Research References
Babo, G., Tienken, C. H., & Gencarelli, M. A. (2014). Interim
testing, socio-economic status, and the odds of passing grade
8 state tests in New Jersey.
RMLE Online: Research in Middle Level Education, 38(3),
1–9.
https://eric.ed.gov/?id=EJ1047113
From the ERIC abstract: “A review of the literature
pertaining to the effect and influence of
commercially-prepared interim assessments in mathematics and
language arts literacy reveals a lack of quantitative data to
determine the value of these products for school reform. This
study examined the ability of commercially-prepared interim
pretest and posttest assessments in language arts literacy
(LAL) and math to predict student achievement on the
state-mandated summative assessment in those subjects.
Analyses were conducted using binary logistic regression
models. Data for this study included results from the
state-mandated grade 8 assessments (NJ ASK 8) for 291 eighth
grade students enrolled in two middle level schools located in
a suburban/urban central New Jersey community during the
2009-2010 academic school year. The findings suggest that REL
Southwest Ask A REL Response the predictive value of the
students’ pretest results is very similar to that of the
posttest results and call into question the efficacy of
implementing both interim pretests and posttests.”
Blanc, S., Christman, J. B., Liu, R., Mitchell, C., Travers,
E., & Bulkley, K. E. (2010). Learning to learn from data:
Benchmarks and instructional communities.
Peabody Journal of Education, 85(2), 205–225.
https://eric.ed.gov/?id=EJ883193. Retrieved from
https://www.researchgate.net/publication/248942488
From the ERIC abstract: “This article examines the use
of interim assessments in elementary schools in the School
District of Philadelphia. The article reports on the
qualitative component of a multimethod study about the use of
interim assessments in Philadelphia. The study used an
organizational learning framework to explore how schools can
best develop the capacity to utilize the potential benefits of
interim assessments. The qualitative analysis draws on data
from intensive fieldwork in 10 elementary schools and
interviews with district staff and others who worked with the
schools, as well as further in-depth case study analysis of 5
schools. This article examines how school leaders and grade
groups made sense of data provided through interim assessments
and how they were able to use these data to rethink
instructional practice. We found substantial evidence that
interim assessments have the potential to contribute to
instructional coherence and instructional improvement if they
are embedded in a robust feedback system. Such feedback
systems were not the norm in the schools in our study, and
their development requires skill, knowledge, and concerted
attention on the part of school leaders.”
Bulkley, K. E., Christman, J. B., Goertz, M. E., & Lawrence,
N. R. (2010). Building with benchmarks: The role of the
district in Philadelphia’s benchmark assessment system.
Peabody Journal of Education, 85(2), 186–204.
https://eric.ed.gov/?id=EJ883188. Retrieved from
https://www.researchgate.net/publication/233120636
From the ERIC abstract: “In recent years, interim
assessments have become an increasingly popular tool in
districts seeking to improve student learning and achievement.
Philadelphia has been at the forefront of this change,
implementing a set of Benchmark assessments aligned with its
Core Curriculum district-wide in 2004. In this article, we
examine the overall context for Benchmarks in Philadelphia,
the expectations district leaders had for the use of those
Benchmarks, the supports put in place to assist those in
schools in meeting those expectations, and the challenges
encountered in that implementation.”
Chojnacki, G., Eno, J., Liu, F., Meyers, C., Konstantopoulos,
S., Miller, S., & van der Ploeg, A. (2013, September).
Do interim assessments influence instructional practice in
year one? Evidence from Indiana elementary school
teachers.
Paper presented at the Society for Research on Educational
Effectiveness Fall 2013 Conference, Washington, District of
Columbia.
