Research References
Brown, R. S., & Coughlin, E. (2007).
The predictive validity of selected benchmark assessments used in the Mid-Atlantic
region
(Issues & Answers Report, REL 2007-No. 017). Washington, DC: U.S. Department
of Education, Institute of Education Sciences, Regional Educational Laboratory Mid-Atlantic.
https://eric.ed.gov/?id=ED499099
From the ERIC abstract: “This report examines the availability and quality of
predictive validity data for a selection of benchmark assessments identified by state
and district personnel as in use within Mid-Atlantic Region jurisdictions. Based
on a review of practices within the school districts in the region, this report details
the benchmark assessments being used, in which states and grade levels, and the technical
evidence available to support the use of these assessments for predictive purposes.
The report also summarizes the findings of conversations with test publishing company
personnel and of technical reports, administrative manuals, and similar materials.
The study investigates the evidence provided to establish a relationship between
district and state test scores, and between performance on district-administered
benchmark assessments and proficiency levels on state assessments. When particular
district benchmark assessments cover only a subset of state test content, the study
sought evidence of whether district tests correlate not only with overall performance
on the state test, but also with relevant subsections of the state test. While the
commonly used benchmark assessments in the Mid-Atlantic Region jurisdictions may
possess strong internal psychometric characteristics, the report finds that evidence
is generally lacking of their predictive validity with respect to the required state
or summative assessments. To provide the jurisdictions with additional information
on the predictive validity of the benchmark assessments currently used, further research
is needed linking these assessments and the state tests currently in use. Additional
research could help to develop the type of predictive validity evidence school districts
need to make informed decisions about which benchmark assessments correspond to state
assessment outcomes, increasing potential success of instructional decisions meant
to improve student learning as measured by state tests. The following are appended:
(1) Methodology; (2) Glossary; and (3) Detailed Findings of Benchmark Assessment
Analysis.”
Burchinal, M. (2018). Measuring early care and education quality.
Child Development Perspectives 12(1), 3–9.
https://onlinelibrary.wiley.com/doi/epdf/10.1111/cdep.12260
From the abstract: “High-quality early care and education (ECE) programs are
thought to increase opportunities for all children to succeed in school, but recent
findings call into question whether these programs affect children as anticipated.
In this article, I examine research relating the quality of ECE to children’s outcomes,
finding somewhat inconsistent and modest associations with widely used measures of
process and structural quality, and more consistent and stronger associations with
other dimensions of ECE such as curricula and type of ECE program. I discuss why
the associations between ECE quality and outcomes are so modest, including limited
children’s outcomes, psychometric issues with quality measures, and a need to revise
and expand measures of ECE quality. The evidence indicates that we need to focus
on the content of instruction and teaching practices, as well as the extent to which
teachers actively scaffold learning opportunities. We also need to continue to focus
on the quality of interactions between teachers and children, and on children’s access
to age-appropriate activities.”
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., et al. (2007). School readiness
and later achievement.
Developmental Psychology, 43(6), 1428–1446.
https://pdfs.semanticscholar.org/8041/de7a7646a08d06eef94e2fa75ccaecb650a0.pdf?_ga=2.28345077.898802666.1530834445-1776330897.1530834445
From the abstract: “Using 6 longitudinal data sets, the authors estimate links
between three key elements of school readiness—school-entry academic, attention,
and socioemotional skills—and later school reading and math achievement. In an effort
to isolate the effects of these school-entry skills, the authors ensured that most
of their regression models control for cognitive, attention, and socioemotional skills
measured prior to school entry, as well as a host of family background measures.
Across all 6 studies, the strongest predictors of later achievement are school-entry
math, reading, and attention skills. A meta-analysis of the results shows that early
math skills have the greatest predictive power, followed by reading and then attention
skills. By contrast, measures of socioemotional behaviors, including internalizing
and externalizing problems and social skills, were generally insignificant predictors
of later academic performance, even among children with relatively high levels of
problem behavior. Patterns of association were similar for boys and girls and for
children from high and low socioeconomic backgrounds.”
Halle, T., Vick Whittaker, J. E., & Anderson, R. (2010).
Quality in early childhood care and education settings: A compendium of measures,
second edition. Washington, DC: Child Trends.
https://www.acf.hhs.gov/sites/default/files/opre/complete_compendium_full.pdf
From the introduction: “Quality measures were originally developed for research
aimed at describing the settings in which children spend time and identifying the
characteristics of these environments that contribute to children’s development.
They were also developed to guide improvements in practice. Increasingly, however,
measures of quality are being used for further purposes. In particular, they are
being used to guide components of state policies. For example, many states are developing
Quality Initiatives and employing measures originally created for research or for
guiding improvement in practice for the new purpose of assigning quality ratings
to early care and education settings. States are also using these measures to monitor
change in quality over time.
The
Quality in Early Childhood Care and Education Settings: A Compendium of Measures,
Second Edition was compiled by Child Trends for the Office of Planning, Research
and Evaluation of the Administration for Children and Families, U.S. Department of
Health and Human Services, to provide a consistent framework with which to review
the existing measures of the quality of early care and education settings.”
Jordan, N. C., Glutting, J., Ramineni, C., & Watkins, M. W. (2010). Validating a number sense screening tool for use in kindergarten
and first grade: Prediction of mathematics proficiency in third grade.
