The Big Picture
Student Growth Percentiles and Accountability
Future Directions
References
An Introduction to Student Growth Percentiles and the
SGP Package
Damian W. Betebenner
National Center for the Improvement of Educational Assessment
Dover, NH
Utah State Board of Education, Salt Lake City, Utah
January 10th, 2016
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
From a Paucity to a Plethora of Data
The Economist: The Data Deluge
Historical records of student achievement
Historical records of student demographics, teachers, schools,
educational programs, . . .
Stakeholder interest in an examination of this longitudinal data
Interest in examining student achievement over time (student
growth) derives from data availability.
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Describing Student Growth
Measuring student growth, even with a vertical scale, is not a simple
task.
Some believe a vertical scale simplifies the task of measuring
student growth.
Even with an interval (or ratio) scale, growth is not easy to interpret.
Consider, for example, height.
A child might grow 4 inches between ages 3 and 4.
4 inches is a well understood quantity.
The 4 inch increase becomes really meaningful only when understood
alongside the growth of other 3 to 4 year olds.
Student growth percentiles were developed to provide a normative
context for describing student growth.
Damian W. Betebenner An Introduction to SGPs
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The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Student Growth Percentiles
Should we be surprised with a child’s current achievement given their prior
achievement?
Given a student’s prior scale scores and the associated conditional
density, their current scale score corresponds to a percentile of that
conditional distribution.
This percentile is the student’s growth percentile.
Growth percentiles are closely related to estimating the probability of
observing a student’s current achievement taking account of their
past achievement:
Pr(Current Achievement |Past Achievement ).
As such, growth percentiles describe the rarity of a student’s current
achievement conditional upon their prior achievement.
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Student Growth Percentiles
Should we be surprised with a child’s current achievement given their
prior achievement?
Student growth percentiles answer this question.
Consider a low achieving student with 50th percentile growth and a
high achieving student with 50th percentile growth.
The low achieving student grew at a rate exceeding 50 percent of
similar students.
The high achieving student grew at a rate exceeding just 50 percent of
similar students.
The low achiever’s growth is probabilistically as rare as the high
achiever’s.
Equally rare does not mean equally good.
Judgments about the adequacy of student growth require external
criteria.
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Model for Student Growth Percentiles
Student growth percentiles are calculated using quantile regression
with B-spline smoothing, a generalized additive model.
Quantile regression is used to model the complete distribution of the
response variable (current achievement)
B-spline smoothing is uses to accommodate non-linearity and
heteroscedasticity of the data.
The model/method is descriptive and all about data fit—it’s a data
mining procedure.
The model quantifies distance = rate · time probabilistically.
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Model for Student Growth Percentiles
Conditional Decile Regression Curves Conditional Decile Regression Lines
2006−07 Math: Grade 5 versus 6 2006−07 Math: Grade 5 versus 6
1000 Unsatisfactory Partially Prof. 1000 Unsatisfactory Partially Prof.
Proficient Proficient
Partially Prof. Proficient Advanced Partially Prof. Proficient Advanced
Grade 6 Scale Score Grade 6 Scale Score
Grade 5 Scale Score Grade 5 Scale Score
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Software for Student Growth Percentiles
Student Growth Percentiles and Percentile Growth Trajectories are
calculated using the open source R Software
Environment [R Development Core Team, 2023] and the SGP
package [Betebenner et al., 2024]
In working with state departments of education, the goal is to build
local capacity so analyses can be performed and validated on their
own using software available and easily used by the state.
Colorado, Massachusetts, Indiana, Nevada, Arizona, Wisconsin,
Idaho, Washington, Hawaii, Georgia, West Virginia, Oregon, are
states (that I know of) who have state staff capable of generating the
student growth percentiles together with aggregations that follow
from their calculation.
State ownership/oversight of the SGP calculations has been a big
plus in terms of buy-in from the state, enhancing their ability to
explain and work with local stakeholders.
