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While current higher education literature stresses the importance of equity, diversity, and inclusivity, these imperatives have been mainly absent from conversations related to boards of higher education. In this paper, the authors present a historical overview of the demographic landscape of trustee boards from inception to the present. Using critical literacy as a methodology, the authors problematize the lack of discourses regarding Board's diversity. The authors juxtapose the longstanding homogeneity of boards with the increasing heterogeneity of higher education students and argue that systemic forms of racism have denied the opportunity to diversify those in charge of making decisions in higher education. Additionally, using the case of California, the authors problematize how diversity gaps in board composition manifest even within one of the most diverse and liberal states in the country. Ultimately, the authors make a case for diversifying the board of trustees as an instrumental step to align with the national push for enhanced diversity and equity in higher education.

This paper reviews overall student performance as well as the performance of student subgroups on the assessment system developed in response to the Massachusetts Education Reform Act of 1993 (MERA), the Massachusetts Comprehensive Assessment System (MCAS). Comparing students in Massachusetts to students in the rest of the United States or against students in other countries can not only confirm the rigor of the MCAS, but the comparison can also provide meaning to MCAS scores and ensure that they accurately measure student performance. There are two primary international exams given at regular intervals: (1) the Trends in International Math and Science Study (TIMSS); and (2) the Program for International Student Assessment (PISA). The strong performance on the international exams across several years and subjects, especially on TIMSS, confirmed the quality of Massachusetts K-12 schools.

More than half of states have implemented tuition-free college policies aimed at reducing attendance costs and incentivizing enrollment. We review the academic literature on the design features and impacts of these tuition-free policies, and we analyze an initiative Virginia implemented in 2021 called Get a Skill, Get a Job, Get Ahead (G3), which provides tuition-free community college to students enrolled in eligible associate degree, certificate, and noncredit occupational training programs in five high-demand fields. Our descriptive analysis of G3 from 2016-17 through 2022-23 shows that both institutions and students responded to the tuition-free messaging and eligibility criteria. Specifically, G3-eligible institutional program offerings and student enrollment in such programs both increased by roughly 30% within the first two years of program implementation. While Virginia's tuition-free policy promotes enrollment in targeted occupational programs, overall enrollment effects are partially offset by a 3% enrollment reduction in aid-ineligible transfer-oriented programs. To promote skill development and improve labor market outcomes, policymakers should ensure that programs eligible for tuition-free college include pathways to longer term credentials.

Student service member/veteran (SSM/V) university enrollment has grown exponentially in recent years. In response, many U.S. universities have developed military-focused student services to address navigational and social challenges SSM/Vs face on campus. While research suggests these services are beneficial, few studies have empirically examined how often contemporary SSM/Vs engage with them across universities, how engagement connects to predictors of university success, or how SSM/Vs describe such connections. Using social capital theory, surveys (n=531), and interviews (n=59) of SSM/Vs across four universities, we analyze SSM/V military-focused service engagement levels, correlations between engagement and campus belonging and institutional satisfaction, and SSM/V perspectives on engagement. Findings suggest SSM/Vs very rarely engage in these services. Higher engagement, however, is significantly associated with more campus belonging and institutional satisfaction. Interviewees describe how the moral support military-focused service staff offer while providing reliable administrative assistance, as well as SSM/V-dedicated spaces and community building, foster belonging and satisfaction.

In many low- and medium-income countries (LMICs), student-centered pedagogies are often implicitly or explicitly at the heart of innovative pedagogical reforms. In recent years, there has been a growing emphasis on student-centered pedagogies, which aim to shift power dynamics, increase interaction, and prioritize the needs of learners. Many international agencies, governments, and education experts view these pedagogies as "best practices" or a pedagogical "silver bullet" to improve classroom practice. This paper is the second in a series of three working papers meant to serve as references and conversation starters for policymakers and researchers as they navigate pedagogical reform for education system transformation in their local contexts. Together, the three working papers emphasize the need for more locally driven collaborative research on how the interaction of culture, local education ecosystems, and learning theories--collectively called Invisible Pedagogical Mindsets--influences teachers' pedagogical choices in the classroom. This paper details why the authors recommend policymakers examine Invisible Pedagogical Mindsets in their local context to inform pedagogical reforms. The authors discuss the reasons why generalized "best practices"--namely "student-centered pedagogies" as currently implemented--do not often successfully transfer to new cultures, countries, and contexts and argue that many pedagogical reforms do not adequately consider the Invisible Pedagogical Mindsets embedded in each local context.

Although global access to schooling has increased over the last several decades, Sustainable Development Goal 4 (SDG 4), which champions inclusive, equitable, quality education, is far from being achieved. Experts predict that if the global community continues to operate education systems in the same way, by 2030, only one in six countries will reach the universal secondary school completion targets, and approximately 300 million students in school will continue to lack basic numeracy and literacy skills. The 2022 United Nations Transforming Education Summit emphasized the urgent need for a complete overhaul of education systems to meet SDG 4 targets. One significant outcome of the summit was a call to improve student learning by transforming teacher classroom practice. This paper is the first in a series of three working papers meant to serve as references and conversation starters for policymakers and researchers as they navigate pedagogical reform for education system transformation in their local contexts. This paper explores various definitions of pedagogies, the lack of consensus on what pedagogy means in practice, and the effects of Invisible Pedagogical Mindsets on pedagogical approaches.

