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AbstractThis paper investigates the level of LGBT+ representation among staff and students in higher education in England and Wales. We compare data from the 2021 England and Wales Census to Higher Education Statistics Agency (HESA) data. We find that LGBT+ people are more highly represented in higher education among all staff groups and students than in relevant comparator groups according to age and educational level in the general population. LGBT+ representation among students and STEM academics is modestly higher than the general population comparator group, while representation among non-STEM academics is substantially higher than one would expect from the general population comparator group. We found no statistically significant under-representation in any particular higher education institution. [ABSTRACT FROM AUTHOR]

In Japan, standards have been established for curricular organization. The latest standards mention the enrichment of inquiry, statistical education, and active use of ICT. We focus on the enrichment of statistical education in inquiry and describe a case study of problem research, one of the educational activities in the SSH project (Super Science High School), a national project to promote science and mathematics education, and problem study in the required course "Mathematics I." Based on this discussion, we propose future directions for statistical education and the use of ICT. Based on this discussion, we propose the future direction of statistics education and the use of ICT. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An investigative project can engage the learner in all aspects of a statistical investigation, including developing a question or issue of interest, gathering needed information, exploring the data, and communicating the results. This article summarizes the available literature regarding the implementation of investigative projects, including the potential benefits of projects, how projects have been used in a variety of settings, advice for those looking to implement projects, and future research avenues. [ABSTRACT FROM AUTHOR]

This paper provides a snapshot of United States academic libraries in 2020 and explores longitudinal trends in staffing and expenditures for 1996 to 2020. The authors merged and analyzed academic library data from the National Center for Education Statistics from over 4,000 postsecondary institutions. Characteristics are explored by region and maps are provided. Total inflation-adjusted library expenditures have increased steadily for all regions from 1996 to 2020, including in the two major expenditure categories of staffing and collections. In the Northeast and West, averages are markedly higher in staffing and total expenditures than the other two regions. [ABSTRACT FROM AUTHOR]

Hispanic‐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. [ABSTRACT FROM AUTHOR]

We report on a course project in which students submit weekly probabilistic forecasts of two weather variables and one financial variable. This real-time format allows students to engage in practical forecasting, which requires a diverse set of skills in data science and applied statistics. We describe the context and aims of the course, and discuss design parameters like the selection of target variables, the forecast submission process, the evaluation of forecast performance, and the feedback provided to students. Furthermore, we describe empirical properties of students' probabilistic forecasts, as well as some lessons learned on our part. [ABSTRACT FROM AUTHOR]

This study develops statistical learning models to assess the probability of undergraduate students graduating within a predetermined period, utilizing admission, performance, and demographic data. The urgency of addressing student attrition is highlighted by recent data from the National Center for Education Statistics (NCES), indicating a 59% completion rate by full-time undergraduates within six years. This research leverages institutional data from a Saudi University, focusing on freshmen enrolled in the 2012-2013 and 2013-2014 academic years, to identify students at risk of dropping out, thereby enabling timely interventions. Ten algorithms, including decision trees, ensemble models, SVM, and ANN, were built and evaluated on a test set representing 33.3% of the entire dataset using precision, recall, accuracy, and Matthews correlation coefficient (MCC). The findings show that SVM and Random Forest models were the most reliable, achieving accuracies of 0.830 and 0.831 respectively, and maintaining balance in precision, recall, and MCC. Conversely, the naïve Bayes model recorded the worst performance. The comparative analysis revealed the superior performance of ensemble models over decision tree models in predicting student attrition, emphasizing the importance of model selection in developing effective early intervention strategies. In addition, our analysis revealed that academic data is a better predictor of ontime graduation than admission data, emphasizing the need for institutions to focus on continuous academic assessment data. [ABSTRACT FROM AUTHOR]

Using data from the U.S. Department of Education National Center for Education Statistics Integrated Postsecondary Education Data System (IPEDS), longitudinal trends in graduate degree completion rates for Hispanic and White students were analyzed over a period of 17 years (2002–2019). The results indicated that there was a significant positive linear trend in graduation rates for both Hispanic and White graduate students, with no adverse impact in graduate degree completion rates for Hispanic students when compared to White students. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic altered course delivery in higher education at many universities. This article evaluates the differences between student experiences in the fall 2019 semester (pre-pandemic) and those during the fall 2020 semester (pandemic) within a multidisciplinary, project-based introductory statistics course. Results indicated that there were minimal differences in student experiences of this course based on delivery mode (in person vs. online). [ABSTRACT FROM AUTHOR]