Damian W. Betebenner An Introduction to SGPs
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Software for Student Growth Percentiles
Creative Commons Share-and-Share Alike License:
Software is open source and developed on the GitHub collaborative
version control system:
https://github.com/CenterForAssessment/SGP
Source code for analyses of each state are version controlled on
GitHub for complete transparency. For example
https://github.com/CenterForAssessment/Colorado
Meta-data (e.g., names of achievement levels, CSEMs, ...) for state
assessment systems is housed within the package and
developed/maintained on GitHub:
https://github.com/CenterForAssessment/SGPstateData
Damian W. Betebenner An Introduction to SGPs
Student Growth Percentile Use
Extensive Use
Some Use
Investigating Use
The Data Revolution
The Big Picture
Describing Student Growth
Student Growth Percentiles and Accountability
Student Growth Percentiles
Future Directions
Model & Software for Student Growth Percentiles
References
Criterion Referenced Growth
Establishing growth-standards based upon growth-norms
The most common adequacy criterion are judging growth toward an
achievement goal (i.e., growth-to-standard).
Results from student growth percentile analyses can be used to
calculate percentile growth trajectories for each student.
These trajectories indicate what future rates of growth will lead to
and are used to make adequacy judgments.
This growth-to-standard approach was approved as part of
Colorado’s successful application to the Growth Model Pilot
Program.
Damian W. Betebenner An Introduction to SGPs
Advanced Reading
Achievement
DEMO Reading
● Scale Score
Proficient Growth
● Catch Up
Target
Catch Up ●● Level Percentiles
Target ●
Very High 81st − 99th
Part Proficient High 61st − 80th
● Typical 40th − 60th
Low 20th − 39th
Unsatisfactory
Very Low 1st − 19th
Grade 3 Grade 4 Grade 5
Scale Score 449 533
Achievement Level
Achievement Target
Unsatisfactory Part Proficient
Proficient (538) Proficient (562)
Achievement
Growth Percentile 69
Growth Level
Growth Target
High
Catch Up (75) Catch Up (76)
Growth
Billy Gonzales Wenning Arts Elementary School
How to interpret this student
growth & achievement report Mathematics
Advanced
Achievement
DEMO ● DEMO Mathematics
● Move Up
Scale Score
Scale Score ●
Target ●
Catch Up
Target
Keep Up ●
Growth
Target
Proficient ● Level Percentiles
DEMO Very High 81st − 99th
Achievement High 61st − 80th
Part Proficient
Levels Typical 40th − 60th
Low 20th − 39th
Unsatisfactory Very Low 1st − 19th
Student
Grade 3 Grade 4 Grade 5
Growth 2015−2016 2016−2017 2017−2018
Percentile Scale Score 438 447
Achievement Level
Achievement Target
Proficient Part Proficient
Proficient (482)/Advanced (503) Proficient (494)
Achievement
Growth Percentile 18
Catch Up/Keep Up Growth Level Very Low
Growth
Move Up/Stay Up Growth Target Keep Up (55)/Move Up (74) Catch Up (60)
Targets
Suggested Uses
Advanced Reading
Achievement
DEMO Reading
● Scale Score
● Review past growth to assess
student academic progress toward Proficient Growth
● Catch Up
DEMO achievement goals. Catch Up ●●
Target
Level Percentiles
Target ●
● Develop remediation or enrich− Very High 81st − 99th
ment plans based on rate of Part Proficient High 61st − 80th
growth needed to reach higher
DEMO achievement levels. ● Typical 40th − 60th
Low 20th − 39th
● Identify the rate of progress Unsatisfactory
Very Low 1st − 19th
needed in order to reach or
maintain proficient status
Grade 3 Grade 4 Grade 5
on the DEMO next year. 2015−2016 2016−2017 2017−2018
Scale Score 449 533
Achievement Level
Achievement Target
Unsatisfactory Part Proficient
Proficient (538) Proficient (562)
Achievement
Growth Percentile 69
Growth Level
Growth Target
High
Catch Up (75) Catch Up (76)
Growth
For more information please visit the Student Growth Percentiles Package (the SGP Package) at www.sgp.io or contact dbetebenner@nciea.org
Cooperatively developed by the SGP Package & the Center for Assessment, Inc. Distributed by the SGP Package.
