National Center For Education Statistics Research Articles

SchoolHEAT: Racial and Ethnic Inequity in School Temperature.

Exposure to high environmental temperature is detrimental to health through multiple pathways. This paper describes disparities in school-based high-temperature exposure at metropolitan schools in the United States. Using school location and sociodemographic data from the National Center for Education Statistics, neighborhood data from the US Census Bureau, and land surface temperature (LST) data from the Aqua Earth-observing satellite mission, we find that for every 10% more Black or Hispanic residents in the neighborhood, schools have LST 0.25°C and 0.38°C hotter, respectively. When the Black or Hispanic student population is greater than the neighborhood population, LST is an additional 0.20°C and 0.40°C for each 10% increase in students over neighborhood population, respectively. Black and Hispanic students are overrepresented in the hottest schools, making up 58.7% of students in the hottest 20% of schools, compared to only 30.0% of students in the coolest 20% of schools.

Relationship Between Athletic Trainer Access, Socioeconomic Status, and Race and Ethnicity in United States Secondary Schools.

Extensive research has exposed healthcare disparities regarding socioeconomic status (SES) and race/ethnicity demographics. Previous research has shown significant differences in access to athletic training services (AT access) in the secondary school setting based on SES, but with limited samples. This study investigated differences in AT access based on race/ethnicity and SES on a national scale. Cross-sectional study. Database study using secondary analysis. Data were collected from the National Center for Education Statistics (NCES), Athletic Training Location and Services (ATLAS) database, and US Census Bureau. 10,983 public schools. Descriptive data was summarized by measures of central tendency. A one-way ANOVA determined differences between school characteristics: median household income (MHI), percent of students eligible for free and reduced lunch (%FRL), percent white students, and percent non-white students based on AT access: Full-time (FT-AT), part-time (PT-AT), and no athletic trainer (no-AT). A Bonferroni pairwise comparison was used for variables with significant main effects. Across all schools included in the study, 43.8% had no-AT (n=4,812), 23.5% had PT-AT access (n=2,581), and 32.7% had FT-AT access (n=3,590). There were significant effects between AT access and MHI (p<.001), %FLR (p<.001), percent white (p<.001), and percent non-white (p<.001). FT-AT schools had a higher SES when compared to PT-AT and no-AT schools. Significant differences existed between AT access groups and race/ethnicity of schools. Schools with FT-AT had a significantly lower percent of non-white students (31.3%) compared to schools with no-AT (46.0%) (p<.001). No significant differences between FT-AT and PT-AT based on race/ethnicity demographics presented (p≥.13). Schools with higher SES had greater AT access; whereas, schools with a higher percentage of non-white students were more likely to have no AT access, demonstrating the disparities in healthcare extends to athletic healthcare as well. To increase AT access, future initiatives should address the inequities where larger minority populations and counties of lower SES exist.

Characteristics of U.S. Baccalaureate Health Informatics Programs.

Health informatics (HI) is a growing field of study, yet sparse data are available on the characteristics of undergraduate HI programs in the United States. The lack of a central location for U.S. HI undergraduate program data has led to a gap in information to support current efforts to promote academic standards in the field and attract potential students. The objective of this study was to perform an environment scan of colleges and universities within the United States and Puerto Rico to identify undergraduate programs in HI including majors, minors, and undergraduate-level certificates. Potential institutions offering HI programs were identified from the National Center for Education Statistics (NCES), the Commission for Accreditation of Health Informatics and Health Information Management Education (CAHIIM), the Association of University Programs in Health Administration (AUPHA), the Healthcare Information and Management Systems Society (HIMSS), and the American Health Information Management Association (AHIMA). Publicly available materials for these institutions were reviewed, and data were captured for identified HI programs including geographic location; college or school in which the program was offered; type of degree (if applicable); program title; total credits to complete the program; delivery format; and source of data. A total of 83 HI programs were identified from 60 institutions and 26 states. The primary finding of this environment scan was that inconsistencies exist among U.S. HI undergraduate programs including variations in offering college/school, title of program, number of credits required, delivery formats, CIP codes, and the type of information published on university/college websites. This environment scan was a first step in exploring the characteristics of undergraduate HI programs within the United States. Further research is needed on the curricular similarities and differences among the programs, the administrative methods of these interdisciplinary programs, and the information most needed by current and potential undergraduate students.

