A BRIEF HISTORY OF STUDENT GROWTH
PROMISES FULFILLED & OPPORTUNITIES MISSED
Damian W Betebenner
National Center for the Improvement of Educational Assessment
CCSSO/NCSA Orlando, FL June 25th, 2019
dbetebenner@nciea.org @dbetebenner
My Background
• Began investigating large scale longitudinal analyses in 1999 as a
graduate student at the University of Colorado, Boulder.
• Investigated/replicated EVAAS and other VAMs, Markov-chain/
transition matrices, growth curve/HLM models in early 2000s.
• Developed Student Growth Percentile (SGP) methodology in
2005-2007 while a professor at Boston College.
• Joined the Center for Assessment in 2007 and over the last 12 years
have worked with over 40 states and several consortia and testing
companies on the calculation and use of student growth.
Promises Fulfilled
• All states have investigated and nearly every state has adopted/
utilized an individual student growth model.
• States and testing vendors are very interested in calculating student
growth in almost all contexts in which they have longitudinal student
achievement data.
• There is MUCH greater understanding of student growth amongst
state level personnel (far exceeding what academics know). State
level personnel, in general, know what they are talking about.
• States recognize that a vertical scale doesn’t solve all the growth
issues and are taking advantage of both norm- and criterion-
referenced growth.
• States recognize and are taking advantage of both norm- and
criterion-referenced growth.
Opportunities Missed (thus far)
• Broadly, we are much better at using data as a hammer than as a
flashlight.
• Student growth has primarily been used as part of state accountability
initiatives. For example, school and teacher evaluations.
• Student growth has, in general, not been used to investigate:
• Issues related to equity: For example, growth gaps between demographic
subgroups.
• Issues related to assessment bias: For example, test mode of administration
effects.
• Issues related to program evaluation: For example, investigating whether
programs or curricula are associated with exemplary student growth.
• Issues related to diagnosis of individual strengths/weaknesses.
• Policy makers don’t understand the implications of what growth-to-
standard analyses imply.
Growth Gaps
• The analysis of student growth can enable powerful discussions about
equal educational opportunity.
• Even after accounting for where students start, students from
disadvantaged subgroups demonstrate less academic growth than
students from advantaged subgroups.
• Median/mean SGPs for disadvantaged subgroups are almost always in
the mid to low 40s where as advantaged groups are usually in mid 50s.
• Using growth analyses to identify districts and schools with extreme
growth gaps or reverse growth gaps supports powerful discussions
about equity.
• Conversely, including demographic adjustments in growth analyses
themselves adjusts out these differences and sweeps the problem under
the rug.
Assessment Bias
• Regression based growth analyses (e.g. SGP) which utilize students’ prior
scores act like a propensity score based analysis.
• SGP analyses in the past have detected mode effects between paper and
pencil and computer administered tests that appeared inconsequential
when looked at using only current attainment.
• SGP analyses have also detected substantial differences in the growth of
subgroups when states have transitioned to different tests.
• Beyond accountability, disparate growth results can quickly and easily
highlight issues related to to the testing system itself — but it is rarely
used in this fashion.
Program Evaluation
• Again, regression based growth analyses (e.g. SGP) which utilize students’
prior scores act like a propensity score analysis.
• States, districts, schools often have local knowledge about student group
membership that can be used to quickly and easily investigate impact.
• A school district in MA noticed unusually low student growth amongst
4th graders. This district had K-3 schools followed by a transition to
4-6. The transition was likely impacting student growth.
• With growth results over multiple years, the impact of curricular
changes can be investigated to see whether they lead to increased
student growth.
Education is not the filling of a pail,
but the lighting of a fire.
William Butler Years
Gifted & Talented
• As the definition suggests, gifted & talented is often
associated with extraordinary levels of attainment.
• Gifted in the common parlance refers to students
whose pails are “full”.
• How do we square this definition within a growth
based view of the world. One that focuses on fire.
Explosive growth!
Advanced Reading
Move Up
Achievement
●● Target
DEMO Reading
● Scale Score
Keep Up
Catch Up ● Target
Proficient Target ●
● Growth
Level Percentiles
● Very High 81st − 99th
High 61st − 80th
Part Proficient Typical 40th − 60th
Low 20th − 39th
Very Low 1st − 19th
Unsatisfactory
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7
Scale Score 449 533 579 602
Achievement Level
Achievement Target
Unsatisfactory Part Proficient Part Proficient Proficient
Proficient (592) Proficient (620)/Advanced (661)
Achievement
Growth Percentile 69 85 74
Growth Level
Growth Target
High Very High High
Catch Up (60) Keep Up (76)/Move Up (99)
Growth
Demonstration: 2018−2019 Mathematics
Norm & Criterion Referenced Growth & Achievement
College Ready
Percentile Growth Trajectory to College Readiness
Growth to
Career/College 550
Scale Score
2018−2019 Achievement Percentile
Readiness
Not College Ready
SGP trajectories for
SGP trajectories for aa 3rd
3rd grade
grade student
student starting
starting from
from the
the Level
Level 1/Level
1/Level 22 cut.
cut.
Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 Grade 10
Damian Betebenner
dbetebenner@nciea.org
@dbetebenner
About this copy
A Brief History of Student Growth — CCSSO National Conference on Student Assessment, June 25, 2019.
This is an image-based copy of the original Keynote slides; builds and animations are flattened.