 100 115 130 Grade A B C D E % 20 14.7 26 21.3 18

Types of Differential Effectiveness Pre-Test Post-Test Figure 1 Figure 2 Figure 3 Schools are different in their value-added performance, but have no significant difference in promoting the academic performance of students of different abilities.

Types of Differential Effectiveness Pre-Test Post-Test Figure 4 Figure 5 Figure 6 Schools are different in their value-added performance but all are more effective in promoting the academic attainment of more able students

Types of Differential Effectiveness Pre-Test Post-Test Figure 7 Figure 8 Figure 9 Schools are different in their value-added performance but all are more effective in promoting the academic attainment of less able students

Estimates high estimate 95% confidence interval low

Estimates All Years Report Group of schools with similar value-added Data in tabular form Name/Group Value-Added Stanine Low Estimate High 2000 -9.56 -7.08 -4.59 1 2001 -4.02 -1.87 0.28 4 2002 -1.49 1.24 3.97 6 Enable comparison of value-added performance of a subject across the years

Stanine A stanine is a standardized score with a mean of 5 and a standard deviation of 2. They range from 1 to 9. There are two kinds of stanines, (a) School intake: To categorize schools into groups with a similar intake, the average AAI was calculated of all students in all schools at the S5 level and the average core 3 was calculated of all students in all schools at the S7 level. (b) School value-added estimates: To categorize schools into groups with similar value-added

× : stanine of a school stanine = 7 Normal distribution 1 2 3 4 5 6 7 8 9 stanine = 7 Similar intake Group × : stanine of a school Normal distribution (Converted from average AAI )

Multi-Subject Report Multi-Subject Estimate Table Multi-Subject Estimate Graph

Multi-Subject Estimate Table Low Value-added Estimate High Additional Mathematics -3.88 -0.69 2.51 Biology -5.22 -3.42 -1.61 Chemistry -7.1 -4.86 -2.62 Chinese History -8.78 -6.46 -4.13 Chinese Language -7.84 -5.59 -3.35 Computer Studies -4.02 -1.87 0.28 Economics -9.01 -6.59 -4.18 English Language (Syl B) -3.77 -1.97 -0.17 Mathematics -6.57 -4.26 -1.95 Physics -5.04 -2.58 -0.13    

Multi-Subject Estimate Table Subject Group N Subjects Offered N Subjects in Top 10% VA N Subjects in Top 50% VA Chinese Language Education 1 English Language Education Mathematics Education 2 Personal, Social and Humanities Education Science Education 3 Technology Education    

Multi-Subject Estimate Graph Value Added Score Additional Mathemathics Best 6 Biology Chemistry Chinese History Chinese Language Chinese Literature Computer Studies Core 3 English Language (Syl B) Geography History Mathematics Physics Religious Studies (B, C)

Both high and low estimates are positive Above average value-added

Both low and high estimates are negative Below average value-added

Cannot conclude that value-added is above average

Cannot conclude that value-added is below average

Check value-added estimates listed in Multi-Subject Table

Both low and high estimates are positive Subject Low Estimate High Additional Mathematics -0.84 1.67 4.18 Best 6 -1.88 0.02 1.93 Biology -3.82 -1.93 -0.04 Chemistry -4.33 -2.23 -0.13 Chinese History 3.83 6 Chinese Language -2.35 -0.47 1.41 Chinese Literature -0.81 1.43 3.67 Computer Studies 0.05 2.12 4.19 Core 3 -0.64 1.4 3.45 Economics -1.44 0.84 3.11 English Language 1.66 3.96 6.25 Geography -4.5 -2.55 -0.59 History -2.87 -0.56 1.75 Mathematics -0.74 1.39 3.52 Physics -3.06 1.78 Above average value-added

Check value-added estimates listed in Multi-Subject Table

Both low and high estimates are negative Subject Low Estimate High Additional Mathematics -0.84 1.67 4.18 Best 6 -1.88 0.02 1.93 Biology -3.82 -1.93 -0.04 Chemistry -4.33 -2.23 -0.13 Chinese History 3.83 6 Chinese Language -2.35 -0.47 1.41 Chinese Literature -0.81 1.43 3.67 Computer Studies 0.05 2.12 4.19 Core 3 -0.64 1.4 3.45 Economics -1.44 0.84 3.11 English Language 1.66 3.96 6.25 Geography -4.5 -2.55 -0.59 History -2.87 -0.56 1.75 Mathematics -0.74 1.39 3.52 Physics -3.06 1.78 Below average value-added