Oceania in the Desert: A QuantCrit Analysis of the (Under)Counting of Native Hawaiian and Pacific Islander Students at an AANAPISI-HSI

Most education research uses the National Center for Education Statistics (NCES) Integrated Postsecondary Education Data System (IPEDS), often leaving the logic undergirding the IPEDS racial classification system (i.e., categorization and counting) unquestioned. Framed by Quantitative Critical Race Theory (QuantCrit) principles, this research demonstrates how the NCES IPEDS racial classification misrepresents and undercounts students. Specifically, we show how IPEDS guidance around racial classification misrepresents the number of Asian American, Native Hawaiian, and Pacific Islander (AA&NHPI) undergraduates, with particular attention to NHPI students, at a single institution. We show the ways in which IPEDS logic leads to undercounting, namely that, based on the NCES IPEDS racial classification system, most undergraduates identifying as NHPI are classified as Two or More Races and Hispanic or Latino. A similar pattern of suppression is found to varying degrees for students identifying as American Indian or Alaska Native, Asian, and Black or African American. Our findings complicate the taken-for-granted nature of IPEDS racial classification and have implications for serving racially minoritized student groups and for institutions that may qualify as enrollment-based Minority-Serving Institutions.

Rurality and Resources: Influence of High School and Individual Characteristics on Postsecondary Participation

This study explores a cohort of rural high school student's participation in postsecondary education within three years of graduation. We use the National Center for Educational Statistics (NCES) 's High School Longitudinal Study of 2009 (HSLS2009) and logistic regression to answer our research questions. We found that many rural students plan to attend college and even apply to college; however, this did not mean that students would attend college. Also, counselors spending 20-50 percent of their time on college support positively affected students' college enrollment.

Mixed-Reality Simulation to Prepare Preservice Teachers to Use Culturally Responsive Teaching Strategies: A Pilot Study

By 2031, culturally and linguistically diverse students will represent approximately 55% of students enrolled in United States public schools (National Center for Educational Statistics, 2023). Despite increased ethnic diversity among students, most teachers are White. Consequently, many new teachers report feeling ill-equipped to implement culturally responsive teaching strategies to meet the needs of culturally and linguistically diverse students. To prepare culturally responsive preservice teachers, teacher preparation programs can embed technologies such as mixed-reality simulation paired with explicit instruction and performance feedback to support the preservice teachers’ implementation of culturally responsive teaching strategies. This mixed methods (convergent parallel design) pilot study evaluated how using mixed-reality simulation, explicit teaching, and performance feedback impacts preservice teachers’ knowledge of culturally responsive teaching strategies and self-efficacy. Results indicated that participants increased their knowledge, implementation, and self-efficacy. We discuss the findings and limitations and offer recommendations to improve mixed-reality simulation within teacher preparation programs and recommendations for future research.

A.M.Aminee, J.Taylor. Generative AI Results and Reality

The accuracy of Generative Artificial Intelligence (GAI) tools is the product of the quality of underlying data used to train models, and the models themselves. This interplay between data and models can lead to differences in the accuracy of outputs provided to common prompts across different GAI tools. This study investigates the disparities in accuracy related to representativeness between the outputs of GAI tools and demographic data from National Center for Education Statistics (NCES) and large enrollment, regional comprehensive university in the western United States (CSU). Three GAI platforms - ChatGPT, Co-pilot, and Gemini were evaluated using five samples each, with the same instruction across all platforms: “Show a class of graduate students.” The GAI outputs were analyzed based on three demographic variables: gender, race, and age group. These outputs were then compared to national averages from the NCES for gender and race and the CSU for age group. Notably, the variances in the results showed broader distributions across the demographic variables. To assess accuracy, a representation rate metric was calculated, reflecting the average absolute variance from the NCES and CSU benchmarks. The findings highlight the opportunity of higher quality data in model training, as well as the necessity for improved algorithms and methodologies in GAI systems to represent complex demographic information more accurately.