As the use of data in courses that incorporate statistical methods has become more prevalent, so has the need for tools for working with such data, including those for data creation and adjustment. While numerous tools exist that support faculty who teach statistical methods, many are focused on data analysis or theoretical concepts, and there remains a need for tools that assist faculty when making data-based examples and assignments. In this article, we describe a free application, available both online and through an R package, which we developed for instructors of courses that incorporate introductory statistical methods. The app treats the process of coming up with data for examples and assignments synergistically, beginning with either data creation (through random number generation) or adjustment (when the user has data) and ending with an assessment of the data's suitability for the desired analysis. The app enables the quick creation of many versions of variables for multiple versions of assignments and is compatible with file types associated with popular interdisciplinary software such as Excel, R, and SPSS. We highlight the app's features and discuss survey feedback provided by faculty that demonstrates the desire and need for and effectiveness of such an app. for this article are available online. [ABSTRACT FROM AUTHOR]

In 2003, the Department for Education in England commissioned research which supported the policy drive to reduce the reliance on statements for special educational needs (SEN). Twenty years on and the government's emphasis has now switched from reducing workload to creating financially sustainable systems. There continues to be wide variations in local authority (LA) statutory assessment practice, with considerable differences in the proportion of pupils with education, health and care plans (EHCPs), even when benchmarked across demographically comparable authorities. LAs with low EHCPs have smaller high needs block (HNB) budgets but typical rates of special needs and disability (SEND) Tribunal appeals. A comparison is also made of the statutory assessment process within the four nations of the UK. The discussion considers the implications of the findings for sustainable high needs systems and for appropriately managing the demand for EHCPs. The current 25-year trendline is projecting towards 10% EHCPs by 2042, a remarkable increase from 2.5% in 2017. [ABSTRACT FROM AUTHOR]

The meaning of randomization tests has become obscure in statistics education and practice over the last century. This article makes a fresh attempt at rectifying this core concept of statistics. A new term—"quasi-randomization test"—is introduced to define significance tests based on theoretical models and distinguish these tests from the "randomization tests" based on the physical act of randomization. The practical importance of this distinction is illustrated through a real stepped-wedge cluster-randomized trial. Building on the recent literature on randomization inference, a general framework of conditional randomization tests is developed and some practical methods to construct conditioning events are given. The proposed terminology and framework are then applied to understand several widely used (quasi-)randomization tests, including Fisher's exact test, permutation tests for treatment effect, quasi-randomization tests for independence and conditional independence, adaptive randomization, and conformal prediction. for this article are available online. [ABSTRACT FROM AUTHOR]

The present study illustrates how select data can be organized to guide researchers to HSIs proficient at graduating Hispanics with STEM bachelor's degrees to investigate best practices that less proficient HSIs can adopt for program improvement. The Integrated Postsecondary Education Data System (IPEDS) from the National Center for Education Statistics (NCES) was the data source. The primary analytic consisted of the scatterplot, supplemented by Pearson correlation r and regression analysis. While the findings failed to support the Hispanic undergraduate Pell rate as an explanatory variable for Hispanic STEM degree production capacity as the response variable, in a new light, the findings were an ideal model for initiating best practices research. Guidelines on initiating a "thousand word" discourse on best practices among HSI stakeholders, common defining moments one should anticipate at site visits, as well as the limitations and assumptions of the approach are presented. Based on the data, if low performing HSIs met the minimum benchmark level identified, the model predicted an increase of 17,392 or 50.7% additional Hispanics with STEM degrees for the US academic, technical, and professional workforce. [ABSTRACT FROM AUTHOR]

The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE pedagogy, and provide five perspectives on the subject: one from each of the authors as well as a composite profile derived from a survey of DOE instructors. Our work provides a snapshot of current DOE pedagogy that showcases both the similarities and variety in how the subject is taught, as well as a look ahead at how its instruction may evolve. for this article are available online. [ABSTRACT FROM AUTHOR]