https://eric.ed.gov/?id=ED563059
From the ERIC abstract: “Recent work that has examined
the impact of what are variously called periodic, interim,
benchmark, or diagnostic assessments, typically administered
three or four times during a school year, has produced mixed
findings. For instance, one study reported small significant
effects in mathematics in grades 3-8, but not in reading
(Carlson et al., 2011). Other research however, has reported
significant effects on both mathematics and reading (Slavin et
al., 2011). Finally, a very recent study found no effects on
reading achievement in grades 4-5 (Cordray et al., 2012). This
study compares instructional practices of teachers in schools
that were randomly assigned to receive an interim assessment
tool with those of teachers in schools that did not receive
the tool. Using rich data collected at 16 time points during
the school year, the authors study teachers’ self-reported
instructional practices to determine whether teachers with
access to an interim assessment tool alter each of three
facets of instructional practice— scope and sequence of
content coverage, instructional level, and instructional
grouping— more than those without the tool. The research
questions are: (1) Do teachers with access to the interim
assessment change the scope and sequence of content, and/or
vary instructional difficulty level and grouping methods more
than those without? (2) Do variations in these teacher
practices respond to variations in student Acuity performance?
Researchers employ treatment vs. control comparisons to
explore whether teachers with the interim assessment
intervention engage in expected instructional practices more
than those without it. Results are reported from rich data on
teacher instructional practices generated at sixteen intervals
by teachers with and without access to a specific interim
assessment tool. Estimates provide no strong evidence that
teachers change the instructional practices measured here in
response to Acuity performance data. One possible reason for
these findings is that Acuity is not a unique intervention,
and a significant number of control teachers reported using
other interim assessment tools. Another possible explanation
for these results is that the relatively small sample of
teachers completing checklists harms the study’s power.
Finally, these results pertain to the first year of the
intervention, when teachers are likely still learning how to
use the assessment tool and integrate it into their
instructional practice. Future research should explore the
hypothesis that impacts on teacher practice grow over time as
teachers learn to use the assessment tool.”
Cordray, D., Pion, G., Brandt, C., Molefe, A., & Toby, M.
(2013).
The impact of the Measures of Academic Progress (MAP)
program on student reading achievement
(Final Report, NCEE 2013-4000). Washington, DC: U.S.
Department of Education, Institute of Education Services,
National Center for Education Evaluation and Regional
Assistance.
https://eric.ed.gov/?id=ED537982
From the ERIC abstract: “During the past decade, the
use of standardized benchmark measures to differentiate and
individualize instruction for students received renewed
attention from educators. Although teachers may use their own
assessments (tests, quizzes, homework, problem sets) for
monitoring learning, it is challenging for them to equate
performance on classroom measures with likely performance on
external measures, such as statewide tests or nationally
normed standardized tests. One of the most widely used
commercially available systems incorporating benchmark
assessment and training in differentiated instruction is the
Northwest Evaluation Association’s (NWEA) Measures of Academic
Progress (MAP) program. The MAP program includes: (1)
computer-adaptive assessments administered to students three
or four times a year; and (2) teacher training and access to
MAP resources on how to use data from these assessments to
differentiate instruction. MAP tests and training are
currently in use in nearly 20 percent of K-12 school districts
nationwide and more than a third of districts in the Midwest.
Although the technical merits and popularity of MAP
assessments have been widely referenced in
practitioner-oriented journals and teacher magazines, few
studies have investigated the effects of MAP or other
benchmark assessment programs on student outcomes. This study
was designed to address questions from Midwestern states and
districts about the extent to which benchmark assessment may
affect teachers’ differentiated instructional practices and
student achievement. Thirty-two elementary schools in five
districts in Illinois participated in a two-year randomized
controlled trial to assess the effectiveness of the MAP
program. Half the schools were randomly assigned to implement
the MAP program in grade 4, and the other half were randomly
assigned to implement MAP in grade 5. Schools assigned to
grade 4 treatment served as the grade 5 control condition, and
schools assigned to grade 5 treatment served as the grade 4
control. The results of the study indicate that the MAP
program was implemented with moderate fidelity but that MAP
teachers were not more likely than control group teachers to
have applied differentiated instructional practices in their
classes. Overall, the MAP program did not have a statistically
significant impact on students’ reading achievement in either
grade 4 or grade 5.”
Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E.,
Supovitz, J. A., & Wayman, J. C. (2009).
Using student achievement data to support instructional
decision making
(IES Practice Guide, NCEE 2009-4067). Washington, DC: U.S.
