Math Scores Research Articles

The effect of stand-your-ground laws on student achievement

ObjectivesTo examine how “stand-your-ground” (SYG) laws affect children’s academic performance. MethodsWe analyze 2008–2018 nationwide school district-level math and reading/language arts (RLA) test scores for 3rd-8th grade students combined with information on SYG laws by state and year. We implement two estimation approaches—two-way-fixed effects and group-time average treatment effects—and conduct analyses stratified by student race (Black, White) and area income level. ResultsWe find negative effects of SYG on math achievement among all students using both estimation approaches (−0.0377 standard deviation decline, p < 0.001 and −0.0493, p < 0.001). We find adverse effects of SYG on math among White students (−0.0315, p = 0.001 and −0.0312, p = 0.08) and among students in low-income districts (−0.0616, p < 0.001 and −0.0903, p < 0.001). The precision of estimates for the effect on math scores among Black students varies across approaches (−0.0666, p = 0.05, −0.0444, p = 0.48). We estimate negative effects of SYG on RLA achievement in only a subset of models. ConclusionsOur findings suggest SYG laws adversely affect math performance among 3rd-8th grade students. Policy implicationsThese findings underscore the importance of additional work to understand and quantify the relationship between the nation’s gun policies and children’s academic performance.

The impact of the COVID-19 pandemic on the academic achievement of elementary and junior high school students: analysis using administrative data from Amagasaki City

AbstractThe coronavirus disease 2019 (COVID-19) pandemic has had a global impact on children’s education. In Amagasaki City, Japan, elementary and junior high schools were temporarily closed for approximately three months during the pandemic. This study examines the effects of the COVID-19 pandemic on academic performance in mathematics and the Japanese language among public elementary and junior high school students in Grades 1 to 8. Using data from the Amagasaki City Survey of Academic Achievement and Life Conditions from 2018 to 2021, this study compares changes in the academic performance of cohorts with and without COVID-19 experience (the COVID-19 and non-COVID-19 cohorts, respectively) 7 and 19 months after school closures using the difference-in-differences method. The findings indicate that the negative impact of the pandemic on academic performance was more pronounced for math than for the Japanese language, both at 7 months and 19 months after the closures. Math scores showed considerable decreases of 0.133 standard deviations (SDs) and 0.249 SDs at 7 and 19 months after the closures, respectively, while Japanese language scores were not significantly affected 7 months after closures but decreased by 0.113 SDs at 19 months after the closures. Furthermore, the negative effects on Japanese language scores were more significant for individuals in younger grades, whereas math scores were consistently affected across all grades. These results have important implications for policymakers and educators struggling to overcome the learning losses among children caused by the pandemic.

Gender Differences in Math Tests: the Role of Time Pressure

Abstract We investigate the role of time pressure in generating gender gaps in math tests. In a randomised experiment, college students took a twenty-question math test under high, low or no time pressure. Reducing or eliminating time pressure decreases the math gender gap by up to 40%. Larger gaps under time pressure are mostly due to increased anxiety rather than to students modifying their test-taking strategies. The correlation between math test scores and university performance is equally high under the different scenarios. Hence, less time pressure may increase gender equality in math subjects with no effect on the selection process.

The effect of family economic capital on the cognitive ability of migrant children in China

The scale of migrant populations and the prevalence of family-based migration in China have sparked concerns about migrant children. After moving to the city, compared to loacl children, migrant children are at a disadvantage in terms of access to external educational resources and internal family education. It is thus of great academic and practical importance to explore the factors affecting the cognitive abilities of migrant children. Using the CFPS database in 2014, 2016, and 2018, this study investigates the effects and mechanisms of family economic capital on the cognitive ability of migrant children. The findings show that family economic capital greatly enhances the Chinese and Math performance of migrant children and that there is heterogeneity in the effect of family economic capital on the cognitive ability of migrant children attending key schools and non-key schools. In addition, the mediating effect model shows that family economic capital mainly influences the Chinese and Math scores of migrant children through mediating variables such as family education expenditure and parental involvement. At the same time, the results of the hierarchical linear model show that the regional education level has a significantly positive moderating effect on family education expenditure, while the moderating effect on parental involvement is not significant. Therefore, assisting migrant families to increase their financial resources, family educational expenditure, and family communication can contribute to their children's human capital development.