Over the last several decades, "zero-tolerance" policies have been implemented by federal, state, and local educational systems, which have altered the culture of learning. A consequence of this "tough on education" culture is what some scholars have called the "school-to-prison-pipeline" which disproportionately impacts students of color. By using a national representative sample of Latinx students from the National Center for Education Statistics' (NCES) High School Longitudinal Study (HSLS), and intersectionality as a theoretical framework, this paper examines the relative impact of parent-level variables, student-level variables, and key demographics on in-school suspension. That relationship is further interrogated separately for Latinx students below and above the Federal poverty line. Findings indicate that Latinx males living in poverty and Latinx students who are above the poverty line, who attend public schools, are more likely to receive in-school suspension. This suggests that structural inequities of discriminatory practices might play a larger role in secondary schools' disciplinary procedures. [ABSTRACT FROM AUTHOR]

Statistics education at all levels includes data collected on human subjects. Thus, statistics educators have a responsibility to educate their students about the ethical aspects related to the collection of those data. The changing statistics education landscape has seen instruction moving from being formula-based to being focused on statistical reasoning. The widely implemented Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report has paved the way for instructors to present introductory statistics to students in a way that is both approachable and engaging. However, with technological advancement and the increase in availability of real-world datasets, it is necessary that instruction also integrate the ethical aspects around data sources, such as privacy, how the data were obtained and whether participants consent to the use of their data. In this article, we propose incorporating ethics into established curricula and integrating ethics into undergraduate-level introductory statistics courses based on recommendations in the GAISE Report. We provide a few examples of how to prompt students to constructively think about their ethical responsibilities when working with data. [ABSTRACT FROM AUTHOR]

Background: Generalisation inferences let readers identify a conceptually superordinate statement to represent multiple subordinate concepts. This study measures text genres' influence on the scope and timing of generalisation inferences. Methods: To measure the scope, or breadth, of generalisation inferences, undergraduates (N = 266) read expository and literary texts containing target sentences that were consistent, inconsistent or off‐topic in relation to the generalisation implied in each paragraph. To test when the generalisations were inferred, target sentences were placed either early or late in each paragraph. Results: Readers drew broad generalisations early in the text and changed to specific generalisations later for exposition. The generalisations inferred from fairy tales were specific regardless of whether tested early or later in the text. Conclusions: Readers construct generalisation inferences while reading both expository and literary texts, although the timing and scope of the inferences vary slightly by genre. Implications for theories of reading comprehension and applications for reading interventions are discussed. Highlights: What is already known about the topic Readers infer superordinate concepts, or generalisations, as they read.Inferring generalisations is important for reading comprehension.Text genre affects reading behaviours, including inference construction. What this paper adds This study investigated how genre affects the scope, or breadth, of generalisation inferences and the timing of those inferences.Readers' inferences for expository texts began as broad but became specific as the text continued but were always specific for literary texts.Readers began drawing the inferences while reading, as opposed to after reading. Implications for theory, policy or practice Although readers often struggle to identify the main point of a text, these results suggest readers begin to find connections between ideas within paragraphs very early in the text.Readers reacted to inconsistent information differently in literary versus expository texts, suggesting continued instruction of genre‐specific reading strategies is appropriate. [ABSTRACT FROM AUTHOR]

Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye‐tracking research as an example, background information on eye‐tracking and possible applications of eye‐tracking in statistics education is provided. Teachers indicated that our eye‐tracking research created awareness of the difficulties students have when interpreting histograms. Gaze data showed details of students' strategies that neither teachers nor students were aware of. With this discussion paper, we hope to contribute to the future usage and implementation of gaze data in statistics education by teachers, researchers, educational and textbook designers, and students. [ABSTRACT FROM AUTHOR]

In recent years, big data has become ubiquitous in our day‐to‐day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and nontraditional big data investigation activities. We first suggest a theoretical framework based on integrated insights from statistics education and data science to analyze and describe novices' reasoning with the various uncertainties that characterize both traditional and big data—the Variability, Data, and Phenomenon (VDP) framework. We offer a case study of graduate students' participation in the integrated modeling approach (IMA) learning trajectory, illustrating the utility of the VDP framework in accounting for the different types of articulated uncertainties. We also discuss the teaching implications of the VDP. [ABSTRACT FROM AUTHOR]