Since the 1990s, there has been a growing demand for evidence-based education policy and practice. This demand stems from concerns that education systems are not meeting the needs of a changing world and that education research lacks rigor. While this demand aims to improve the quality of education, silos between different actors often hinder how evidence informs policymaking. We encourage researchers to use a collaborative research approach by involving multiple education actors in the research process to close the gaps between research, policy, and practice. This paper is the third in a series of three working papers meant to serve as references and conversation starters for policymakers and researchers as they navigate pedagogical reform for education system transformation in their local contexts. Together, the three working papers emphasize the need for more locally driven collaborative research on how the interaction of culture, local education ecosystems, and learning theories--collectively called Invisible Pedagogical Mindsets--influences teachers' pedagogical choices in the classroom. Primarily intended for education researchers, Working Paper III advocates the use of collaborative research approaches to actively include multiple education actors in the research process, foster complementary relationships between actors with different expertise, and make research findings more relevant and responsive to the local education ecosystem. The paper has three parts that discuss the need for flexible research approaches to inform policy given the complexities of education decision-making, the importance of communication and dissemination, and how collaborative research can bridge the gaps between research, policy, and practice. The paper concludes by looking at the ongoing work of the SPARKS project at the Center for Universal Education and how collaborative research can contribute to education systems transformation.

This paper presents a rationale for using professional and continuing education (PaCE) units at post-secondary institutions throughout California to design and implement talent-pipelines, research and development collaborations, and other knowledge ecosystems where emerging and returning professionals can acquire the knowledge, skills, and abilities (KSAs), as well as the experience, they need to address the challenges of the Fourth Industrial Revolution (4IR). The paper provides an analysis of the reasons why PaCE units are uniquely positioned to address the needs of industry and job seekers, and on a timetable that keeps pace with 4IR velocity.

An ongoing debate in K-12 education policy has been between the "reform" agenda, including charter schools and school vouchers, and advocates of traditional public schools, led by educator unions. A similar split has emerged in higher education, particularly community colleges. Using California as an example, this paper: 1) summarizes the evolution of the current political divide between advocates of the "completion and success" agenda and faculty-led opponents, including the major reforms involved, 2) discusses the claims that leading organizations on each side have made, including their policy priorities, and 3) argues that the two sides share do share some areas of mutual agreement. The paper concludes by noting future policy considerations that could complicate reform efforts.

In recent years, American universities have implemented many innovative strategies to enhance the academic success of students, especially those from underrepresented backgrounds. Yet first-generation and/or low-income (FLI) college students continue to encounter barriers to success because they do not have authentic access to digital technology needed to graduate and be career-ready in our rapidly changing economy. This paper analyzes the current state of digital inequity among FLI students at Stanford University. It also reviews existing programs to address digital inequity at California State University, Fresno (Fresno State), the University of Michigan and Bowdoin College and provides guidance on developing a device program. Finally, the paper recommends strategies to better understand digital inequity and to address it in a sustainable way.

Asian Americans as a group are overrepresented among STEM college graduates and have the highest average college enrollment rate of any racial or ethnic category. Thus, Asian Americans are typically excluded from educational interventions directed at improving STEM education for Students of Color because they are not considered to be underrepresented minorities. However, statistics obscure the individual needs of the more than 20 ethnic subgroups that fall under the umbrella term Asian Americans. Using a participatory action research approach, this paper documents the institutional and sociocultural factors that push out HMoob (or Hmong) American college students from STEM programs at one large, predominantly White university; and the coordinate processes of gatekeeping and transactional advising that either redirect those students toward non-STEM programs or force them out of the university completely.

Over a 6-year period, a sociolinguistic and sociocultural project was undertaken by Alaska Native expert educators and linguists (aka the Yup'ik Expert Group) from the Yup'ik community in the Lower Kuskokwim School District, Central Alaska. The native experts developed their own culturally sustainable, valid, and reliable Kindergarten through Grade 6 Alaska Native language (Yugtun) assessment. Yup'ik experts named their assessment the Yugtun Piciryaranek Qaneryaranek-llu Cuqyun (aka Yup'ik Culture and Language Measurement). This paper focuses on a foundational component of the assessment, the Yup'ik Cultural Awareness subtest, which has two components, Nonverbal Communication and Yup'ik Worldview.

This paper examines the impact, characteristics, and entrepreneurial proclivities of foreign-born college graduates in the United States. A significant body of research has found that immigrants are more likely to start businesses than those born in the U.S., and the propensity of international students to concentrate in STEM fields indicates enormous potential for economic contributions and innovation. Yet the static nature of the immigration system, with visa pathways and restrictions that discourage business creation, hamper the nation's ability to take full advantage of the benefits immigrants can provide. In fact, this study finds that the U.S. immigration system likely delays foreign-born graduates from creating incorporated firms by as many as five years. The authors estimate that the creation of 150,000 incorporated firms and 580,000 jobs were delayed between 2013 and 2021. Without reform, the U.S. will continue to depress high-value firm creation by international students and cease to be the primary destination of global talent.