Department of Education, Institute of Education Sciences,
National Center for Education Evaluation and Regional
Assistance.
https://eric.ed.gov/?id=ED506645
From the ERIC abstract: “The purpose of this practice
guide is to help K-12 teachers and administrators use student
achievement data to make instructional decisions intended to
raise student achievement. The panel believes that the
responsibility for effective data use lies with district
leaders, school administrators, and classroom teachers and has
crafted the recommendations accordingly. This guide focuses on
how schools can make use of common assessment data to improve
teaching and learning. For the purpose of this guide, the
panel defined common assessments as those that are
administered in a routine, consistent manner by a state,
district, or school to measure students’ academic achievement.
These include: (1) annual statewide accountability tests such
as those required by No Child Left Behind; (2) commercially
produced tests—including interim assessments, benchmark
assessments, or early-grade reading assessments—administered
at multiple points throughout the school year to provide
feedback on student learning; (3) end-of-course tests
administered across schools or districts; and (4) interim
tests developed by districts or schools, such as quarterly
writing or mathematics prompts, as long as these are
administered consistently and routinely to provide information
that can be compared across classrooms or schools. This guide
includes five recommendations that the panel believes are a
priority to implement: (1) Make data part of an ongoing cycle
of instructional improvement; (2) Teach students to examine
their own data and set learning goals; (3) Establish a clear
vision for schoolwide data use; (4) Provide supports that
foster a data-driven culture within the school; and (5)
Develop and maintain a districtwide data system.”
Henderson, S., Petrosino, A., Guckenburg, S., & Hamilton, S.
(2007).
Measuring how benchmark assessments affect student
achievement
(Issues & Answers Report, REL 2007-039). Washington, DC: U.S.
Department of Education, Institute of Education Sciences,
National Center for Education Evaluation and Regional
Assistance, Regional Educational Laboratory Northeast &
Islands.
https://eric.ed.gov/?id=ED499792
From the ERIC abstract: “This report examines a
Massachusetts pilot program for quarterly benchmark exams in
middle-school mathematics, finding that program schools do not
show greater gains in student achievement after a year. But
that finding might reflect limited data rather than
ineffective benchmark assessments. Benchmark assessments are
used in many districts throughout the nation to raise student,
school, and district achievement and to meet the requirements
of the No Child Left Behind Act of 2001. This report details a
study using a quasi-experimental design to examine whether
schools using quarterly benchmark exams in middle-school
mathematics under a Massachusetts pilot program show greater
gains in student achievement than schools not in the program.
The following are appended: (1) Methodology; (2) Construction
of the Study Database; (3) Identification of Comparison
Schools; (4) Interrupted Time Series Analysis; and (5)
Massachusetts Curriculum Frameworks for Grade 8 Mathematics
(May 2004).”
Henderson, S., Petrosino, A., Guckenburg, S., & Hamilton, S.
(2008).
A second follow-up year for “Measuring how benchmark
assessments affect student achievement.” REL Technical
Brief
(REL 2008-002). Washington, DC: U.S. Department of Education,
Institute of Education Sciences, National Center for Education
Evaluation and Regional Assistance, Regional Educational
Laboratory Northeast & Islands.
https://eric.ed.gov/?id=ED501327
From the ERIC abstract: “This technical brief examines
whether, after two years of implementation, schools in
Massachusetts using quarterly benchmark exams aligned with
state standards in middle school mathematics showed greater
gains in student achievement than those not doing so. A
quasi-experimental design, using covariate matching and
comparative interrupted time-series techniques, was used to
assess school differences in changes in mathematics
performance between program and comparison schools. Following
up on an earlier report with just one year of
post-implementation data, the study found no significant
differences between schools using this practice and those not
doing so after two years. The brief summarizes findings from a
follow-up study to the Issues & Answers report, ‘Measuring How
Benchmark Assessments Affect Student Achievement. REL 2007-No.
039’ [ED499792]. The follow-up study adds another year of
post-implementation data to examine the impact of benchmark
assessments on grade 8 mathematics achievement, using the same
data sources, methods, and reporting as the original study.