This study compared the effectiveness of teaching a distance education statistics course using a computer‐aided personalized system of instruction (CAPSI) in comparison to a distance education course that used video lectures. Data were collected between 2017 and 2022. Two‐hundred and sixty‐eight students were included in the sample. Results supported that students enrolled in the CAPSI statistics course were less likely to drop out of the course and mastered significantly more material than students enrolled in the lecture‐based distance education course. It is recommended that instructors teaching statistics in distance education settings consider using CAPSI to improve student outcomes. [ABSTRACT FROM AUTHOR]

This study examines whether community-level social disorganization and community engagement initiatives are associated with public high school performance. Analyzing data from the National Center for Education Statistics (NCES) School Attendance Boundary Survey (SABS), a latent variable measuring community-level social disorganization is examined within a structural equation model for 302 traditional public high schools in Florida. The study finds a statistically significant and large negative association between community-level social disorganization and a latent variable representing Florida Department of Education performance metrics. Correspondingly, the recognition of receiving the Florida Five Star School award for satisfying recommended community engagement criteria is positively associated with high school performance with social disorganization factors simultaneously considered. This research hopes to further provide an emphasis for recognizing and engaging community within the context of addressing disparities in public education performance. [ABSTRACT FROM AUTHOR]

A common conclusion drawn from publicly available Higher Education Statistics Agency (HESA) data releases is that Higher Music Education (HME) courses have a predominantly male population. However, HESA data has key issues when examining HME courses: which courses are reported as 'music' courses to HESA; how do universities decide which courses are 'music' courses; how many different topics are contained within the umbrella of 'music' courses? To address questions of gender representation in HME, universities in the UK were approached with Freedom of Information Act requests for the gender demographics of student populations on "music-related" courses. Information was gained on 3456 courses populations between 2014 and 2020, which was categorised by the subject of study. Six core undergraduate topics were identified: generic music degrees (female bias), degrees combining music and technology (male bias), degrees combining music and business (no gender bias), degrees on popular music (male bias), degrees combining music and theatre (female bias) and major conservatoire courses (no gender bias). No area was accurately represented by HESA data, and gender representation varied significantly between areas. These findings have implications for discussions of gender representation in HME across the UK. [ABSTRACT FROM AUTHOR]

In recent years, the adjunct faculty phenomenon has grown steadily. This research focused on adjunct instructors teaching introductory statistics courses. The purpose of the study was to give a voice to adjunct instructors by allowing them to describe their experiences teaching statistics. We conducted a qualitative study with 15 adjunct instructors of introductory statistics through semi-structured interviews. The participants came from several fields:psychology, nursing, and business, among others. Thematic analysis was used to find themes of statistical anxiety, use of technology in the classroom, lack of curriculum flexibility, and connection to the host institution. Our findings can inform institutions and interdisciplinary departments hosting introductory statistics courses. Similarly, educational statisticians can gain knowledge on the practices and barriers of adjunct instructors. [ABSTRACT FROM AUTHOR]

Gaze data are still uncommon in statistics education despite their promise. Gaze data provide teachers and researchers with a new window into complex cognitive processes. This article discusses how gaze data can inform and be used by teachers both for their own teaching practice and with students. With our own eye‐tracking research as an example, background information on eye‐tracking and possible applications of eye‐tracking in statistics education is provided. Teachers indicated that our eye‐tracking research created awareness of the difficulties students have when interpreting histograms. Gaze data showed details of students' strategies that neither teachers nor students were aware of. With this discussion paper, we hope to contribute to the future usage and implementation of gaze data in statistics education by teachers, researchers, educational and textbook designers, and students. [ABSTRACT FROM AUTHOR]

In recent years, big data has become ubiquitous in our day‐to‐day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and nontraditional big data investigation activities. We first suggest a theoretical framework based on integrated insights from statistics education and data science to analyze and describe novices' reasoning with the various uncertainties that characterize both traditional and big data—the Variability, Data, and Phenomenon (VDP) framework. We offer a case study of graduate students' participation in the integrated modeling approach (IMA) learning trajectory, illustrating the utility of the VDP framework in accounting for the different types of articulated uncertainties. We also discuss the teaching implications of the VDP. [ABSTRACT FROM AUTHOR]