The COVID-19 pandemic has presented numerous challenges to students across the United States, particularly those who are parents enrolled in community colleges. California's community college system serves a diverse student population, including a significant number of non-traditional, working adults who are also parents. These students have faced unprecedented challenges due to the pandemic, including the difficulties of balancing childcare responsibilities with academic and professional obligations. This paper summarizes the preliminary findings of a study that intends to contribute to the crucial conversation around childcare needs among community college students. The focus of this study was understanding the experiences of BIPOC (Black, Indigenous, People of Color) mothers with young children and the impact of COVID-19 on their educational experiences in community colleges across the state of California.

In this paper we present the Advancing Racial Equity in Community College Model which maps out the organizational conditions shaping institutional transformation. Focused on two dimensions, the level of "organizational support" and "shared responsibility" to enact equity, we describe four quadrants with distinct organizational conditions that shape how equity advocates design, build, and sustain equity efforts. With well-documented racial inequities and renewed calls for racial justice across higher education, it demands new ways of exploring and understanding how institutional actors leading equity efforts are nested within differing organizational contexts that can enable as well as restrict the enactment and success of racial equity efforts. Our model helps equity advocates gain an "awareness" of known barriers to implementation in higher education, assess the readiness of their campus for racialized change, and take action to build the necessary institutional support and capacity to move the work forward.

Professional references are widely used in hiring decisions, yet their effectiveness remains largely understudied. This study analyzes structured ratings collected from the professional references of teacher applicants and conduct an experiment to see whether the ratings influence hiring managers' assessments of applicants and hiring decisions. There is little evidence that providing reference ratings to hiring managers influences their evaluations of candidates or hiring choices in productive ways. However, the analysis suggests that reference ratings are predictive of future job performance independent of other applicant information available to hiring managers. The result is a paradox: reference ratings offer potentially low-cost, high-value information, but hiring managers do not appear to make productive use of them.

This article clarifies historical and sociocultural factors that impact the role of STEM in the racialization of Asian Americans. Drawing on critical race and other theories of Asian American racialization, and a review of empirical research on the experiences of Asian American college students in STEM, we develop a conceptual framework called "STEM Asianization" that highlights the role of STEM ideology in the model minority racialization of Asian Americans. Consequences for Asian American students include (1) erasure of the intersectional experiences of minoritized Asian American students; (2) dehumanization of Asian Americans and establishment of a bamboo ceiling; (3) representation of Asian Americans as a perpetual foreigner/Yellow Peril during times of cultural and political crisis; and (4) representation of Asian Americans who cannot or do not conform to the STEM achievement narrative as a failed minority. We argue that STEM Asianization reproduces White supremacy by ideologically reinforcing the colorblind meritocracy of STEM institutions in the United States. [Additional funding provided by the Wisconsin Louis Stokes Alliance for Minority Participation.]

We study the effect of paternity leave on early child development. We collect sur-vey data on 5,000 children under age six in Spain and exploit several extensions of paternity leave that took place between 2017 and 2021. We follow a differences-in-discontinuities research design, based on the date of birth of each child and using cohorts born in non-reform years as controls. We show that the extensions led to significant increases in the length of leave taken by fathers, without affecting that of mothers, thus increasing parental time at home in the first year after birth. Eligibility for four additional weeks of paternity leave led to a significant 12 percentage-point increase in the fraction of children with developmental delays. We provide evidence for two potential mechanisms. First, children exposed to longer paternity leave spend less time alone with their mother, and more time with their father, during their first year of life. Second, treated children use less formal childcare. Our results suggest that paternity leave replaces higher-quality modes of early care. We conclude that the effects of parental leave policies on children depend crucially on the quality of parental versus counterfactual modes of childcare. [Funding for this report was provided by the Spanish Agencia Estatal de Investigación (AEI) and the Spanish Ministry of Science, Innovation and Universities.]

This study explores the underrepresentation of Black and Latinx students in California's community college Dual Enrollment (DE) programs. The study investigates how DE staff describe an understanding and commitment towards equity for Black and Latinx students in DE programs and how staff engage in equitably aimed praxis to serve Black and Latinx students through practices and collaborations between feeder high schools. Using a Critical Policy Analysis lens, the research highlights how Black and Latinx students are prioritized through equitable practices focused in advising and outreach. However, not all DE staff prioritize Black and Latinx through practices. Despite this, scant instances reveal that collaborative efforts between DE programs, high schools, and districts improve DE services and outcomes, though majority of K-12 partners are absent from collaborative efforts led by DE programs. The study emphasizes the need for increased collaboration between K-12 partners and integrating equitable approaches to DE outreach and advising to engage and recruit Black and Latinx students. This research advances the conversation of equity in DE programs and offers insights for addressing participation gaps among Black and Latinx students.

