Implementing a randomized controlled trial design, the present study investigated the effects of two types of accommodations, linguistic modification and a glossary, for English learners (ELs) taking a computer-based mathematics assessment. Process data including response time and clicks on glossary words were also examined to better interpret students’ interaction with the accommodations in the testing conditions. Regression and ANOVA analyses were performed with data from 513 students (189 ELs and 324 non-ELs) in Grade 9. No statistically significant accommodation effects were detected in this study. Process data revealed possible explanations (i.e., student engagement and glossary usage) for the nonsignificant results. Implications for future research on test accommodations for EL students are discussed.

English language learners (ELLs) perform significantly lower academically than their non-ELL peers. This performance-gap is mainly due to construct-irrelevant factors such as cultural bias and unnecessary linguistic complexity. To help reduce the impact of construct-irrelevant sources in the assessment of ELL students, accommodations should be used that (1) are effective in making assessments more accessible for EL students and (2) provide outcomes that are valid. Accommodations that have these characteristics can be considered as being universally designed and can be used for all students as accessibility features regardless of their linguistic and cultural backgrounds.

The academic assessment of students, including English learners (ELs), in the United States dates back more than a century. The practice of large-scale assessment began with intelligence testing in the 1910s. Emphasis on intelligence testing quickly shifted to academic achievement testing by the 1930s. ELs remain the fastest-growing subgroup of students in the nation. Much EL student growth has been concentrated in specific states. In 2016, for example, California’s EL population was 20.2 percent, while West Virginia’s was less than 1 percent. During the 1910s intelligence tests were first used for Army job placement and later transitioned into intelligence measurement tools for children in school. Through a series of revisions to the Binet-Simon intelligence scale by Lewis Terman in 1912, the test was renamed the Stanford-Binet scale and was administered to thousands of students in the late 1910s. In early twentieth century, intelligence was primarily viewed as result of heredity, predetermined by genes rather than based on nurture and environment.

In the present article, we present a systematical review of previous empirical studies that conducted formative assessment interventions to improve student learning. Previous meta-analysis research on the overall effects of formative assessment on student learning has been conclusive, but little has been studied on important features of formative assessment interventions and their differential impacts on student learning in the United States' K-12 education system. Analysis of the identified 126 effect sizes from the selected 33 studies representing 25 research projects that met the inclusion criteria (e.g., included a control condition) revealed an overall small-sized positive effect of formative assessment on student learning (d = .29) with benefits for mathematics (d = .34), literacy (d = .33), and arts (d = .29). Further investigation with meta-regression analyses indicated that supporting student-initiated self-assessment (d = .61) and providing formal formative assessment evidence (e.g., written feedback on quizzes; d = .40) via a medium-cycle length (within or between instructional units; d = .52) were found to enhance the effectiveness of formative assessments.

Research indicates that the performance-gap between English Language Learners (ELLs) and their non-ELL peers is partly due to ELLs' difficulty in understanding assessment language. Accommodations have been shown to narrow this performance-gap, but many accommodations studies have not used a randomized design and are based on relatively small sample sizes. Addressing such issues, we administered a standard-based mathematics assessment to approximately 3,000 Grade 9 ELL and non-ELL students under five different language-based accommodations. Results indicate that many of these accommodations did not produce significant gains for the recipients. Some even had a negative impact. We believe several factors may explain these findings. First, newer assessments, including those developed for this study, may have been linguistically modified to the point that further modification has only a limited effect. Second, the language of instruction may have not adequately prepared students for the assessment. If the language of instruction (textbook, etc.) contains unnecessary linguistic complexity, then students may not have had the opportunity to learn the assessed content. A third factor is students' unfamiliarity with these accommodations because they are seldom used in classroom instruction and teacher assessments. We discuss our findings and implications for policymakers, assessment developers, practitioners, and researchers.

In the present article, we present a systematical review of previous empirical studies that conducted formative assessment interventions to improve student learning. Previous meta-analysis research on the overall effects of formative assessment on student learning has been conclusive, but little has been studied on important features of formative assessment interventions and their differential impacts on student learning in the United States' K-12 education system. Analysis of the identified 126 effect sizes from the selected 33 studies representing 25 research projects that met the inclusion criteria (e.g., included a control condition) revealed an overall small-sized positive effect of formative assessment on student learning (d = .29) with benefits for mathematics (d = .34), literacy (d = .33), and arts (d = .29). Further investigation with meta-regression analyses indicated that supporting student-initiated self-assessment (d = .61) and providing formal formative assessment evidence (e.g., written feedback on quizzes; d = .40) via a medium-cycle length (within or between instructional units; d = .52) were found to enhance the effectiveness of formative assessments.

This study reports an independent investigation of the psychometric properties of Desired Results Developmental Profile (DRDP), a teacher-rated measure of school readiness for preschool-aged children. In a sample of 2,031 low-income, 3- to 5-year-old children attending Head Start, we tested three measurement models: a higher order one-factor model, a seven-factor model, and a five-factor model. To explore the appropriateness of the DRDP for use with diverse populations of young children, we used multiple group and differential item functioning (DIF) analyses to determine whether the DRDP works differently for dual language learners (DLL) and non-DLLs. The proposed five-factor structure fits the data best, with greater face and statistical validity. Using this conceptually driven factor structure, the multiple group analyses were robust for DLL and non-DLL preschool students. More than half of the items on the DRDP displayed little DIF. Items measuring emergent language and literacy exhibited DIF favoring non-DLL children.

This study examines the power of cognitive and noncognitive variables to predict students’ performance in algebra. We investigated students’ prior year’s assessment scores and demographic characteristics to predict eighth-grade algebra scores. Using California statewide assessment data, we explored predictive factors in three regression models. These analyses reveal that the seventh-grade mathematics test scores account for 61% of the variance in eighth graders’ algebra test scores. Analyzing subscores of the seventh-grade mathematics test, the assessment content focus of rational numbers is a major predictor, contributing 48% of the variance in eighth graders’ algebra test scores. On the other hand, students’ demographic variables show little predictive power for eighth-grade algebra scores. This study provides empirical evidence for understanding the factors that impact a student’s success in learning algebra.

Writing achievement levels are chronically low for K-12 students. As assessments follow the transition to computer-based writing, differences in technology access may exacerbate students’ difficulties. Indeed, the writing process is shaped by the tools we use and computer-based writing is different from writing with pen and paper. We examine the relationship between reported prior use of computers and students’ achievement on the first national computer-based writing assessment in the United States, the 2011 National Assessment of Educational Progress (NAEP) assessment. Using data from over 24,100 eighth grade students, we found that prior use of computers for school-related writing had a direct effect on writing achievement scores on the computer-based NAEP assessment. One standard deviation increase in prior use led to a 0.14 and 0.16 standard deviation increase in mean and scaled writing achievement scores respectively, with demographic controls and jackknife weighting in our SEM analysis. We also looked at earlier NAEP assessments and found that prior computer use did not positively affect the earlier pen and paper-based writing assessments.

This data article contains information based on the 2011 National Assessment of Educational Progress in Writing Restricted-Use Data, available from the National Center for Education Statistics (NCES Pub. No. 2014476). https://nces.ed.gov/nationsreportcard/researchcenter/datatools.aspx. The data include the statistical relationships between survey reports of teachers and students regarding prior use of computers and other technology and writing achievement levels on the 2011 computer-based NAEP writing assessment. This data article accompanies “The Effects of Prior Computer Use on Computer-Based Writing: The 2011 NAEP Writing Assessment” [1].