The study examines whether, after two years of implementation,
schools in Massachusetts using quarterly benchmark exams
aligned with state standards in middle school mathematics
showed greater gains in student achievement than those not
doing so. A quasi-experimental design, using covariate
matching and comparative interrupted timeseries techniques,
was used to assess differences in changes in mathematics
performance between program and comparison schools. The
follow-up study finds no significant differences between
schools using this practice and those not doing so after two
years. Limitations include the lack of data on what benchmark
assessment practices comparison schools may be using, having
only 22 treatment and 44 comparison schools, and having only
two years of post-implementation data—perhaps still too few to
observe an impact from the intervention.”
Konstantopoulos, S., Li, W., Miller, S., & van der Ploeg, A.
(2015, March).
Effects of interim assessments on the achievement gap:
Evidence from an experiment.
Paper presented at the Society for Research on Educational
Effectiveness Spring 2015 Conference, Washington, District of
Columbia.
https://eric.ed.gov/?id=ED562166
From the ERIC abstract: “Motivated by the passage of
the No Child Left Behind (NCLB) Act, all states operate
accountability systems that measure and report school and
student performance annually. The purpose of this study is to
examine the effects of interim assessments on the achievement
gap. The authors examine the impact of interim assessments
throughout the distribution of student achievement with a
focus on the lower tail of the achievement distribution.
Specifically, they investigated the effects of two interim
assessment programs (i.e., ‘mCLASS’ and ‘Acuity’) on
mathematics and reading achievement for high- median- and
low-achievers. They use data from a large-scale experiment
conducted in the state of Indiana in the 2009-2010 school
year. Quantile regression is used to analyze student data. The
study was a large-scale experiment conducted in Indiana during
the 2009-2010 academic year and included K-8 public schools
that had volunteered to participate in the intervention in the
spring of 2009. From a stratified (by school urbanicity) pool
of 116 schools the authors randomly selected 70 schools. Ten
of the 70 schools had used one or both assessment programs the
prior year and were excluded from the pool. Two other schools
closed and another school did not provide any student data.
Thus, the final sample included 57 schools, 35 in treatment
and 22 in control condition. Overall, nearly 20,000 students
participated in the study during the 2009-2010 school year.
The design was a two-level cluster randomized design. Students
were nested within schools, and schools were nested within
treatment and control conditions. Schools were randomly
assigned to a treatment (interim assessment) or a control
condition. The schools in the treatment condition received
‘mCLASS’ and ‘Acuity’, and the training associated with each
program. The control schools operated under business-as-usual
conditions. Overall, the findings suggest that the treatment
effect was positive, but not consistently significant across
all grades. Significant treatment estimates were observed in
the grade 3-8 analysis in mathematics. The estimates were
typically larger for low-achievers and in some cases
significant. These results are consistent in terms of the sign
of the effect (i.e., positive), but inconsistent in terms of
statistical significance. The authors observed positive,
statistically significant effects for grades 3-8 especially in
mathematics. It seems that ‘Acuity’ affected mathematics and
reading achievement positively and in some instances
considerably in grades 3-6.”
Pereira, M., & Tienken, C. (2012). An evaluation of the
influence of interim assessments on grade 8 student
achievement in mathematics and language arts.
International Journal of Educational Leadership
Preparation, 7(3), 1–13.
https://eric.ed.gov/?id=EJ997471
From the ERIC abstract: “A review of the literature
pertaining to the effect and influence that interim
assessments have on student achievement lacks quantitative
data to determine the efficiency of their use in the classroom
as a school reform tool. This study examined the strength and
the direction of the relationships between interim pre and
posttest assessments in language arts and mathematics in Grade
8 and student achievement on the New Jersey Grade 8 state
standardized tests in those subjects. Analyses were conducted
using simultaneous multiple regression models. All student
data explored in this study pertained to 670 students in Grade
8 enrolled in four middle schools located in a suburban/urban
central New Jersey community during the 2009-2010 academic
school year. The results of the study revealed each school
produced a combination of site specific results and the
interim pretests accounted for the same or almost the same
amount of variance in state test scores as the interim
posttests.”
Perie, M., Marion, S., & Gong, B. (2009). Moving toward a
comprehensive assessment system: A framework for considering
interim assessments.