We study the effect of educational attainment on family formation using regression discontinuity designs generated by centralized admissions processes to both secondary and tertiary education in Finland. Admission to further education at either margin does not increase the likelihood that men form families. In contrast, women admitted to further education are more likely to both live with a partner and have children. We then pre-register and test two hypotheses which could explain each set of results using survey data. These suggest that the positive association between men's education and family formation observed in the data is driven by selection. For women, our estimates are consistent with the idea that, as increased returns to social skills shift the burden of child development from schools to parents and particularly mothers, education can make women more attractive as potential partners. [Funding for this report was provided by The Strategic Research Council, the Research Council of Finland, and Palkansaajasäätiö.]

In this essay, we explore the consequences of the University of California's policies to address racial disparities and its support for social justice activism as influences on its commitment to academic freedom and other intellectual values. This is a story of the interaction between two essential public university missions -- one civic, the other intellectual -- and the slow effacement of one by the other. The University's expressed commitments to academic freedom and the culture of rationalism have not been abandoned, but they are too often considered secondary or when confronted by new administrative initiatives and social movement activism related to diversity, equity, and inclusion (DEI). The experimental use of mandatory DEI statements on a number of the ten UC campuses, within willing academic departments, as initial screening mechanisms in faculty hiring is the most dramatic of the new administrative policies that have been put into place to advance faculty diversity. This policy can be considered the most problematic of a series of efforts that the UC campuses and the UC Office of the President have taken for more than a decade to prioritize representation in academic appointments. Our intent is to encourage a discussion of these policies within UC in light of the University's fundamental commitments to open intellectual inquiry, the discovery and dissemination of a wide range of new knowledge, and a culture of rationalism.

Most states responded to the onset of the pandemic by temporarily granting teachers Emergency licenses. These licenses allowed teachers to work in classrooms without passing the typical licensure exams. Since then, several states have extended their use of Emergency licenses, raising questions about how these policies impact the composition of the teacher workforce and student outcomes. In this paper, we examine the result of these policies using data on multiple cohorts of Emergency licensed teachers (ELTs) who taught in Massachusetts between 2021 and 2023. We find that ELTs were slightly more likely to remain in the same school and in the teaching workforce than teachers from other entry routes. However, ELTs' students scored significantly lower on standardized tests in math and science than other students in the same school and same year. Our findings are at odds with earlier, more positive assessments of Emergency licensure in Massachusetts. Our updated results appear to be driven by more recent cohorts of ELTs, rather than the teachers who received Emergency licenses at the start of the pandemic. Overall, this study suggests policymakers should be cautious when drawing sweeping conclusions about the impacts of teacher licensure based solely on the earliest cohort of teachers who obtained pandemic-era Emergency licenses.

The guided pathways model, comprising 14 different practices, is a framework for comprehensive, whole-college reform undertaken by community colleges to help all students choose, enter, progress through, and complete a program of study that enables them to secure sustaining-wage employment or transfer with junior standing in a major. Since its introduction in 2015, it has been adopted by hundreds of community colleges across the United States. This paper asks whether guided pathways practices implemented at 62 community and technical colleges in three states--Tennessee, Ohio, and Washington--are associated with improvements in student outcomes during the first year of college. Specifically, using institutional survey and rich administrative data, we construct measures of adoption of guided pathways reforms to examine the association between guided pathways practices and fall-to-fall persistence, college credits earned, college math credits earned, and STEM credits earned. Our study reveals substantial variation in the adoption of guided pathways reforms across the states and across community colleges within the states over time. While we cannot establish a causal relationship between guided pathways adoption and student outcomes, we find significant positive associations between the statewide adoption of guided pathways reforms and early student outcomes in Tennessee. The observed improvements in that state are likely the result of concurrent reforms--guided pathways and others--implemented simultaneously, rather than of guided pathways reforms alone. We do not find evidence of improved student outcomes in either Ohio or Washington following the launch of statewide guided pathways initiatives. Our findings suggest that complementarities among adopted practices within and across areas of practice--rather than the adoption of individual practices or the intensity of adoption--seem to drive larger improvements in early academic success across the three states. Our study is the first of its kind to explore the potential of guided pathways reforms in contributing to improved early academic success, representing a significant descriptive contribution given that whole-college reforms in higher education are understudied.

This study used Postsecondary Student Information System (PSIS) administrative data within the Education and Labour Market Longitudinal Platform to compare enrolment and persistence in postsecondary education (PSE) among high school graduates in British Columbia with and without special needs across five cohorts from 2010/2011 to 2014/2015 before and after controlling for several sociodemographic characteristics and academic achievement. The use of integrated longitudinal administrative data from the British Columbia Ministry of Education, the PSIS and the T1 Family File and the disaggregation of the special needs categorization were two major strengths of this study. Results show that high school graduates with mental health-related or cognitive needs and those with physical or sensory needs were less likely to enrol in PSE compared with high school graduates without special needs, even after controlling for covariates. Moreover, graduates with mental health-related or cognitive needs were less likely to transition to PSE immediately and less likely to persist in PSE two years after enrolment. These findings suggest that high school graduates with special needs, particularly those with mental health-related or cognitive needs, may encounter different types of barriers in transitioning to PSE.