Poor air quality at school and educational inequality by family socioeconomic status in Italy

This paper investigates social stratification in the context of poor air quality's impact on educational achievement in Italy, a country characterized by high levels of air pollution and significant geographical diversity. We address two primary questions: firstly, whether students from different socio-economic backgrounds vary in their exposure to high levels of particulate matter (PM2.5) at school, and secondly, if the effect of exposure to poor air quality on academic performance differs between children from high and low socio-economic status families. Utilizing a novel dataset comprising test scores in math and reading for 456,508 8th-grade students, collected nationally in Italy in 2019, we geocode the locations of 6882 schools based on their addresses and link the level of air pollution in the surrounding areas using PM2.5 data from the Atmospheric Composition Analysis Group. To address potential confounding factors, we estimate municipality and province fixed effects and control for indicators of school neighborhood characteristics and school quality. Our analysis yields three key findings. Firstly, students from higher socio-economic backgrounds tend to attend schools with higher PM2.5 levels. However, the positive association between SES and exposure to PM2.5 disappears when adding province and municipality fixed effects, suggesting that the positive association can be explained by selection into provinces and municipalities by SES. Secondly, we identify a small yet consistent negative effect of PM2.5 on math and reading test scores. Thirdly, this adverse impact is primarily observed among students from low socio-economic backgrounds. We conclude that the relationship between environmental risks and disparities in educational achievement based on social background in Italy is nuanced and critically influenced by the country's specific context.

Assessing the Causal Effect of Special Education Services on Math Achievement: A Causal Inference and Machine Learning Study

This study aims to assess the Average Treatment Effect (ATE) of receiving special education services on revised Item Response Theory (IRT) scaled math achievement test scores. By employing a methodological repertoire comprising linear regression with ordinary least squares (OLS), propensity score matching (PSM), Bayesian Additive Regression Trees (BART), and Multilayer Perceptron (MLP), we examine the impact of these interventions. Leveraging data from the Early Childhood Longitudinal Study Kindergarten 2010-11 cohort (ECLS-K:2011), we systematically analyze the ATE of special education services on students' math achievement. The results show that all models yield negative ATE results, suggesting a deleterious effect of special education services on fifth-grade math scores. Furthermore, we employ Principal Component Analysis (PCA) to corroborate these findings, aligning with outcomes obtained from causal inference and Machine Learning (ML) based methods. This research emphasizes the importance of method diversity in educational research and highlights the need for assessments of intervention effectiveness to help educational practices and policies.

Development and validation of Mathematical Higher‐Order Thinking Scale for high school students

AbstractGlobally, significant attention is given to the cultivation and evaluation of Mathematical Higher‐Order Thinking Skills (MHOTS). This study aims to address the gap in developing and validating suitable MHOTS structures for high school students. In this study, 53 items were determined by experts in the field of mathematics education and scale development. The study group of this study consists of 654 students educated at the high school level. We decided to split the samples randomly in two by designating a random half as exploratory factor analysis (EFA) and the other half as confirmatory factor analysis (CFA). EFA was used to confirm a robust “four‐dimensional, nine‐factor” measurement structure, encompassing four key dimensions, namely mathematical critical thinking, mathematical creative thinking, mathematical problem‐solving, and mathematical metacognitive skills. The scale's quality was assessed through a retest using CFA and the structural validity was evaluated through CFA and correlation analysis. The criterion validity of the scale was also examined using math scores. The results from the double validity analysis showed that the scale had a reasonable and valid structure. The findings established the MHOTS for high school students as a reliable and valid instrument for measuring the level of MHOTS among high school students. This newly developed scale holds promise as an effective tool to assess and enhance mathematical higher‐order thinking in the student population.

Does Family Structure Account for Child Achievement Gaps by Parental Education? Findings for England, France, Germany and the United States

AbstractThis paper explores the role of family trajectories during childhood in explaining inequalities by maternal education in children's math and reading skills using harmonized, longitudinal, and nationally representative surveys, which follow children over the course of primary and lower secondary school in four high‐income countries (England, France, Germany, and the United States). As single parenthood and family transitions are more likely among less educated parents and are associated with fewer resources for children, we explore whether growing up outside a stable two‐parent family mediates educational inequalities in math and reading scores.Results show a strong educational gradient in family trajectories in the four countries, but this varies by child age and by country. Children who experience a family transition record lower test scores, although the magnitude differs by the type of postseparation arrangements.Overall, family trajectories are strongly associated with children's math and reading scores but, because of the importance of selectivity in family trajectories, they play only a modest role in explaining the skills gaps by maternal education, considerably less than determinants such as income. The penalties associated with not living within a stable two‐parent family are always larger in the United States and England than in France and Germany.