Educational Measurement: Issues and Practice, 28(3),
5–13.
https://eric.ed.gov/?id=EJ853799. Retrieved from
https://www.nciea.org/sites/default/files/inline-files/Defining%20Interim_PerieMarionGong2009.pdf
From the ERIC abstract: “Local assessment systems are
being marketed as formative, benchmark, predictive, and a host
of other terms. Many so-called formative assessments are not
at all similar to the types of assessments and strategies
studied by Black and Wiliam (1998) but instead are interim
assessments. In this article, we clarify the definition and
uses of interim assessments and argue that they can be an
important piece of a comprehensive assessment system that
includes formative, interim, and summative assessments.
Interim assessments are given on a larger scale than formative
assessments, have less flexibility, and are aggregated to the
school or district level to help inform policy. Interim
assessments are driven by their purpose, which fall into the
categories of instructional, evaluative, or predictive. Our
intent is to provide a specific definition for these ‘interim
assessments’ and to develop a framework that district and
state leaders can use to evaluate these systems for purchase
or development. The discussion lays out some concerns with the
current state of these assessments as well as hopes for future
directions and suggestions for further research.”
West, M. R., Morton, B. A., & Herlihy, C. M. (2016).
Achievement Network’s Investing in Innovation expansion:
Impacts on educator practice and student achievement.
Cambridge, MA: Center for Education Policy Research, Harvard
University.
https://eric.ed.gov/?id=ED565458
From the ERIC abstract: “Data-based instructional
programs have proliferated in American schools despite limited
evidence of their effectiveness in improving educator practice
and raising student achievement. We report results from a
two-year schoolrandomized evaluation of the Achievement
Network (ANet), a program providing schools with
standards-aligned interim assessments and intensive supports
for instructional data use. Survey data show that ANet
increased teacher satisfaction with the timeliness and clarity
of the data they receive and available supports for
instructional data-use and caused them to review and use
interim assessment data more often. ANet did not, however,
affect their confidence in data use or how frequently they
differentiated instruction. Student impact estimates show no
overall effect on student achievement in English language arts
or mathematics. Despite the lack program effects on student
achievement, we find that achievement is positively correlated
with our survey-based measures of teacher perceptions and
practices around instructional data use. Exploratory analyses
suggest that the success of ANet in improving teacher practice
and student achievement varies with the pre-existing capacity
of schools to engage in data-based instruction. Schools rated
by program staff as having a high level of readiness to
implement the intervention prior to random assignment
experienced positive impacts on student achievement, while
those rated as a having a low level of readiness experienced
negative impacts.”
What Works Clearinghouse. (2015).
WWC review of the report
“The impact of Indiana’s system of interim assessments on
mathematics and reading”
(What Works Clearinghouse Single Study Review). Washington,
DC: U.S. Department of Education, Institute of Education
Sciences.
https://eric.ed.gov/?id=ED553423
From the ERIC abstract: “The study, ‘The Impact of
Indiana’s System of Interim Assessments on Mathematics and
Reading,’ examined the effects of using Diagnostic Assessment
Tools (DAT) on mathematics and reading outcomes for students
in 59 Indiana schools during the 2009-10 academic year. DAT
consists of interim assessment tools—Wireless Generation’s
mCLASS for students in grades K-2 and CTB/McGrawHill’s Acuity
for students in grades 3-8-modified to align with Indiana’s
state assessments. The goal is for teachers to use the
assessment results to tailor instruction to students’ needs.
After random assignment, schools in the intervention group
received DAT, and schools in the comparison group did not
receive the assessment tools or associated training. The study
is a well-executed randomized controlled trial with low sample
attrition. A subset of the analyses described in the study
meets WWC group design standards without reservations. The
study authors found, and the WWC confirmed, that the use of
DAT did not have a statistically significant impact on general
mathematics achievement or reading achievement for the full
sample of students in grades K-8, but that the use of DAT did
have statistically significant positive effects for grades 5
and 6 in mathematics achievement and grades 3-5 in reading
achievement.”
REL Southwest note: WWC rating of the study reviewed:
Meets Evidence Standards without Reservations.
Wilcox, K. C., Gregory, K., & Yu, L. (2017). Connecting the
dots for English language learners: How odds-beating
elementary school educators monitor and use student
performance data.