Using British Columbia Ministry of Education administrative school data within the Education and Labour Market Longitudinal Platform, this study compared the proportions of high school graduates among Grade 12 students with and without special needs across nine cohorts from 2010/2011 to 2018/2019 before and after controlling for several sociodemographic characteristics. Two major strengths of this study were the use of longitudinal administrative education data integrated with income tax data from the T1 Family File and the further disaggregation of the special education needs categorization. Students with special needs in all different categories (excluding those with gifted status) were less likely to have graduated across all nine cohorts compared with students without special needs, even after controlling for sociodemographic characteristics and academic achievement, suggesting that students with special needs may face other types of barriers in completing high school. Yet there was diversity among students with special needs, with the highest proportions of graduation among students with learning disabilities or those with sensory needs and the lowest among students with intellectual disabilities. A larger share of females than males graduated high school among students without special needs. However, sex differences were less consistent among students with special needs status (including students with gifted status). As expected, the proportions of graduation were significantly higher at age 19 compared with at age 18 or younger, with the differences being slightly higher among students with special needs (excluding those with gifted status; 5 to 10 percentage points) compared with those without special needs (3 to 7 percentage points). The largest age differences were observed among students with autism spectrum disorder, behavioural needs or mental illness, and those with physical needs across all nine cohorts.

This study addresses the burgeoning phenomenon of fully online alternative teacher certification programs (ACPs). In Texas where most teachers are prepared via ACPs, our research zeroes in on the proportion of teachers who are prepared fully online and the relative effectiveness of teacher preparation programs on student achievement and teacher retention. Using statewide longitudinal data from 2014-2023, our findings show that 1 in 4 of Texas students are being taught by teachers prepared fully online Students taught by teachers prepared online exhibit comparable levels of achievement to those taught by uncertified teachers, underperforming compared to students taught by teachers from other preparation pathways. Moreover, these teachers exhibit a markedly higher turnover rate. This study contributes to the ongoing discourse on teacher preparation quality, offering insights for policymakers and stakeholders.

The Elementary and Secondary School Emergency Relief Fund (ESSER) was the largest onetime federal investment in K-12 schools in history, funneling almost $200 billion to states and school districts. We use novel data from Washington State to investigate the extent to which ESSER funding causally influenced spending on school personnel. We argue one cannot infer this directly from ESSER claims data because of the fungibility of school budgets. Thus, we rely on a more direct signal of district hiring decisions: public education job postings scraped from district hiring websites. To address endogeneity concerns, our preferred approach employs an instrumental variables strategy that exploits a formula mechanism used to determine Title I funding for 2020-21 (and thus ESSER allocations in 2022) based on the number of Title I formula-eligible children. We find strong, arguably causal, evidence that public school hiring increased in response to the availability of ESSER funding. Specifically, we estimate that each $1,000 in ESSER allocations caused districts to seek to hire $206 in additional staff, disproportionately teachers. These estimates suggest that roughly 12,000 new staff (including 5,100 teachers) were hired in Washington because of ESSER. In the absence of new funding, school staffing budgets will likely need to contract substantially following the sunset of ESSER.

Departmentalized instruction, in which teachers specialize in one or more core subjects and instruct multiple groups of students in a day, has become increasingly prominent in elementary schools. Using 8 years of data from Massachusetts and a difference-in-differences design, we estimate the effects of departmentalization on student achievement. We find that departmentalization has positive effects in English language arts (ELA) and science and mixed evidence of positive effects in math. These positive effects are not driven by teacher productivity improvements: Consistent with prior findings on teacher specialization, teachers are less effective when specializing in math and no more effective in ELA than when teaching self-contained classrooms. Rather, consistent with the theoretical underpinnings for specialization, departmentalized schools tend to assign teachers to their stronger subjects.

Policymakers and educational leaders across state and federal agencies have invested considerable effort in identifying how schools can both mitigate and exacerbate student absenteeism. Despite extensive research into school-level characteristics and programs, there remains a notable gap in understanding the impact of classroom-level factors on absenteeism. This study investigates how classmates' absences impact student absenteeism in four Texas school districts, analyzing both in-person and virtual contexts. Using a novel approach that accounts for day-to-day attendance variation, findings indicate that in-person absenteeism among peers significantly increases a student's absenteeism, with effects lasting up to three days, regardless of achievement levels. However, virtual absenteeism showed no similar impact, highlighting distinct absenteeism dynamics in virtual environments. Amid COVID-19 disruptions, this underscores the need for interventions addressing absenteeism across varied learning settings, offering insights for policymakers and educators in navigating the challenges of both physical and virtual classroom dynamics.

Who ends up in the teacher workforce is greatly influenced by who is admitted into teacher education programs (TEPs). To better understand how the preferences of teacher education faculty might shape admissions of STEM teacher candidates, we surveyed faculty who teach content or methods courses to STEM teacher candidates across five universities. Faculty reported that they most value information collected from individual interviews with applicants and data on the number of STEM courses taken in college and their performance in these courses, and least value data on university admissions tests, high school GPA, and teacher licensure test scores. When we investigate faculty members' revealed preferences through a conjoint analysis, we find that faculty most value applicants who have worked with students from diverse backgrounds and applicants from a marginalized racial or ethnic community, and least value whether they received high grades in math and/or science courses. Finally, we find significant variation in these perceptions across respondents in different faculty roles, who teach different courses, and from different institutions: for example, Arts and Sciences faculty tend to value TEP applicants' performance in college STEM courses relatively more than STEM education faculty, while STEM education faculty tend to value applicants' race and ethnicity relatively more than Arts and Sciences faculty.

