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Meeting students' basic needs – including ensuring they have access to nutritious meals and a sense of belonging and connection to school – can positively influence students' academic performance. Recognizing this connection, schools provide resources in the form of school meals programs, school nurses, and school guidance counselors. However, these resources are not always available to students and are not always prioritized in school reform policies, which tend to focus more narrowly on academic learning. This book is about the balancing act that schools and their teachers undertake to respond to the social, emotional, and material needs of their students in the context of standardized testing and accountability policies. Drawing on conversations with teachers and classroom observations in two elementary schools, How Schools Meet Students' Needs explores the factors that both enable and constrain teachers in their efforts to meet students' needs and the consequences of how schools organize this work on teachers' labor and students' learning.

When do children become unequal in reading and math skills? Some research claims that inequality grows mainly before school begins. Some research claims that schools cause inequality to grow. And some research—including the 2004 study “Are Schools the Great Equalizer?”—claims that inequality grows mainly during summer vacations. Unfortunately, the test scores used in the Great Equalizer study suffered from a measurement artifact that exaggerated estimates of inequality growth. In addition, the Great Equalizer study is dated and its participants are no longer school-aged. In this article, we replicate the Great Equalizer study using better test scores in both the original data and a newer cohort of children. When we use the new test scores, we find that variance is substantial at the start of kindergarten and does not grow but actually shrinks over the next two to three years. This finding, which was not evident in the original Great Equalizer study, implicates the years before kindergarten as the primary source of inequality in elementary reading and math. Total score variance grows during most summers and shrinks during most school years, suggesting that schools reduce inequality overall. Changes in inequality are small after kindergarten and do not replicate consistently across grades, subjects, or cohorts. That said, socioeconomic gaps tend to shrink during the school year and grow during the summer, while the black-white gap tends to follow the opposite pattern.

This study describes psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) executive function measures in an adult sample. The NIHTB-CB was designed for use in epidemiologic studies and clinical trials for ages 3 to 85. A total of 268 self-described healthy adults were recruited at four university-based sites, using stratified sampling guidelines to target demographic variability for age (20–85 years), gender, education and ethnicity. The NIHTB-CB contains two computer-based instruments assessing executive function: the Dimensional Change Card Sort (a measure of cognitive flexibility) and a flanker task (a measure of inhibitory control and selective attention). Participants completed the NIHTB-CB, corresponding gold standard convergent and discriminant measures, and sociodemographic questionnaires. A subset of participants (N=89) was retested 7 to 21 days later. Results reveal excellent sensitivity to age-related changes during adulthood, excellent test–retest reliability, and adequate to good convergent and discriminant validity. The NIH Toolbox EF measures can be used effectively in epidemiologic and clinical studies. (JINS, 2014, 20, 1–10)

This paper presents the development and validation of a cost-effective 3D-printed conductive phantom for EEG sensing system validation that achieves 85% cost reduction (£48.10 vs. £300–£500) and 48-hour fabrication time while providing consistent electrical properties suitable for standardized electrode testing. The phantom was fabricated using conductive PLA filament in a two-component design with a conductive upper section and a non-conductive base for structural support. Comprehensive validation employed three complementary approaches: DC resistance measurements (821–1502 Ω), complex impedance spectroscopy at 100 Hz across anatomical regions (3.01–6.4 kΩ with capacitive behavior), and 8-channel EEG system testing (5–11 kΩ impedance range). The electrical characterization revealed spatial heterogeneity and consistent electrical properties suitable for comparative electrode evaluation and EEG sensing system validation applications. To establish context, we analyzed six existing phantom technologies including commercial injection-molded phantoms, saline solutions, hydrogels, silicone models, textile-based alternatives, and multi-material implementations. This analysis identifies critical accessibility barriers in current technologies, particularly cost constraints (£5000–20,000 tooling) and extended production timelines that limit widespread adoption. The validated 3D-printed phantom addresses these limitations while providing appropriate electrical properties for standardized EEG electrode testing. The demonstrated compatibility with clinical EEG acquisition systems establishes the phantom’s suitability for electrode performance evaluation and multi-channel system validation as a standardized testing platform, ultimately contributing to democratized access to EEG sensing system validation capabilities for broader research communities.