Using national data from the National Center for Education Statistics 2011–2012 Schools and Staffing Survey and Common Core of Data, we examined the relationship between K–12 practitioners' risk for stress and the teacher-to-student racial/ethnic congruence. Analyses indicated significant variation in risk for stress by school racial composition and suggested that the likelihood of being categorized as most at-risk for stress is associated with the teacher-to-student racial/ethnic congruence. Findings point to substantial differences in how teachers appraise their environments depending on school context, which has implications for how education stakeholders recruit and prepare classroom practitioners. [ABSTRACT FROM AUTHOR]

Empirical likelihood is widely used in many statistical problems. In this article, we provide a review of the empirical likelihood method, due to its significant development in recent years. Since the introduction of empirical likelihood, variants of empirical likelihood have been proposed, and the applications of empirical likelihood in high dimensions have also been studied. It is necessary to summarize the new development of empirical likelihood. In this article, we give a review of the Bayesian empirical likelihood, the bias‐corrected empirical likelihood, the jackknife empirical likelihood, the adjusted empirical likelihood, the extended empirical likelihood, the transformed empirical likelihood, the mean empirical likelihood, and the empirical likelihood with high dimensions. Finally, we have a brief survey of the computation and implementation for empirical likelihood methods. This article is categorized under:Applications of Computational Statistics > Education in Computational Statistics [ABSTRACT FROM AUTHOR]

This quasi-experimental study examines the effect of short instruction videos on students' business statistics learning. Two hundred and thirty-one Dutch students attended 6-week online seminars on Business Statistics. One hundred and nineteen students were in an experimental group, and 112 in a control group. Students in the experimental group watched short instructional videos and studied online quizzes at their own pace. In the control group, students followed teachers' instructions throughout the seminars. It was found students watching short videos significantly outperformed those following teachers' virtual instruction. Short videos were especially useful for those who were good at math. The research sheds light on the design of hybrid learning, particularly for business statistics education at the university level. A quasi-experimental research to examine the effects of short instructional videos on students' statistics learning performance vs. the virtual lectures with teachers. Evidence of the benefits of short videos in statistics education for students who are good at math. Practical experiences sharing for designers of instructional videos. Recommendations for creating short instructional videos in higher education. [ABSTRACT FROM AUTHOR]

Being a teacher or a student in a class with a large enrollment can be intimidating. Often, teachers view comforts that are common to small classes as unattainable in a larger class, including knowing students' names, using active learning, employing group work, and creating group discussion. Students in large classes may find that the class size leads to isolation. At Utah State University, we offer introductory statistics classes for various audiences using a large lecture format. The authors have collectively led these large lectures dozens of times and found that, despite its shortcomings, the large lecture format can be an asset when teaching statistics. With an active learning approach such as recommended by the revised GAISE College report, large class sizes permit realistic sampling, facilitate student-driven simulation, and provide bountiful opportunities for experimentation. In this article, we discuss the benefits of large classes for statistics teaching and present examples of using large class sizes to create an engaging environment that where students are involved in active learning and collecting real data to foster statistical thinking. [ABSTRACT FROM AUTHOR]

In K–12 statistics education, there is a call to integrate statistics content standards throughout a mathematics curriculum and to teach these standards from a data analytic perspective. Annotated lesson notes within a lesson plan are a freely available resource to provide teachers support when navigating potentially unfamiliar statistics content and teaching practices. We identified several types of annotated lesson notes, created two statistics lesson plans that contained various annotated lesson notes, and observed secondary mathematics teachers implement the lesson plans in their intermediate algebra courses. For this study, we qualitatively investigated how two teachers' instructional actions compared to what was prescribed in the annotated lesson notes. We found ways in which the teachers' instructional actions, across their differing contexts, aligned with, varied from, or adapted to the annotated lesson notes. From these results, we highlight affordances and limitations of annotated lesson notes for statistics instruction and offer recommendations for those who create statistics curricula with annotated lesson notes. [ABSTRACT FROM AUTHOR]