A reference-based classification system for individual Scopus publications is presented which takes into account the categories of the papers citing those references instead of the journals in which those cited papers are published. It supports multiple assignments of up to 5 categories within the Scopus ASJC structure, but eliminates the Multidisciplinary Area and the miscellaneous categories, and it allows for the reclassification of a greater number of publications (potentially 100%) than traditional reference-based systems. Twelve variants of the system were obtained by adjusting different parameters, which were applied to the more than 3.2 million citable papers from the active Scientific Journals in 2020 indexed in Scopus. The results were analyzed and compared with other classification systems such as the original journal-based Scopus ASJC, the 2-generation-reference based M3-AWC-0.8 (\'Alvarez-Llorente et al., 2024), and the corresponding authors' assignment based AAC (\'Alvarez-Llorente et al., 2023). The different variants obtained of the classification give results that improve those used as referents in multiple scientometric fields. The variation called U1-F-0.8 seems especially promising due to its restraint in assigning multiple categories, consistency with reference classifications and the fact of applying normalization processes to avoid the overinfluence of articles that have a greater number of references.

This report presents the findings of the 2023 EUA Learning & Teaching Thematic Peer Group "Development and strategic benefits of learning and teaching centres", beginning with a presentation of the centres represented in the group and proceeding by presenting a virtuous cycle model for the continuous advancement of centres. Recommendations accompany each of the model's elements and, where possible, are illustrated through real-world practices.

Multi-campus public higher education governance systems exist in 44 of the 50 U.S. states. They include all the largest and most influential public colleges and universities in the United States, educating fully 75 percent of the nation's public sector students. Their impact is enormous. And yet, they are largely neglected and as a tool for improvement are underutilized. Meanwhile, many states continue to struggle achieving their goals for higher education attainment, social and economic mobility, workforce development, equitable access and affordability, technological innovation, and human and environmental health. The dearth of scholarly research on these systems and their more effective use is explored in a forthcoming volume edited by the author. This paper extracts from that volume a set of specific ways in which systems can leverage their unique ability to use scale in service to their mission.

In 1993, the Commonwealth of Massachusetts dramatically overhauled its K-12 education system and created a new school finance formula, building an educational accountability structure to ensure every child has access to a high-quality education. The Massachusetts Education Reform Act (MERA) established academic standards in core subjects, mandated assessments to measure student outcomes on those standards, and established a system for holding schools accountable when students failed to meet basic expectations. This system has helped Massachusetts' public schools become the highest performing in the country. Student outcomes in all tested subjects and across demographic groups have improved steadily over time, but disparities in achievement and attainment exist between the Commonwealth's most privileged students and their less privileged counterparts, many of whom are black or Hispanic. Without the MERA and its requirement to assess every student and publish aggregate academic outcomes, policymakers may not understand the extent of disparity or how to address it as student outcomes data are integral to understanding where Massachusetts' public schools have been, where they are going, and how they can get there. This paper illustrates the importance of the Massachusetts Education Reform Act and how it has positively impacted students over time. It explains why the current accountability system evolved as it did and why preserving the most important aspects of that system is critical if the state is going to fulfill its constitutional obligation to educate all children to a high common standard.

It is now well established that the COVID-19 pandemic had a devastating and unequal impact on student achievement. Test score declines were disproportionately large for historically marginalized students, exacerbating preexisting achievement gaps and threatening educational and economic inequality. In this paper, we use longitudinal student-level NWEA MAP Growth test data to estimate differences in test score declines for students at different points on the prepandemic test distribution. We also test the extent to which students' schools and districts accounted for these differences in declines. We find significant differences in learning loss by baseline achievement, with lower-achieving student's scores dropping 0.100 SD more in math and 0.113 SD more in reading than higher-achieving students' scores. We additionally show that the school a student attended accounts for about three-quarters of this widening gap in math achievement and about one-third in reading. The findings suggest school and district-level policies may have mattered more for learning loss than individual students' experiences within schools and districts. Such nuanced information regarding the variation in the pandemic's impacts on students is critical for policymakers and practitioners designing targeted academic interventions and for tracking disparities in academic recovery. [Additional funding for this report was provided by Kenneth C. Griffin.]

This document provides technical detail and supporting data for the research findings discussed in 'The student journey in VET: the many faces of completion and non-completion'. The analysis in this technical paper explores: (1) an approach to identifying VET subject enrolment activity that serves a compliance or regulatory purpose; (2) variability in completion rates across VET qualifications, and associated differences in patterns of subject enrolments and outcomes; (3) different indicators of student outcomes in VET, including program completion, subject completion, and movement to subsequent VET; (4) student training pathways exploring the extent to which students undertook programs, stand-alone subjects, or a combination of the two, and how this training choice evolved over time; and (5) student training pathways exploring the extent to which students went on to enrol in a program at a higher, lower, or the same level of educations, and how these pathways compared for students who did and did not complete their initial program.