Is the GI Bill Enough? An Exploratory Analysis of Student Veteran Borrowing in College

In the United States, many student veterans use their GI Bill benefits to help fund their postsecondary education; however, when the GI Bill is not enough, student veterans may turn to grants and loans to subsidize their financial needs. This study examines the degree and extent to which Pell Grants and student loans are being used by student veterans using data pulled from the National Center for Education Statistics’ Baccalaureate and Beyond dataset. We found that Pell Grant awards were higher for student veterans with disabilities as well as Blacks and that a student’s age contributed to the overall amount of federal student loans borrowed. Implications, future directions, and a discussion of the results are provided.

Novel Feature-Based Difficulty Prediction Method for Mathematics Items Using XGBoost-Based SHAP Model

The level of difficulty of mathematical test items is a critical aspect for evaluating test quality and educational outcomes. Accurately predicting item difficulty during test creation is thus significantly important for producing effective test papers. This study used more than ten years of content and score data from China’s Henan Provincial College Entrance Examination in Mathematics as an evaluation criterion for test difficulty, and all data were obtained from the Henan Provincial Department of Education. Based on the framework established by the National Center for Education Statistics (NCES) for test item assessment methodology, this paper proposes a new framework containing eight features considering the uniqueness of mathematics. Next, this paper proposes an XGBoost-based SHAP model for analyzing the difficulty of mathematics tests. By coupling the XGBoost method with the SHAP method, the model not only evaluates the difficulty of mathematics tests but also analyzes the contribution of specific features to item difficulty, thereby increasing transparency and mitigating the “black box” nature of machine learning models. The model has a high prediction accuracy of 0.99 for the training set and 0.806 for the test set. With the model, we found that parameter-level features and reasoning-level features are significant factors influencing the difficulty of subjective items in the exam. In addition, we divided senior secondary mathematics knowledge into nine units based on Chinese curriculum standards and found significant differences in the distribution of the eight features across these different knowledge units, which can help teachers place different emphasis on different units during the teaching process. In summary, our proposed approach significantly improves the accuracy of item difficulty prediction, which is crucial for intelligent educational applications such as knowledge tracking, automatic test item generation, and intelligent paper generation. These results provide tools that are better aligned with and responsive to students’ learning needs, thus effectively informing educational practice.

Who’s the best? Investigating the NAMM Foundation’s “Best Communities of Music Education” awardees

The “Best Communities for Music Education” (BCME) award from the National Association for Music Merchants (NAMM) Foundation is intended to celebrate school districts committed to supporting music education. However, despite its over twenty-year history, little is known about the awardees themselves. The purpose of this study was to describe the characteristics of school districts that received NAMM’s BCME award in 2021 and 2022. We utilized publicly available data from NAMM and the National Center for Education Statistics (NCES) to analyze demographic data of 2021 and 2022 awardees along several categories. We also gathered and analyzed BCME lists from 2005–2020 to provide an insight on the frequency of repeat awardees. Findings show that awardees primarily represent suburban communities that skew more affluent, more educated, and more white than national averages. These findings may help interrogate conceptions of quality, highlight issues of inequity among school districts, and bring insight into policy tools underpinning public music education advocacy efforts.