Journal for Leadership and Instruction, 16(1), 37–43.
https://eric.ed.gov/?id=EJ1159864
From the ERIC abstract: “This article reports on
findings from a multiple case study investigating the nature
of educators’ approaches toward monitoring English language
learners’ (ELLs) performance and using data to improve
instruction and apply appropriate interventions. Six New York
elementary schools where ELLs’ performance was better than
predicted (i.e. odds-beating) based on student assessment data
were studied. The analysis revealed that several strategies
were common among the schools studied and were associated with
the schools’ better ELL performance outcomes. These include:
1) connecting instruction and interventions to ‘real time’
data based on multiple measures of student performance
including benchmark and formative assessments; 2)
communicating performance via technology among teachers and
with family members and legal guardians; 3) collaborating
through routines among teaching and support staff as well as
school and district leaders. Implications for district and
school leaders and teachers are discussed. Implications for
district and school leaders as well as teachers and other
instructional specialists are offered.”
Additional Organizations to Consult
Center for Assessment –
https://www.nciea.org/
From the website: “Comprehensive and balanced
assessment systems are the subject of current technical and
policy conversations, but designing effective and efficient
systems can be fraught with major obstacles. Center
professionals work with states and districts to first help
identify highest priority uses and outline a Theory of Action.
They then design and implement an assessment solution that may
include formative, interim, and/or largescale summative
assessments, to meet the identified needs. In addition to
their assessment expertise in general, Center professionals
are recognized as national leaders in assessment design for
students with significant cognitive disabilities and English
language learners. The Center is also a leader in designing
innovative assessment system to support educational reforms.”
Smarter Balanced Assessment Consortium –
http://smarterbalanced.org
From the website: “Smarter Balanced is a public agency
currently supported by its members. Through the work of
thousands of educators, we created an online assessment system
aligned to the Common Core State Standards (CCSS), as well as
tools for educators to improve teaching and learning. Smarter
Balanced is housed at the University of California Santa Cruz
Silicon Valley Extension.
Our work is guided by the belief that a high-quality
assessment system can provide information and tools for
teachers and schools to improve instruction and help students
succeed—regardless of disability, language, or subgroup.
We involve experienced educators, researchers, state and local
policymakers, and community groups working together in a
transparent and consensus-driven process.”
The Center on Standards and Assessment Implementation (CSAI) –
https://www.csai-online.org
From the website: “The nation faces an unprecedented
education challenge as nearly all of our states work to
implement new and rigorous college and career readiness
standards and the innovative assessments designed to measure
student learning against these standards. The Center on
Standards and Assessment Implementation (CSAI) is a federally
funded national center charged with focusing research- and
evidence-based technical assistance to increase states’
capacity to support their districts and schools in this
implementation effort.
CSAI’s theory of action begins with the new college and career
readiness standards that provide the framework for classroom
instruction and student learning. Research and best practice
have shown us that the degree to which there is coherence and
alignment among the standards, curricular materials, and
instructional strategies used is directly correlated to
opportunities for student learning.
The standards also provide the foundation for developing
meaningful and effective assessment. The alignment between the
standards and assessments is key in determining to whom the
assessments are administered and how the data are used. Issues
of technical adequacy, including validity (content, construct,
predictive, consequential), reliability (measurement
precision, stability/consistency, scoring), and fairness (with
implications for diverse student populations), are critical to
consider in developing, identifying, or evaluating diagnostic,
interim, benchmark, and summative assessments. This is
especially true as student achievement data is increasingly
used as a metric for accountability at the teacher, school,
and district levels.
As seen in our theory of action model, there is not only
alignment among curriculum and instruction and assessment, but
also a continuous feedback loop among the three, as each
informs the others to provide a valid and accurate measure of
student learning.
Although CSAI does not work directly in classrooms, we apply
this model through the lens of supporting the needs of our
diverse learning population at the center of our work. This is
reflected in the research, technical assistance, and support
that is needed at the classroom, school, district, and state
levels of decision-making. Our aim is to focus on building
capacity, at all levels, in the development of balanced,
coherent, and efficient systems of teaching and learning.”