Each year, more than a million high school students nationally take college dual enrollment courses, which have been shown to increase college access and success among participants. Yet racial/ethnic and other equity gaps in dual enrollment participation are widespread. To broaden the benefits of dual enrollment, the state of Ohio passed legislation in 2017 establishing the Innovative Programs (IP) policy, allowing waivers to test-based eligibility requirements--a frequently identified barrier to equitable access--for specific high school-college partnerships providing expanded outreach and support for students underrepresented in the state's dual enrollment program. This paper describes a multiple methods study of IP we conducted to examine how these partnerships were implemented to address the needs of underrepresented students and to evaluate whether the partnerships were successful in broadening access to and success in dual enrollment, as measured by course participation, pass rates, and college matriculation after high school. We find that the IP increased participation in dual enrollment among Black and Hispanic students. And while the implementation of the policy broadened access without changing course outcomes, the impacts on college enrollment after high school were mixed. Our results underscore the importance of pairing increased access to dual enrollment with adequate financial, advising, and academic resources to promote student success in and beyond dual enrollment courses.

This white paper is the output of a multidisciplinary workshop in Nairobi (Nov 2023). Led by a cross-organisational team including Microsoft Research, NEPAD, Lelapa AI, and University of Oxford. The workshop brought together diverse thought-leaders from various sectors and backgrounds to discuss the implications of Generative AI for the future of work in Africa. Discussions centred around four key themes: Macroeconomic Impacts; Jobs, Skills and Labour Markets; Workers' Perspectives and Africa-Centris AI Platforms. The white paper provides an overview of the current state and trends of generative AI and its applications in different domains, as well as the challenges and risks associated with its adoption and regulation. It represents a diverse set of perspectives to create a set of insights and recommendations which aim to encourage debate and collaborative action towards creating a dignified future of work for everyone across Africa.

Generative Artificial Intelligence (AI) technologies are in a phase of unprecedented rapid development following the landmark release of Chat-GPT, which brought the phenomenon to wide public attention. As the deployment of AI products rises geometrically, considerable attention is being given to the threats and opportunities that AI technologies offer, and to the need for regulatory and standards initiatives to ensure that use of the technology aligns with societal needs and generates broad benefits while mitigating risks and threats. This manuscript is the third of a series of White Papers informing the development of IEEE-SA's p3995 {\it `Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence Models'} \cite{P3395}, Chair Marina Cort\^{e}s. This part focuses on assessing calmly and objectively, as far as is possible, the current state of Artificial Intelligence (AI) technology development and identifying predominant trends, prospects, and ensuing risks. It necessarily forms a snapshot of the current instant of a rapidly-evolving landscape, with new products and innovations emerging continuously. While our main focus is on software and hardware developments and their corporate context, we also briefly review progress on robotics within the AI context and describe some implications of the substantial and growing AI energy demand., Comment: This is an interim version of our p3395 WG White Paper, Part III. We will update this version, until publication by IEEE-SA, Sponsor Committee - Artificial Intelligence Standards Committee (C/AISC); https://standards.ieee.org/ieee/3395/11378/ This White Paper is companion to Part I available at arXiv:2410.01808

Large language models (LLMs) represent a promising, but controversial, tool in aiding scientific peer review. This study evaluates the usefulness of LLMs in a conference setting as a tool for vetting paper submissions against submission standards. We conduct an experiment at the 2024 Neural Information Processing Systems (NeurIPS) conference, where 234 papers were voluntarily submitted to an "LLM-based Checklist Assistant." This assistant validates whether papers adhere to the author checklist used by NeurIPS, which includes questions to ensure compliance with research and manuscript preparation standards. Evaluation of the assistant by NeurIPS paper authors suggests that the LLM-based assistant was generally helpful in verifying checklist completion. In post-usage surveys, over 70% of authors found the assistant useful, and 70% indicate that they would revise their papers or checklist responses based on its feedback. While causal attribution to the assistant is not definitive, qualitative evidence suggests that the LLM contributed to improving some submissions. Survey responses and analysis of re-submissions indicate that authors made substantive revisions to their submissions in response to specific feedback from the LLM. The experiment also highlights common issues with LLMs: inaccuracy (20/52) and excessive strictness (14/52) were the most frequent issues flagged by authors. We also conduct experiments to understand potential gaming of the system, which reveal that the assistant could be manipulated to enhance scores through fabricated justifications, highlighting potential vulnerabilities of automated review tools.