Advanced Reading
Achievement
DEMO Reading
● Scale Score
Proficient Growth
● Catch Up
Target
Catch Up ●● Level Percentiles
Target ●
Very High 81st − 99th
Part Proficient High 61st − 80th
● Typical 40th − 60th
Low 20th − 39th
Unsatisfactory
Very Low 1st − 19th
Grade 3 Grade 4 Grade 5
Scale Score 449 533
Achievement Level
Achievement Target
Unsatisfactory Part Proficient
Proficient (538) Proficient (562)
Achievement
Growth Percentile 69
Growth Level
Growth Target
High
Catch Up (75) Catch Up (76)
Growth
Advanced Reading
Achievement
DEMO Reading
● Scale Score
Proficient Growth
● Catch Up
Target
Catch Up ●● Level Percentiles
Target ●
Very High 81st − 99th
Part Proficient High 61st − 80th
● Typical 40th − 60th
Low 20th − 39th
Unsatisfactory
Very Low 1st − 19th
Grade 3 Grade 4 Grade 5
Scale Score 449 533
Achievement Level
Achievement Target
Unsatisfactory Part Proficient
Proficient (538) Proficient (562)
Achievement
Growth Percentile 69
Growth Level
Growth Target
High
Catch Up (75) Catch Up (76)
Growth
Utah: 2017 Mathematics
Norm & Criterion Referenced Growth & Achievement
Percentile Growth Trajectory
Scale Score
2017 Achievement Percentile
SGP trajectories for a 3rd grade student starting from the Level 1/Level 2 cut.
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 EOCT EOCT EOCT
Mathematics Mathematics Mathematics Mathematics Mathematics Mathematics Sec Math I Sec Math II Sec Math III
Utah: 2017 Mathematics
Norm & Criterion Referenced Growth & Achievement
Percentile Growth Trajectory
Scale Score
2017 Achievement Percentile
SGP trajectories for a 3rd grade student starting from the Level 2/Level 3 cut.
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 EOCT EOCT EOCT
Mathematics Mathematics Mathematics Mathematics Mathematics Mathematics Sec Math I Sec Math II Sec Math III
Utah: 2017 ELA
Norm & Criterion Referenced Growth & Achievement
Percentile Growth Trajectory
Scale Score
2017 Achievement Percentile
SGP trajectories for a 3rd grade student starting from the Level 1/Level 2 cut.
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
Utah: 2017 ELA
Norm & Criterion Referenced Growth & Achievement
Percentile Growth Trajectory
Scale Score
2017 Achievement Percentile
SGP trajectories for a 3rd grade student starting from the Level 2/Level 3 cut.
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10 Grade 11
The Big Picture
Student Growth Percentiles and Accountability
School Accountability
Future Directions
References
Going from Students to Schools
It’s of interest to examine schools where students demonstrate, on
average, extraordinarily high and low student growth.
To summarize the student growth percentiles associated with a
school (or other grouping) calculate the median of the student
growth percentiles.
If students were randomly assigned to schools, expect to see a
median of 50.
Values greatly above or below 50 are of interest in identifying best
practices or providing extra support.
Examining growth with achievement sheds new light on school
performance.