Course coordination implies coordination in the design, structure, and teaching of a course to the extent that multiple instructors within a multi-section course have come to a common agreement. The course coordination model within our college's Department of Mathematics is described and discussed. The outcomes experienced as the department moved towards course coordination, particularly how and why the introductory statistics course was transformed into a coherent multi-section course, the need for course coordination, and the level of coordination implemented are the focus. Similarities between our course coordination model and traditional Faculty Learning Communities are addressed. Student grades data are analyzed. [ABSTRACT FROM AUTHOR]

Employing a statistical modeling inspired pedagogy is becoming a widespread practice in the statistics education community. Many have incorporated the practice of formulating conjectures in their modeling-enhanced educational designs and have reported on its benefits. We further elucidate the mechanism through which students' conjecturing may be beneficial, in particular to their emergent reasoning with informal statistical models and modeling, as well as examine what challenges it may entail – the double-edged sword of conjecturing. We introduce a framework to describe young learners' reasoning with informal statistical models and modeling (RISM), in which students' conjecturing is represented as one of two parallel planes of model creation and refinement. We offer a case study of a pair of students' participation in an integrated modeling learning sequence, including both real-world modeling tasks and probability-world modeling tasks. The pair was chosen as both students held strong, opposing real-world conjectures. Our goal is to elucidate the roles these conjectures can play, for better or for worse, to fully harvest the pedagogical potential of conjecturing. [ABSTRACT FROM AUTHOR]

Background/Context: Career and technical education (CTE) coursework in science, technology, engineering, mathematics, and medical/health (STEMM) fields has been supported by policy makers as a way to align the secondary-to-postsecondary-to-career pipeline. Yet, in the research, the focus has been on whether STEMM CTE coursetaking in high school predicts college-going or whether it predicts employment for non–college goers. Little attention has been paid to whether STEMM CTE coursetaking in high school aligns with college employment opportunities. Purpose/Objective/Research Question/Focus of Study: This study investigates the relationship between one promising educational practice—STEMM career and technical education (STEMM CTE) coursetaking—and outcomes along students' college employment pathways. Specifically, we asked the following research questions: Does taking more STEMM CTE courses in high school link to "general" college employment outcomes? Does taking more STEMM CTE courses in high school link to "STEMM-specific" college employment outcomes? How do these relationships vary across important student subgroups, namely, those identified by the National Science Foundation as traditionally underrepresented in STEMM fields: low-income students, students with learning disabilities, women, and Black and Hispanic students? Research Design: We relied on data from the High School Longitudinal Study of 2009 (HSLS). Administered by the National Center for Education Statistics (NCES), HSLS is the most current, nationally representative data set that follows a cohort of more than 20,000 ninth-grade students across the United States throughout high school and after graduation. Our regression analyses relied on data collected during the baseline year school-level survey (2009), the high school transcript update (2013), and student-level surveys from all four data-collection waves (2009, 2012, 2013, 2016). Conclusions/Recommendations: Using these national data, we find that taking more STEMM CTE courses was associated with a higher chance of having a STEMM job during college and having higher expectations for future STEMM employment, though not with general employment outcomes such as wages. The findings were different for students from some underrepresented backgrounds in STEMM fields, and implications are discussed. [ABSTRACT FROM AUTHOR]

Background/Context: The sense of belonging to a school is important for students, in terms of various short- and long-term developmental and academic outcomes. The inequities in the sense of school belonging among Asian American and Pacific Islander (AAPI) students may reveal a severe lack of opportunities or serious process gaps for these students. Purpose/Objective: This study investigated the nuances and complexities involved in the sense of school belonging among AAPI students in U.S. high schools, and particularly how such perceptions relate to various demographic characteristics (i.e., ethnicity, gender, socioeconomic status, and immigration status) and their intersectionalities. The study disaggregated this group into subgroups based on their ethnicities, with the aim of challenging the model minority stereotype that generalizes the experiences of AAPI students. Research Design: This study used base-year data of the High School Longitudinal Study of 2009 (HSLS:09) provided by the National Center for Education Statistics (NCES). Linear mixed-effects modeling was used to analyze a nationally representative sample. Multiple statistical interaction terms were used to identify the specific contributions (intersectionality) of AAPI students' converging demographic characteristics. Findings/Results: This study found that the sense of school belonging was stronger for South Asian students and weaker for East Asian students when compared to the overall level, with other demographic characteristics held constant. The intersectionality model using disaggregated data revealed that the convergence of AAPI students' ethnicity and gender creates additional nuances in their sense of school belonging, particularly for Southeast Asian and East Asian students. Conclusions/Recommendations: The findings support the call for more accurate narratives and a deeper understanding of intersectionality among AAPI students. The study suggests to policymakers and school leaders that a universal strategy for encouraging students' sense of school belonging may not effectively address the nuanced intersectional disparities that AAPI students experience. Instead, the intersection of students' ethnicity and gender indicates that responsive strategies that address their unique needs can better promote their perceptions of belonging to their schools. [ABSTRACT FROM AUTHOR]