In this paper we discuss the minimal Cayley Hamilton norm for a finite dimensional algebra over a field $F$ based on a paper by Skip Garibaldi

The exponential growth of knowledge and the increasing complexity of interdisciplinary research pose significant challenges for researchers, including information overload and difficulties in exploring novel ideas. The advancements in large language models (LLMs), such as GPT-4, have shown great potential in enhancing idea proposals, but how to effectively utilize large models for reasonable idea proposal has not been thoroughly explored. This paper proposes a scientific paper idea proposer (SciPIP). Based on a user-provided research background, SciPIP retrieves helpful papers from a literature database while leveraging the capabilities of LLMs to generate more novel and feasible ideas. To this end, 1) we construct a literature retrieval database, extracting lots of papers' multi-dimension information for fast access. Then, a literature retrieval method based on semantics, entity, and citation co-occurrences is proposed to search relevant literature from multiple aspects based on the user-provided background. 2) After literature retrieval, we introduce dual-path idea proposal strategies, where one path infers solutions from the retrieved literature and the other path generates original ideas through model brainstorming. We then combine the two to achieve a good balance between feasibility and originality. Through extensive experiments on the natural language processing (NLP) field, we demonstrate that SciPIP can retrieve citations similar to those of existing top conference papers and generate many ideas consistent with them. Additionally, we evaluate the originality of other ideas generated by SciPIP using large language models, further validating the effectiveness of our proposed method. The code and the database are released at https://github.com/cheerss/SciPIP., Comment: 25 pages, 5 figures, 19 tables

Academic paper search is an essential task for efficient literature discovery and scientific advancement. While dense retrieval has advanced various ad-hoc searches, it often struggles to match the underlying academic concepts between queries and documents, which is critical for paper search. To enable effective academic concept matching for paper search, we propose Taxonomy-guided Semantic Indexing (TaxoIndex) framework. TaxoIndex extracts key concepts from papers and organizes them as a semantic index guided by an academic taxonomy, and then leverages this index as foundational knowledge to identify academic concepts and link queries and documents. As a plug-and-play framework, TaxoIndex can be flexibly employed to enhance existing dense retrievers. Extensive experiments show that TaxoIndex brings significant improvements, even with highly limited training data, and greatly enhances interpretability., Comment: EMNLP'24

Listening to audio content, such as podcasts and audiobooks, is one of the ways people engage with knowledge. Listening affords people more mobility than reading by seeing, thus broadening learning opportunities. This study explores the potential applications of large language models (LLMs) to adapt text documents into audio content, addressing the lack of listening-friendly materials for niche content like research papers. LLMs can generate scripts of audio content in various styles tailored to specific needs, such as the duration of the content and whether it is a monologue or dialogue. To explore this potential, we developed PaperWave, a prototype that transforms academic paper PDFs into conversational podcasts. Our two-month investigation involving 11 participants (including the authors) employed autobiographical design, a field study, and a design workshop. The findings highlight the importance of considering listeners' interaction with their environment when designing document-to-audio systems.

Papers, patents, and clinical trials are indispensable types of scientific literature in biomedicine, crucial for knowledge sharing and dissemination. However, these documents are often stored in disparate databases with varying management standards and data formats, making it challenging to form systematic, fine-grained connections among them. To address this issue, we introduce PKG2.0, a comprehensive knowledge graph dataset encompassing over 36 million papers, 1.3 million patents, and 0.48 million clinical trials in the biomedical field. PKG2.0 integrates these previously dispersed resources through various links, including biomedical entities, author networks, citation relationships, and research projects. Fine-grained biomedical entity extraction, high-performance author name disambiguation, and multi-source citation integration have played a crucial role in the construction of the PKG dataset. Additionally, project data from the NIH Exporter enriches the dataset with metadata of NIH-funded projects and their scholarly outputs. Data validation demonstrates that PKG2.0 excels in key tasks such as author disambiguation and biomedical entity recognition. This dataset provides valuable resources for biomedical researchers, bibliometric scholars, and those engaged in literature mining., Comment: 31 pages, 6 figures, 22 tables

The patent domain is gaining attention in natural language processing research, offering practical applications in streamlining the patenting process and providing challenging benchmarks for large language models (LLMs). However, the generation of the description sections of patents, which constitute more than 90% of the patent document, has not been studied to date. We address this gap by introducing the task of outline-guided paper-to-patent generation, where an academic paper provides the technical specification of the invention and an outline conveys the desired patent structure. We present PAP2PAT, a new challenging benchmark of 1.8k patent-paper pairs with document outlines, collected using heuristics that reflect typical research lab practices. Our experiments with current open-weight LLMs and outline-guided chunk-based generation show that they can effectively use information from the paper but struggle with repetitions, likely due to the inherent repetitiveness of patent language. We release our data and code.

Recommendation system is such a platform that helps people to easily find out the things they need within a few seconds. It is implemented based on the preferences of similar users or items. In this digital era, the internet has provided us with huge opportunities to use a lot of open resources for our own needs. But there are too many resources on the internet from which finding the precise one is a difficult job. Recommendation system has made this easier for people. Research-paper recommendation system is a system that is developed for people with common research interests using a collaborative filtering recommender system. In this paper, coauthor, keyword, reference, and common citation similarities are calculated using Jaccard Similarity to find the final similarity and to find the top-n similar users. Based on the test of top-n similar users of the target user research paper recommendations have been made. Finally, the accuracy of our recommendation system has been calculated. An impressive result has been found using our proposed system., Comment: 5 pages, 4 figures