Requirements of the undergraduate economics major: An update and comparison

The undergraduate economics curricula for most of the 793 U.S. colleges and universities that conferred an economics bachelor’s degree in 2019 are described in this article. Besides updating the prevalence of the economics major core requirements and their differences by institution type, the authors record new information on requirement variations across economics degree types, as classified by the National Center for Education Statistics, including STEM-designated degree types. They also investigate the prevalence of calculus-based intermediate courses and find that 63 percent of economics degrees require calculus for intermediate microeconomics and macroeconomics. In addition, 67 percent of degrees require single-variable calculus, 10 percent require multi-variable calculus, and 54 percent require basic econometrics (up from 41% in 2010). These requirements also vary highly by degree type.

Supplementing a Paper Questionnaire with Web and Two-way Short Message Service (SMS) Surveys

Abstract When deciding which modes to offer, researchers consider cost, known respondent contact information, and potential mode effects. For a short survey on employment, we evaluate the effect of adding one of two new electronic data collection modes to a mailed questionnaire. We sent a survey to principals who previously responded to the National Center for Education Statistics’ (NCES) National Teacher and Principal Survey (NTPS) asking about their current job status. This questionnaire, known as the Principal Follow-up Survey (PFS), has typically been administered as a short paper form that is mailed to NTPS respondents. In 2022, the PFS introduced two new modes of completion, and principals were randomly assigned to receive: (i) a paper form only; (ii) a paper form, as well as emails with a direct link to complete a web survey; or (iii) a paper form, as well as invitations by text message to complete an automated two-way short message service text survey by responding to texted “yes/no” questions. This article compares overall response rates and time-to-response by mode to determine respondent preferences for completing short surveys. Adding either electronic mode significantly increased response rates and decreased the number of days in which completed surveys were received, compared to offering only a paper questionnaire. Although email and text messages are both forms of electronic communication that may be accessible on a smartphone, the added text message survey resulted in higher response rates than the added web survey. This suggests that respondents interact differently with emails and text messages they receive and that offering an option to complete a survey by text message can increase the speed and efficiency of data collection for short surveys.

Examining the relationship between Hispanic Serving Community college Title III grants and STEM associate degree completion

AbstractHispanic‐Serving Community Colleges enroll and educate a large share of Hispanic postsecondary students. Due to work trends and demographic changes, Hispanic and other historically underrepresented students play a crucial role in shaping the next generation of Science, Technology, Engineering, and Math (STEM) scholars and practitioners. We use data from the National Center for Education Statistics and a difference‐in‐differences technique to estimate the association between federal capacity building grants aimed at improving STEM degree attainment outcomes and associate degree completion. We find receipt of a Title III grant was associated with about a 30% increase in the total number of STEM associate degrees awarded. Further, the grants nearly doubled the number of STEM associate degrees awarded to Hispanic students, on average. This positive relationship is driven by institutions receiving more than one grant. We conclude by discussing these findings and providing federal and institutional recommendations.

Portrait of Rural Social Studies Teachers (and Their Students)

In this study, we first provide a snapshot of key demographics and characteristics of social studies teachers in a rural setting based the 2017-2018 National Teacher and Principal Survey (NTPS) restricted-use data file from the National Center for Educational Statistics (NCES), administered by the Institute for Education Sciences (IES). Second, we look at potential implications based on specific insights from the data, including recognition of the change happening in the demographics of rural communities and a need for sustained PD about teaching students with diverse identities.

The gender gap in STEM at top U.S. Universities: change over time and relationship with ranking