Examining the role of the visuospatial sketchpad in children's math calculation skills using Baddeley and Hitch's model of working memory

Math difficulties (MDs) occur in about 3–7 % of children and have been associated with academic, health, and occupational challenges. To date, findings about the role of working memory in MDs have been conflicting. The Automated Working Memory Assessment Battery (AWMA), which assesses all components of Baddeley and Hitch's model of working memory, was used to investigate which component of the model was most related to math calculation skills in elementary-school children. Participants were 94 (52 male) children (M age = 9 years 1 month; Range = 6 years 0 months to 11 years 8 months). As hypothesized, math calculation scores were correlated with all four working memory components (phonological loop, visuospatial sketchpad, verbal and visuospatial central executive). After accounting for age, phonological processing, and attention, the visuospatial sketchpad was the only memory component that contributed to the prediction of math calculation scores, explaining an additional 10.2 % of unique variance. Short-term visuospatial memory should be assessed in children having difficulty with math and children could benefit from interventions that include attention to the development of both visuospatial memory and math calculation skills. This study did not use a longitudinal design and so we cannot conclude that weak visuospatial memory impedes the development of math calculation skills. Future research should use longitudinal designs and investigate other types of math skills.

The impact of COVID-19 school disruptions on children's learning.

National health policies to stop the spread of the COVID-19 virus in the US resulted in widespread school closures and disrupted learning in Spring 2020. This study draws on unique individual-level data from n = 282 5-12 year olds enrolled in the NIH Environmental influences on Child Health Outcomes (ECHO) Research Program to investigate associations between caregiver-reported duration of Spring 2020 learning disruptions and academic achievement. Linear regression analyses estimated that children who experienced more than 4 weeks of instruction disruptions in Spring 2020 scored 4.5 points [95% CI: -8.77, -0.22] lower on age-normed math assessments compared to peers who had four or fewer weeks of disruption, adjusting for sociodemographic variables, pre-pandemic vocabulary, and COVID-19 family hardships and stress. No differences were found for reading. Children whose caregivers had higher levels of pandemic-related traumatic stress and lower educational attainment also had lower math scores, adjusting for all other covariates. Results suggest educators and schools focus additional attention on supporting math instruction for children who experienced extended learning disruptions.

Examining the Existence of Cognitive Thresholds in Highly Quantitative College Courses.

While the dominant finding indicates a monotonic relationship between cognitive ability and academic performance, some researchers have suggested the existence of cognitive thresholds for challenging coursework, such that a certain level of cognitive ability is required for reaching a satisfactory level of academic achievement. Given the significance of finding a threshold for understanding the relationship between cognitive ability and academic performance, and the limited studies on the topic, it is worth further investigating the possibility of cognitive thresholds. Using a multi-institutional dataset and the necessary condition analysis (NCA), we attempted to replicate previous findings of cognitive thresholds on the major GPA of mathematics and physics-majored students, as well as the course grade of organic chemistry, to examine whether high SAT math scores constitute a necessary condition for obtaining satisfactory grades in these courses. The results from the two studies do not indicate an absolute cognitive threshold point below which students are doomed to fail regardless of the amount of effort they devote into learning. However, we did find that the chance of students with a low level of quantitative ability to succeed in highly quantitative courses is very small, which qualifies for the virtually necessary condition.

Abstract 7507: Capturing live single circulating tumor cells platform for comprehensive genomic profiling with paired ctDNA in breast cancer patients