School Psychology Review, 39(2), 181–195. Retrieved from
https://www.academia.edu/15608137/Validating_a_number_sense_screening_tool_for_use_in_kindergarten_and_first_grade_Prediction_of_mathematics_proficiency_in_third_grade
From the abstract: “Using a longitudinal design, children were given a brief
number sense screener (NSB) screener (N = 204) over six time points, from the beginning
of kindergarten to the middle of first grade. The NSB is based on research showing
the importance of number competence (number, number relations, and number operations)
for success in mathematics. Children's mathematics achievement on a validated high-stakes
state test was measured 3 years later, at the end of third grade. Test-retest reliability
estimates were obtained for the NSB. Two criterion groups were then formed on the
basis of the third-grade achievement test (children who met and who did not meet
mathematics standards). Diagnostic validity analyses for the NSB were completed using
repeated measures analyses of variance and receiver operator curve analyses. Results
from all analyses revealed that scores on the NSB in kindergarten and first grade
predicted mathematics proficiency in third grade. Areas under the receiver operator
curve indicated that the NSB has high diagnostic accuracy (areas under the receiver
operator curve = 0.78-0.88). Findings suggest that kindergarten and first-grade performance
on the NSB is meaningful for predicting which children experience later mathematics
difficulties.”
McFarland, J., Hussar, B., de Brey, C., Snyder, T., Wang, X., Wilkinson-Flicker, S., et al. (2017).
The condition of education 2017 (NCES 2017-144). Washington, DC: U.S. Department
of Education, Institute of Education Sciences, National Center for Education Statistics.
https://eric.ed.gov/?id=ED574257
From the ERIC abstract: “‘The Condition of Education 2017’ is a congressionally
mandated annual report summarizing the latest data on education in the United States.
This report is designed to help policymakers and the public monitor educational progress.
This year's report includes 50 indicators on topics ranging from prekindergarten
through postsecondary education, as well as labor force outcomes and international
comparisons. ‘The Condition’ includes an ‘At a Glance’ section, which allows readers
to quickly make comparisons within and across indicators, and a ‘Highlights’ section,
which captures a key finding or set of findings from each indicator. The report contains
a ‘Reader's Guide,’ a ‘Glossary,’ and a ‘Guide to Data Sources’ that provide additional
information to help place the indicators in context. In addition, each indicator
references the data tables that were used to produce the indicator, most of which
are in the ‘Digest of Education Statistics.’ In addition to the regularly updated
annual indicators, this year’s report highlights innovative data collections and
analyses from across the Center: (1) The first spotlight indicator examines the relationship
between student risk factors at kindergarten entry (poverty and low parent educational
attainment) and academic achievement in early elementary school; (2) The second spotlight
indicator draws on administrative data from the Center’s EDFacts data collection
and finds that 2.5 percent of students in U.S. public elementary and secondary schools
were reported as homeless in 2014–15; (3) The third spotlight indicator draws on
longitudinal data from the Beginning Postsecondary Students Study to examine the
rates at which first-time college students persist toward completion of a degree
or certificate; and (4) The fourth spotlight indicator examines how disability rates
for U.S. adults vary by educational attainment, finding that 16 percent of 25- to
64-year-olds who had not completed high school had one or more disabilities in 2015,
compared to 4 percent of those who had completed a bachelor’s degree and 3 percent
of those who had completed a master's or higher degree. In addition, two indicators
provide insights from the Center’s recent work on technology in education. The first
previews key findings from the Center’s upcoming report, ‘Student Access to Digital
Learning Resources Outside of the Classroom.’ The second presents findings from the
National Assessment of Educational Progress's 8th-grade Technology and Engineering
Literacy (TEL) assessment.”
Wolf, P. J., & Lasserre-Cortez, S. (2018).
An exploratory analysis of features of New Orleans charter schools associated with
student achievement growth (REL 2018-287). Washington, DC: U.S. Department
of Education, Institute of Education Sciences, Regional Educational Laboratory Southwest.
https://eric.ed.gov/?id=ED579168
From the ERIC abstract: “In the wake of Hurricane Katrina, the number of charter
schools in New Orleans has rapidly expanded. During the 2012/13 school year—the period
covered by this study—of the 85 public schools in New Orleans, 75 were chartered,
enrolling more than 84 percent of all public school students in the city in 92 different
school campuses. This study explored organizational, operational, and instructional
features of New Orleans charter schools serving grades 3-8 that are potential indicators
of student achievement growth in English language arts (ELA), math, and science.
The organizational characteristic of kindergarten provided as an entry grade was
associated with higher levels of [value-added measures] VAM on the ELA test. The
operational characteristic of an extended school year also was associated with higher
levels of ELA VAM. The instructional characteristics of a lower percentage of teachers
with graduate degrees, more experienced teachers, and a lower student/teacher ratio
were associated with higher levels of ELA VAM. The analysis revealed fewer potential
key indicators of charter school effectiveness regarding VAM in math and science.
The inclusion of kindergarten as an entry grade was the only school feature that
was statistically significant in its association with math VAM; schools with kindergarten
were correlated with higher math VAM scores. Having a lower student/teacher ratio
and fewer staff in student support roles were the only school features that were
statistically significant in their association with higher science VAM scores. None
of these associations between potential key indicators and math and science VAM scores
remained statistically significant when estimated using 2013/14 outcome data, indicating
that the results are not robust to such an additional analysis. Offering kindergarten
as an entry grade and having a lower teacher/student ratio were the only potential
key indicators with statistically significant associations with more than one VAM
outcome. Having kindergarten as an entry grade was positively associated with ELA
and math VAM. Having a lower teacher/student ratio was associated with higher ELA
and science VAM. Contains appendices.”