Remediation is one of the largest single interventions intended to improve outcomes for underprepared college students, yet little is known about the remedial screening process. Using administrative data and a rich predictive model, we find that severe mis-assignments are common using current test-score-cutoff-based policies, with \"underplacement\" in remediation much more common than \"overplacement\" college courses. Incorporating high school transcripts into the process could significantly reduce placement errors, but adding test scores to already available high school data often provides little marginal benefit. Moreover, the choice of screening policy has significant implications for the racial and gender composition of college-level courses. Finally, the use of more accurate screening tools would enable institutions to remediate substantially fewer students without compromising college success.

The United States Medical Licensing Examination (USMLE) Step 1, arguably the most significant assessment in the USMLE examination series, changed from a 3-digit score to a pass/fail outcome in January 2022. Given the rapidly evolving body of literature on this subject, this paper aims to provide a comprehensive review of the historical context and impact of this change on various stakeholders involved in residency selection. For this, relevant keyword-based searches were performed in PubMed, Google Scholar, and Scopus to identify relevant literature. Given the unique history of USMLE Step 1 in the US residency selection process and the score's correlation with future performance in board-certifying examinations in different specialties, this scoring change is predicted to significantly impact US Doctor of Medicine students, US Doctor of Osteopathic Medicine students, international medical graduates, and residency program directors, among others. The significance and the rationale of the pass/fail change along with the implications for both residency applicants and educators are also summarized in this paper. Although medical programs, academic institutions, and residency organizing bodies across the United States have swiftly stepped up to ensure a seamless transition and have attempted to ensure equity for all, the conversion process carries considerable uncertainty for residency applicants. For educators, the increasing number of applications conflicts with holistic application screening, leading to the expected greater use of objective measures, with USMLE Step 2 Clinical Knowledge likely becoming the preferred screening tool in lieu of Step 1.

Background The purpose of this systematic review was to (1) determine the scope of literature measuring USMLE Step 1 and Step 2 CK as predictors or indicators of quality resident performance across all medical specialties and (2) summarize the ability of Step 1 and Step 2 CK to predict quality resident performance, stratified by ACGME specialties, based on available literature. Methods This systematic review was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [16]. The original search strategy surveyed MEDLINE and was adapted to survey Cochrane Library and Embase. A study was deemed eligible if it provided all three of the following relevant information: (a) Step 1 or Step 2 CK as indicators for (b) resident outcomes in (c) any ACGME accredited specialty training program. Results A total of 1803 articles were screened from three separate databases. The 92 included studies were stratified by specialty, with Surgery (21.7% [20/92]), Emergency Medicine (13.0% [12/92]), Internal Medicine (10.9% [10/92]), and Orthopedic Surgery (8.7% [8/92]) being the most common. Common resident performance measures included ITE scores, board certification, ACGME milestone ratings, and program director evaluations. Conclusions Further studies are imperative to discern the utility of Step 1 and Step 2 CK as predictors of resident performance and as tools for resident recruitment and selection. The results of this systematic review suggest that a scored Step 1 dated prior to January 2022 can be useful as a tool in a holistic review of future resident performance, and that Step 2 CK score performance may be an effective tool in the holistic review process. Given its inherent complexity, multiple tools across many assessment modalities are necessary to assess resident performance comprehensively and effectively.

Multiple-choice examinations play a critical role in university admissions across the world. A key question is whether imposing penalties for wrong answers on these examinations deters guessing from women more than men, disadvantaging female testtakers. We consider data from a large-scale, high-stakes policy change that removed penalties for wrong answers on the national college entry examination in Chile. The policy change reduced a large gender gap in questions skipped. It also narrowed gender gaps in performance, primarily among high-performing test-takers, and in the fields of math, social science, and chemistry.

Little research exists on the relationship between pre-examination resources, race, and standardized test outcomes. This study aimed to determine the effect of test preparation resources and race on test scores. We surveyed medical students at an allopathic institution on the use of test preparation materials and their test scores. Students were grouped by self-identified race. Underrepresented in Medicine (URiM) students were defined as Black/African American (AA), Hispanic/Latino (HL), Native American (NA) and multiple races. Univariate analysis and linear regression were used for statistical analysis. 192 students completed the survey (response rate = 33%). URiM students reported more MCAT attempts than other students. No differences between scores existed between races. There was no association between scores and the use of test preparation resources. We found that URiM students took the MCAT more times than their peers; however, we found no racial/ethnic differences in examination preparation resources or scores.

Those asked to make valid decisions with data don’t have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this paradox by following a five-step model in which they make a claim, make the opposite claim, and then determine how well both claims are supported by the available evidence. This process can enable practicing educators to make more valid decisions based on data.