Addressing the gender gap in science, technology, engineering, and mathematics (STEM) fields may be an opportunity to promote equity and enhance institutional environments and their performance. We aimed to measure male-dominated undergraduate programs’ change in gender diversity over time, whether it has been converging, and whether it correlates with disciplinary ranking. We considered the number of degrees conferred in 60 disciplines over 19 years at 24 universities representing the top 20 universities of two lists using data from the National Center for Education Statistics (NCES) Integrated Postsecondary Education Data System (IPEDS). We found that the nine most male-dominated disciplines fell within STEM, suggesting continued effort is needed to address the gender gap. Eight of the nine most male-dominated disciplines increased in gender diversity over time, especially between the two most recent time periods, suggesting contemporary policies are often effective. We also found that five out of eight of the most male-dominated disciplines converged over time, which may imply increasing homogeneity in these universities’ gender-diversity policies in some disciplines. Of the nine most male-dominated disciplines, computer science and mechanical engineering had statistically significant results that suggested higher-ranked universities in these disciplines weakly correlated with higher disciplinary gender diversity. The weak correlation between rank and women’s representation suggests that universities with increased resources are better able to create effective initiatives to increase women’s representation in STEM. More broadly, our results suggest these 24 universities’ initiatives have been effective in reducing the STEM gender gap from 2002 to 2021, but room for improvement remains.

Unsafe at any Bandwidth: Towards Understanding Risk Factors for Ransomware in Higher Education

United States higher education institutions host an assortment of services that are accessible via public IP addresses. The wide variety of network services and the important personal and institutional data stored on such services make higher education institutions particularly desirable targets for attackers. This study analyses the vulnerabilities found through Shodan scans on these networks, in conjunction with institutional characteristics data taken from the National Center for Education Statistics (NCES), to examine correlations between an institution’s characteristics and the vulnerabilities found on its networks. By exploring this data, the study aims to bring awareness to the current state of higher education institution network security and determine vulnerability trends between certain institutions. Our analysis reveals that most institutions have many medium impacts but highly exploitable vulnerabilities, with most being on Apache HTTP servers. We also present that the most significant indicators of an institution’s vulnerability are its enrolment and yearly total expenses. We investigate how smaller institutions have lower numbers of vulnerabilities, but their vulnerabilities have the potential for higher impact. We conclude that there is a significant chance of ransomware risk in US higher educational institutions.

Forms of Bullying Prevalent in Public Secondary Schools: A Case of Selected Schools in Machakos County, Kenya.

Bullying in schools is a global problem that has short- and long-term negative health consequences on both the bullies and victims. A report by the National Center for Educational Statistics (2019) shows that one out of every five (20.2%) students report being bullied. This has long term physical, psychological and academic negative impact among students. The researcher sought to assess the prevalence of forms of bullying in public secondary schools in Machakos sub county, Machakos County. The researcher employed descriptive research design. Purposive sampling and simple random sampling were used to select 280 respondents. The study used both open and closed ended questionnaires to collect data. Data was analyzed using SPSS version 23.0. The study used both descriptive and inferential statistics to describe quantitative data which were then analyzed, interpreted, and presented in form of tables and figures. The study established that about 71.5% of students participated in bullying and among the different forms of bullying verbal (38.9%) was leading followed by psychological (21.7%), sexual physical (15.3%) and cyber bullying (11.2%). The study revealed that boys suffered more physical and cyber bullying while girls suffered more of sexual and verbal bullying activities. The study concluded that four forms of bullying are prevalent in Machakos County and that there is need to seek solutions in order to curb it down.

Chicana/Latina feminism: What is it and how does it define us?

AbstractLatinas holding doctoral degrees are few and far between in the academic world as compared to their White female counterparts (National Center for Educational Statistics, 2020). We explore a crucial topic of Chicana/Latina feminism, which resists traditional theoretical concepts and methodologies in the field of adult education. Chicana/Latina feminism is a feminist theory that has transcended academic disciplines since its conception in ethnic women's studies. Therefore, the purpose of this paper is to offer an in‐depth look at Chicana/Latina feminism by defining the origins of a Chicana feminist theory, exploring the need to decolonize adult educational research to allow a more inclusive space for women of color in academia, attesting to the application of a Chicana feminist epistemology with the use of testimonios, and discussing the implications of embedding Chicana feminist perspectives in adult educational research.

