II. Student achievement adjusted
Measuring how well schools support the student/teacher relationship
in PDF format
Middle || Elementary
the Playing Field
If you took the raw achievement scores by district and sorted them high to low, you would
probably find that you had also roughly sorted by the median family income of each
district. Without the strong intervention of schools, students tend to achieve according
to their socio-economic backgrounds. This pattern is by no means peculiar to RI.
Schools with high concentrations of low-income or special needs children have always
complained about being unfairly compared to schools whose less challenged children perform
at high levels on standardized tests. The public tends to compare high-performing schools
with low-performing schools without considering differences in student characteristics. In
fact, poverty is the strongest predictor of student achievement, except for that student's
prior achievement. (Without a Universal Student Identifier system in place, RI is not able
to factor prior achievement into its research.)
In recent years educational researchers have begun building statistically generated models
which can calculate what results schools are likely to achieve when taking into
consideration the characteristics of their student body. For over 30 years, researchers
have known that the achievement results of different sets of students, such as those from
different schools, vary in association with several specific key factors, including:
- Poverty (by far the strongest predictor of student
achievement, with the exception of prior achievement)
- Non-English speaking background
- Educational background of the parents
- Special learning needs, and
- A minority/racial group identity
While individuals with one or more of these
characteristics can and do perform well on state assessments, the majority tend to perform
less well than children who do not have these characteristics. There are many reasons for
these historic patterns of achievement. They include such things as school expectations,
the availability of flexible grouping and different types of instruction, inadequate
funding and support to the schools these children attend, and the quality of social
services offered to students.
Statistical models make it possible to establish an achievement benchmark that
acknowledges the challenges that can affect children's readiness to learn. The models
adjust for certain student characteristics to look at the same achievement data through a
lens that filters out some of the students' challenges. This lens provides a different,
but newly uniform and, in some ways, more practical benchmark against which to measure
Critical note: Rhode Island's goal is for
all students to become proficient in all subjects. This computer generated model is not a
standard and performing as well or even better than similar students across the state is
only the begining of a journey towards full proficiency. Over time, as the schools
improve, the computer-generated ranges wil themselves rise.
RI's Value-Added Charts
Click here to download
and/or print this graph in PDF format.
The dark red number indicates
that the school's students performed above their counterparts statewide and the bold
black number indicates that the school's students performed below similar
students statewide. Regular type' indicates the school's students performed the same
as similar students statewide.
Colored and black dots with years indicate those schools
who in prior years performed consistently above the statistical projection acoss all
subtests and those schools who performed consistently below on all modeled subtests. Those
at either extremes of the list are indicated by a dot with the year this performance took
The question mark: Participation in the assessments is
expected to be 100% unless a child is specifically exempted by an Individual Education
Plan (IEP) or another valid, clearly defined reason such as prolonged illness. When a
school's participation rate falls below 80% of the eligible students, a question mark
appears on the bar indicating that the data might be unreliable because of the large
number of eligible students who did not take the test. (Next year, RIDE will further
tighten required participation rates since a set of alternative tests for special needs
children will be fully operational, making it possible to account for virtually every
child within the state's assessment system.)
Which schools appear to add
In these charts, all the numbers you see are expressed as percentages of each school's
children who met or exceeded the standard on each subtest. Again, 100% proficiency is the
standard for all children, but these charts give us an idea as to which schools are
helping more of their students including their challenged students to
progress toward the standard. Each subtest was modeled separately, showing how comparable
students statewide would be expected to perform on the subtest. The performance of these
comparable students (virtual students, if you will) is then compared with the school's
actual achievement. Schools whose students perform better than the comparable students
(especially over multiple years) are considered to be adding more value to their students'
Thus, in the "value-added" lists, you are looking at all RI schools separated by
level, in reverse chronological order high, middle and elementary sorted
according to the results of the modeling. Each school's individual modeling is represented
on the second field on the first page of each Information Works! school report.
The Rhode Island Model
For the specific elements involved in this year's statistical model, please consult the
Information Works! Users Guide. A technical brief about the design and building of the
modeling is available on the Information Works! home page
infoworks.ride.uri.edu. You can also obtain a hard copy through the Office of
Information Services and Research at the RI Department of Education.
schools are more helpful than others when dealing with similar populations
The value-added charts tell us that certain schools have probably assembled a variety of
strategies that are more successful at helping their children learn than others. The red
dots indicate what schools have been high-achieving over time. Spending a day in a
relatively successful school, observing teaching, learning, and communications strategies
can provide demonstrations of techniques that struggling schools might want to emulate.
Educators who have been part of SALT visiting teams will tell you that observing a school
for a week was arguably the best professional development they have ever had.
Similarly, all schools' SALT data is on-line, accessible through the Information Works!
home page. Those data will illuminate what practices might be helping successful schools.
Do teachers share more decision-making? Do students feel they have someone to talk to? Do
students have the opportunity to revise work that has not yet met standard? Do teachers
communicate high expectations? Are parents involved? Even without a visit, much
information about these schools is available.
While some schools might be having excellent luck with a math program or a reading
initiative, a good general statement about the higher-functioning schools is that the
teachers and students are more accessible to one another and more content passes between
them in a way that is retained. The conditions are such that teachers and students,
together, are more productive. Presumably, these schools are more supportive of the
student/teacher relationship than others.
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