This article describes the experience of participants and facilitators engaging in a psychoeducational group counseling intervention designed to enhance college readiness among Latine first-generation college-going students—those for whom neither parent completed college (National Center for Education Statistics, 2017). The group was designed to increase students' understanding of how their various identities impacted their college preparatory experience and willingness to seek help. Findings suggest that participants recognized the importance of their identities and the way they influenced their help-seeking behaviors. Participants identified similarities among their experiences related to college going while also valuing learning from each other's differences. Last, participants felt a sense of uncertainty and angst about going to college. We also share facilitator experiences. [ABSTRACT FROM AUTHOR]

This study examines the effects of gentrification on exclusionary punishment in urban schools across the United States. Integrating longitudinal data from the National Center for Education Statistics, the Civil Rights Data Collection, the U.S. Census, and the American Community Survey, this study estimates the effects of gentrification on suspensions, expulsions, law enforcement referrals, and school arrests through a series of negative binomial regression models. Results indicate that gentrification does not have broad or striking influences on school disciplinary environments overall, but it does promote modest increases in out-of-school suspensions as well as racial disparities in suspensions. Little evidence is found that effects vary by sex, grade level, or school racial composition. A battery of sensitivity analyses suggests that overall findings are generally robust to the presence of unobserved confounding and are broadly consistent across alternative model specifications and different measures of gentrification. [ABSTRACT FROM AUTHOR]

The School Librarian Investigation—Decline or Evolution? (SLIDE) project is a federally funded study of the almost 20% national decline in the number of full-time equivalents (FTEs) of school librarians between 2015 and 2019, according to the National Center for Education Statistics. In this update to the project's original research, school librarian employment data for the 2020-2021 school year were examined for 12,537 school districts and associated with district characteristics (poverty, locale, and district enrollment) and student demographics (race and ethnicity). Data supported previous findings that access to school librarians is strongly related to race and ethnicity and further exacerbated for students living in extreme poverty, in more-isolated locales, and in the smallest districts—locales where students are less likely to have access to the educational resources available in large urban areas. In school year 2021, 3 million students in majority nonwhite districts were without any librarians; they were 54% of the 5.6 million students in all districts without any librarians during the COVID-19 pandemic. The gap between students in districts with a "library privilege" and those without librarians continues to widen. [ABSTRACT FROM AUTHOR]

The study aimed to develop a proposed vision for developing the content of statistics in the basic education stage in the light of NCTM standards. To achieve this, the researchers used the analytical descriptive approach and the structural descriptive approach. The researchers prepared an analysis tool consisting of (4) main criteria and (10) sub-criteria derived from the list of statistics and probabilistic content criteria for the third cycle (6-8) issued by (NCTM, 2000). It was used to analyze the content of the field of statistics and probability from the mathematics curriculum document for grades (7-9) of the basic education stage, as well as the topics of statistics and probability from mathematics books for grades (7-9). For the academic year (2021/2022 AD), and after verifying the stability of the analysis using the comprehensive equation, the researchers conducted the analysis procedures using frequencies, percentages, and the arithmetic mean. The results of the analysis showed that the degree of availability of the NCTM standards for the field of statistics and probability was medium in the first and second standards, and almost non-existent in the third and fourth standards. Based on the results, a proposal was developed to develop the content of statistics and probability for grades (7-9) of the basic education stage in the light of the NCTM standards. It contains learning outcomes, vocabulary, mathematical operations, instructions and examples. In light of the results, the study presented a number of recommendations, most notably the need to develop statistics and probability courses in basic education in the light of (NCTM) standards, and the need to benefit from the successful experiences of the countries on which they are based. They are based. They were standing. On the philosophy of standards in developing mathematics curricula, enriching the content of statistics and probability with applied functional activities related to life. The process contributes to increasing awareness of the realities of life, such as: demographic, economic and biological aspects. [ABSTRACT FROM AUTHOR]