Abstract Background: Single circulating tumor cells (sCTC) capture without cell fixation with no blood contaminants like leukocytes are highly challenging. sCTC genome transcriptomics anticipates new avenues in new discovery, targeted therapies, and inclusion of patients in clinical trials where the tissue is inaccessible. We report, an assay to selectively capture live sCTCs at singularity with NGS-based comprehensive mutational profiling in breast cancer (BC) patients. Further, paired ctDNA outcomes using blood with mutational heterogeneity scores of sCTCs adds comprehensive genomics for establishing an accelerated treatment outcomes and resistance signatures. Methods: Retrospectively, sCTC were isolated from 70 breast cancer (BC) patients using OncoRadar platform consisting affinity-based glass beads mediated by anti EpCAM antibody. CTCs were selectively captured and released without fixing and contamination of any leukocytes. Platform possess cleavable disulfide spacer at pH 8.0, between glass beads (diam. 2 mm, area 12.57 mm2) and a ligand. Sensitivity, specificity, positive predictive value (PPV), negative prediction value (NPV), and accuracy were evaluated using MCF-7 cells and CTCs. Assay to isolate CTC has been developed in 96 well plate, for downstream NGS-based comprehensive gene panel analysis using hybridization-based target enrichment. Interestingly, no mutations detected in blood samples (~20%) for CtDNA versus CTC DNA offered non-chip implicated mutations. Results:. Analytical validation using OncoRadar showed higher cell capture efficiency (99%) with spiked MCF-7 cells/ml of blood. Sensitivity and specificity values were 97% and 98% respect, while PPV was 99% and NPV was 7.5% with the accuracy parameter of 99%. Sensitivity, specificity, PPV, and NPV parameters when assessed for CTC isolation from 70 BC patients. NGS-based mutational analysis, sCTC showed the presence of PIK3CA, ESR1, and NF1 mutations, which were absent from paired ctDNA samples. Conclusion: Detection of ctDNA obscure mutations in paired sCTC samples suggests high sensitivity of sCTC-based genomic assays compared to current standard of practice. Heterogeneity scores amongst inter and intra CTCs with MATH scores offer new dimensions in genomics. Combination of ctDNA and sCTC DNA assay offers a comprehensive realistic genomic outcome for more significant therapy decisions, especially when guideline based options may exhausts. Citation Format: Gowhar Shafi, Atul Bharde, Ganesh Khutale, Saloni Andhari, Richa Deshpande, Bhagwat Jadhav, Sangeeta Prajapati, Moubeen Fauzul, Kanchan Hariramani, Madhura Basavalingegowda, Jayant Khandare. Capturing live single circulating tumor cells platform for comprehensive genomic profiling with paired ctDNA in breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7507.

School Leadership Capacity and Student Achievement: A Study of High Schools

Organizationally, what does not get measured is not prioritized or improved. Unlike student outcomes, the leadership environment that produces the results is rarely examined for its merit and impact. In this study, a quantitative survey gathered information to investigate the impacts of leadership capacity constructs on academic achievement. Principals from 161 public high schools and their schools provided the data (leadership capacity, demographics, and reading and math scores). Data were analyzed using descriptive, correlational, and regression statistics. Findings indicated significant high correlations among leadership capacity variables, significant relationships between school demographics (total school enrollment, percentage of low-income students, average class size, and attendance) and reading and math scores, and non-significant correlations between leadership capacity and academic achievement. The study delineated specific leadership capacity behaviors within the constructs that predicted student academic achievement in math and reading. The study suggests increased capacity and practice of these leadership behaviors to improve work setting and student achievement.

Assessing the effectiveness of special education services on fifth grade math scores: Using traditional and machine learning methods with ECLS-K data

Assessing the effectiveness of special education services on fifth grade math scores: Using traditional and machine learning methods with ECLS-K data

The Effect of Student Adversity Quotient on Mathematics Test Scores Using PISA Questions

This research aimed to determine the effect of student adversity quotient (AQ) on mathematic test scores of 12th-grade students in Pademawu High School, Pamekasan for geometry material. The questions used in the mathematic tests were PISA questions. The type of research was quasi-experimental research applying a quantitative method, and the populations selected were all students of class XII MIPA, as many as 115 people. By using a purposive sampling technique, the sample members were 90 people. Data was collected using questionnaires and tests. The questionnaire used contained 30 daily events, where each event had 2 questions. The math test contained 2 geometry questions. Furthermore, data collected was analysed using descriptive statistical and simple linear regression analysis. It was obtained that the regression model Y=24,328+0,373X with Y was math test scores and X was AQ scores. From the model, the result showed that there was a significant positive interaction of AQ on the results of mathematic tests at 12th-grade students in Pademawu High School.

Examining the Effects of Language Competencies on Academic Achievements of Special Needs Students and Their Peers Using Standardized Test Scores

The purpose of this study is to investigate the impact of academic language on the standardized test scores of special needs students and their peers in elementary (n = 1140) and middle (n = 451) public schools across the state of Georgia. Several univariate (ANOVA) and multivariate (MANOVA) analyses of variance are conducted on student classification (English language learners “ELL”, non-ELL, students with disabilities “SWD,” non-SWD, economically disadvantaged students “EDA”, and non-EDA) and student test scores in ELA, math, science, and social studies. Univariate (ANCOVA) and multivariate (MANCOVA) analyses of covariance are also conducted where ELA is treated as a predictor of students’ test scores in math, science, and social studies. MANOVA results reveal that the combined-subjects modeling of student test scores is significantly different by student classification with relatively large effect sizes (0.44 to 0.63) for all grade levels. Follow-up ANOVAs indicate that individual modeling of core subjects is significantly different by student classification, with effect sizes between 0.37 and 0.61. The results of ANCOVA and MANCOVA suggest a statistically significant effect of ELA on student test scores results. SWD and ELL groups benefit the most when controlling ELA test scores.