Damian W. Betebenner An Introduction to SGPs
Utah School Performance
SAGE Growth & Achievement 2016 SAGE Mathematics
Higher Achievement Higher Achievement School Size
Lower Growth Higher Growth 50 Students
100 Students
2016 Percent at/above Proficient
250 Students
500 Students
Achievement
Summary Statistics
Correlation: 0.46
Correlation (N ≥ 10): 0.46
Lower Growth Higher Growth
Lower Achievement Lower Achievement
Growth 2016 Median Student Growth Percentile
Utah School Performance
SAGE Growth & Prior Achievement 2016 SAGE Mathematics
Higher Achievement Higher Achievement School Size
2015 Prior Percent at/above Proficient
Lower Growth Higher Growth 50 Students
100 Students
250 Students
500 Students
Achievement
Summary Statistics
Correlation: 0.23
Correlation (N ≥ 10): 0.23
Lower Growth Higher Growth
Lower Achievement Lower Achievement
Growth 2016 Median Student Growth Percentile
Utah School Performance
SAGE Growth & Achievement 2016 SAGE ELA
Higher Achievement Higher Achievement School Size
Lower Growth Higher Growth 50 Students
100 Students
2016 Percent at/above Proficient
250 Students
500 Students
Achievement
Summary Statistics
Correlation: 0.48
Correlation (N ≥ 10): 0.48
Lower Growth Higher Growth
Lower Achievement Lower Achievement
Growth 2016 Median Student Growth Percentile
Utah School Performance
SAGE Growth & Prior Achievement 2016 SAGE ELA
Higher Achievement Higher Achievement School Size
2015 Prior Percent at/above Proficient
Lower Growth Higher Growth 50 Students
100 Students
250 Students
500 Students
Achievement
Summary Statistics
Correlation: 0.24
Correlation (N ≥ 10): 0.24
Lower Growth Higher Growth
Lower Achievement Lower Achievement
Growth 2016 Median Student Growth Percentile
The Big Picture
Student Growth Percentiles and Accountability
Web 2.0 Technologies
Future Directions
References
Web 2.0: Data Visualization and Social Networking
The Colorado Department of Education and the Center for
Assessment have been working for the last two years on developing
next generation data visualization to accompany growth model data.
The goal: Transform conversations about education through active
engagement with data (i.e., evidence).
Our efforts have received tremendous interest and recognition:
Recognized by Adobe for innovative uses of their technology as an
Adobe Max Award finalist in October, 2009.
2010 NCME Award for Outstanding Dissemination of Educational
Measurement Concepts to the Public.
14 states signing MOUs to co-develop a cloud-based reporting
platform in a non-proprietary fashion.
Colorado recently devoted $2.5 million of stimulus funds to the
development efforts
Damian W. Betebenner An Introduction to SGPs
The Big Picture
Student Growth Percentiles and Accountability
Web 2.0 Technologies
Future Directions
References
The Decade of Data Visualization
Chart Wars http://infosthetics.com/archives/2010/01/
chart_wars_the_political_power_of_data_
visualization.html
Hans Rosling/Gapminder
http://www.youtube.com/watch?v=jbkSRLYSojo
Journalism in the Age of Data
http://datajournalism.stanford.edu/
Damian W. Betebenner An Introduction to SGPs
The Big Picture
Student Growth Percentiles and Accountability
Web 2.0 Technologies
Future Directions
References
Web 2.0: Data Visualization and Social Networking
With a collaborative spirit, with a collaborative platform where people can
upload data, explore data, compare solutions, discuss the results, build
consensus, we can engage passionate people, local communities, media
and this will raise–incredibly–the amount of people who can understand
what is going on.
And this would have fantastic outcomes: the engagement of people,
especially new generations; it would increase knowledge, unlock
statistics, improve transparency and accountability of public policies,
change culture, increase numeracy, and in the end, improve democracy
and welfare.
E. Giovannini, Chief Statistician, OECD. June 2007
Damian W. Betebenner An Introduction to SGPs
The Big Picture
Student Growth Percentiles and Accountability
Future Directions
References
References
Betebenner, D. W., Iwaarden, A. V., Domingue, B., and Shang, Y.
SGP: Student growth percentiles & percentile growth trajectories.
Available online complete with source code from https://sgp.io.
R Development Core Team (2023).
R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria.
Damian W. Betebenner An Introduction to SGPs
About this copy
An Introduction to Student Growth Percentiles and the SGP Package — Utah Department of Education, January 10, 2016.
This is an image-based copy of the original beamer slides; builds and animations are flattened.