In this experiment, we recruited 261 psychology faculty to determine the extent to which they were able to visually estimate the overlap of two distributions given a Cohen's d effect size; and vice-versa estimate d given two distributions of varying overlap. In a pre-test, participants in both conditions over-estimated effect sizes by half a standard deviation on average. No significant differences in estimation accuracy by psychology sub-field were found, but having taught statistics coursework was a significant predictor of better performance. After a short training session, participants improved substantially on both tasks on the post-test, with 63% reduction in absolute error and negligible overall bias (98% bias reduction). Furthermore, post-test performance indicated that learning transferred across answering modes. Teachers of statistics might find it beneficial to include a short exercise (less than 10 minutes) requiring the visual estimation of effect sizes in statistics coursework to better train future psychology researchers. [ABSTRACT FROM AUTHOR]

The article discusses the effects of performance statistics in the field of education. It emphasizes that optimizing the performance of the school system and students is of great importance. The text examines the imperatives of performance statistics in three sections: Faster, Higher, and Stronger. It is pointed out that these logics contradict a communal effort towards performance optimization. The article also discusses the influence of performance optimization and competitive thinking in the school sector and raises the question of whether these impair the communal nature of performance and isolate individuals. [Extracted from the article]

Online learning is extremely prevalent in education, more than ever given the COVID-19 pandemic that has shifted most educational services to an online platform. More specifically, in 2015, close to six million students were taking at least one online learning course, which was 29.7% of all postsecondary students (U.S. Department of Education, National Center for Education Statistics 2018). In 2017, the Online Learning Consortium reported an almost 4% increase in online learning students in 2015 as compared to the previous two years. Although online learning is becoming more prevalent, there has been little to no research to determine what makes online learning most effective. Those that have, either have not compared modalities (i.e., only testing one format) (Sella et al. 2014; Walker and Rehfeldt 2012) or have focused on another aspect of the learning (e.g., does grading anonymously affect performance) (Liu et al. 2018). Determining the components of online learning that lead to better student outcomes will add to the current literature and improve online learning as a whole. The primary purpose of this experiment was to determine what forms of discussion (synchronous vs asynchronous) are most effective in an asynchronous online master-level applied behavior analysis course. [ABSTRACT FROM AUTHOR]

The results of the study made it possible to answer the question of what the use of infographics is like, as well as the literacy of statistical skills. For this purpose, experimental actions were carried out in 78 university students of the Faculty of Education; Two groups enrolled in the subject of Statistics Applied to Education were accessed. The experience consisted of the students constructing infographics with contents, concepts and description of statistical tables and figures to later detect their effect on statistical skills. For the reasons stated, the study is of an applied type and explanatory level. The experimental actions led to the conclusion. The use of infographics allowed the literacy of statistical competencies in terms of the acquisition of skills for reading and interpreting data, drawing conclusions from journalistic texts, detecting comparative statistics between both groups (8.21; +-2.47) compared to the group experimental (18.21; +- 1.27) and (p_value <0.05). Statistical reasoning consisted of reasoning the text in relation to statistical reports; finally, in the statistical thinking competition, they were able to make inferences from the data presented in the infographic; however, the statistical thinking competence presents the lowest percentage of achievement compared to the other two, which we deduce that people lack in detecting sources of information and performing critical analysis, in addition to assuming with logical criteria in front of the data; however, it shows statistical significance comparatively. [ABSTRACT FROM AUTHOR]

Context is a key element in statistics education. The objective of this study is to examine the capacity of 14- and 15-year-old students to work with real data, analyse statistical graphs and frequency tables and interpret statistical data in its context. The results of the descriptive, exploratory analysis show that most students were correctly able to analyse and interpret data presented through statistical graphs and tables. However, some students had difficulties when it came to identifying the represented variables. More difficulties arose when calculating and interpreting means and medians — generally produced from the use of class midpoints — and making decisions. Students made little use of the context the data were presented in. Results reinforce the importance of using context in the teaching of statistics, encouraging justified decision-making. [ABSTRACT FROM AUTHOR]