The impact of motivation on mathematics achievement of Saudi students using structure equation method and mediation analysis

This study focuses on the decline in math scores among fourth-grade students in Saudi Arabia, which is a significant concern. The Saudi Arabian Ministry of Education is taking steps to improve education and provide students with the necessary skills for their future careers. Understanding what affects student achievement is key to solving this problem. Motivation in education is a critical factor that influences students' attitudes and their success in school. This research looks at how academic motivation affects educational success through a process called mediation analysis. It considers how self-concept and values, which come from motivation, play a role. The study uses the expectancy-value theory of achievement motivation to create a model that explores how motivation and other factors like school bullying, feeling connected to school, and perceptions of teachers interact and affect each other. Mediation analysis helps examine the direct and indirect effects these factors have on student achievement. Data from the trends in international mathematics and science study (TIMSS) for fourth graders in Saudi Arabia is used to see if the theory fits with the experiences of Saudi students. The findings show that self-confidence is crucial for academic performance, affecting students' motivation, readiness to face challenges, and overall learning attitude. However, math attitude does not directly influence self-concept. School bullying is identified as a significant negative factor in math achievement. These outcomes stress the need to address school bullying to improve math scores and highlight the importance of self-concept and motivation in boosting academic success.

The validity of general cognitive ability predicting job-specific performance is stable across different levels of job experience.

Decades of research in industrial-organizational psychology have established that measures of general cognitive ability (g) consistently and positively predict job-specific performance to a statistically and practically significant degree across jobs. But is the validity of g stable across different levels of job experience? The present study addresses this question using historical large-scale data across 31 diverse military occupations from the Joint-Service Job Performance Measurement/Enlistment Standards Project (N = 10,088). Across all jobs, results of our meta-analysis find near-zero interactions between Armed Forces Qualification Test score (a composite of math and verbal scores) and time in service when predicting job-specific performance. This finding supports the validity of g for predicting job-specific performance even with increasing job experience and provides no evidence for diminishing validity of g. We discuss the theoretical and practical implications of these findings, along with directions for personnel selection research and practice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development of inhibitory control in Head Start children: Association with approaches to learning and academic outcomes in kindergarten

Inhibitory control (IC) and Approaches to Learning (AtL) are two critical domain-general indicators of school readiness that develop rapidly in early childhood and are associated with children's academic outcomes. IC undergoes rapid developmental changes between the ages of 3 and 5, and more studies are needed to examine this change over time. AtL describes how children learn in a classroom, and as such, it may mediate the relationship between IC and academic outcomes. AtL may mediate the relationship between IC and academic achievement for children; growth in IC supports children's ability to direct attention to teachers and peers during interactions, while AtL helps children persist and seek learning opportunities during interactions. Using the Age 3 cohort from the Head Start Family and Child Experiences Survey 2009 (FACES 2009), a latent growth curve analysis was used to examine how both the initial level and growth of IC in HS years to kindergarten were associated with children's academic outcomes in kindergarten as well as the potential mediational role of AtL. The intercept and slope of IC were found to predict children's abilities in AtL, language, and math scores in kindergarten. Moreover, AtL was identified as a mediator between the development of IC and the subsequent gains in math skills from Head Start to kindergarten. These findings underscore the significance of fostering IC development before children enter kindergarten, with AtL emerging as a crucial factor influencing their achievements in mathematics.

DOES THIS MEAN WE GET AN A? CAUSAL IMPLICATIONS OF CHANGES IN SCHOOL ACCOUNTABILITY

Many states and districts in the United States use school report cards to share accountability data in which K–12 schools are rated on a variety of metrics, including test scores, which create a categorical grade or rating. These report cards are shared with the public as a mechanism of school accountability and in the process of school choice. This paper explores the causal impact of a school report card used by the New York City Department of Education which was not attached to specific rewards and/or sanctions. I use a regression discontinuity approach to analyze the impact of receiving a lower rating. I find that just receiving a low rating leads to an increase in Math score growth in comparison to similar schools just beyond the cut point, although no such effect is found in English score growth. I also explore implications in the context of school/district policy and leadership.