미국 Title I 프로그램이 학생 성취에 미치는 효과

[Purpose] This paper aims to empirically investigate the impact of the federally funded Title I program on the performance of students from low-income families, as assessed through the state's own assessments. Additionally, the study seeks to discern the relative effectiveness of two specific program, namely the school-wide program and the targeted assistant program, to see which program is more effective.&#x0D; [Methods] To accomplish these objectives, the research leverages two national data sets from 2008-09 to 2013-14, sourced from the U.S. Department of Education's EDFacts and the National Center for Education Statistics' Common Core of Data. Employing fixed-effects and mixed-effects models with the school-level data, the study conducts a rigorous examination of the program's impact across various grade levels.&#x0D; [Results] The findings of this study reveal that the Title I program exerts substantially positive effects on academic outcomes of economically disadvantaged students in lower grades, with moderate positive effects observed in middle grades. However, no discernible impact is observed at the high school level. In terms of the specific program effects, lower grade levels exhibited higher achievement when implementing the “school-wide program”, whereas high schools showed lower achievement. Conversely, transitioning from the “targeted assistant program” to the “school-wide program” demonstrated positive effects only at the high school level.&#x0D; [Conclusion] The results of this study demonstrate the importance of prioritizing investments in early grades when providing educational services or support to students in need. As students progress to higher grades, there is a need to design and implement programs that are tailored to their levels and circumstances. Furthermore, in allocating education finances for low-income groups, prioritize elementary schools for 'whole-school programs,' and support high schools in developing the capacity to run comprehensive programs.

2320. Impact of Lifting School Mask Mandates on Community COVID-19 Cases and Hospitalizations: A Nationwide, Retrospective Cohort Study with an Event Study Design

Abstract Background During the school re-opening process, masking mandates were widely adopted in schools in the United States to reduce spread of SARS-CoV-2 in in-school settings and in the surrounding community. The aim of this nationwide, retrospective cohort with an event study design was to evaluate the impact of masking policy de-adoption on SARS-CoV-2 cases and hospitalizations in the surrounding community. Methods Data collected from 9/2021-6/2022 on SARS-CoV-2 cases, hospitalizations, and vaccination rates at the county-week level obtained from the Centers for Disease Control and Prevention were combined with manually-validated, weekly district-level masking policy data obtained from Burbio and district-level school demographic data from the National Center for Education Statistics. Data were analyzed using an event study design, a causal inference method, to estimate the primary outcome: incidence of SARS-CoV-2 cases per 100,000 county residents during the 8-week period following the policy change, stratified by age (in decades). Hospitalization rates per 1,000,000 residents were estimated secondarily. Results N= 3,970 districts composed of 53,453 schools and an estimated 31,264,546 students were included. Prior to masking mandate de-adoption, there was no clear trend in case rates in any of the age categories evaluated. Within one-week following policy de-adoption, a small increase in case rates was seen in all age groups evaluated, ranging from 6.92 to 37.34 per 100,000 county residents in the 0-9 year old age group to 25.08 - 120.36 cases per 100,000 residents per week in the 20-49 year old age group. A small increase in hospitalization rates following masking policy de-adoption was seen in all age groups evaluated. Among 0–49-year-olds, increases were seen one week following the policy change. Increases in hospitalization rates were not evident for 50–69-year-olds and &amp;gt;70 year olds until 3 and 4 weeks after the policy change. Conclusion Lifting mask mandates in schools were associated with a small increase in case rates in the surrounding community, with the highest increase in individuals of parental age (20–49-year-olds). A small but measurable impact on severe disease, as measured by hospitalization rates, was identified. Disclosures Elissa Schechter-Perkins, MD, MPH, Gilead Sciences: Grant/Research Support Westyn Branch-Elliman, MD, MMsc, DLA Piper, LLC/Medtronic: Advisor/Consultant|DLA Piper, LLC/Medtronic: Expert Testimony|Gilead Sciences: Grant/Research Support