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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.

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.

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.

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.]

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.

In this position paper, the authors lay out the imperative for equitable artificial intelligence (AI), highlighting the essential role of access-oriented institutions and calling on technology companies (both large and small), foundations, and local, state, and federal regulators to consult with the newly convened Complete College America Council on Equitable AI in Higher Education. Their belief is that equitable AI spans far beyond the risk of mis-trained data. How schools adopt or reject these tools, the priorities of AI vendors, access to resources that enable the use of these tools, and the systemic integration of historically underrepresented and underserved voices will shape whether technology amplifies privilege or fosters inclusivity. A three-fold framework is presented for understanding Equity in AI, considering not just the quality and unbiased nature of the data used to train generative AI machines but also who has access to conversations around policy and product, as well as which institutions have access to the resources and safety nets that enable innovation and experimentation in the field of AI. A disruptive new advisory council is proposed, the Complete College America Council on Equitable AI in Higher Education, composed of representatives from historically excluded institutions and, by extension, students. The authors urge policymakers, technologists, and funders to proactively consult the Council and disrupt systemic inequities by integrating AI into higher education rather than continue to perpetuate them. [This paper was created in partnership with T3 Advisory.]

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.

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.

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.

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.

Graduates of special education teacher education programs can teach in a range of special education settings, raising the potential that their training can occur in very different settings than where they find their first jobs. We follow 263 completers of Moderate Disabilities programs in Massachusetts from their field placements to their early-career teaching positions and study the characteristics of their field placements and the degree to which these are aligned with their early-career teaching positions. We also assess the degree to which alignment is associated with early-career teacher turnover. We found that many of these teachers student-taught in an inclusive setting but were hired into a self-contained special education setting and vice versa, and teachers who experienced this misalignment were more likely to leave the workforce early in their careers. Teachers who student taught with a supervising practitioner without a special education license were also more likely to leave early. Findings suggest that teachers training to educate students with learning disabilities should student teach in a setting that is aligned with where they are likely to be hired, and with a supervising practitioner who is trained in special education.

Correctional education is a prevalent form of rehabilitation programming for prisoners in the United States. There is limited evidence, however, about the labor market returns to credentials received while incarcerated. Using incarceration, educational, and labor market data in Washington State, we study the labor market returns to GEDs and short-term vocational certificates earned in prison. We identify the returns to credentials by a difference-indifferences design that compares changes in earnings and employment for incarcerated persons who earn a credential to those who enroll in a program but fail to complete a GED or certificate. We estimate that GEDs increase post-incarceration earnings by about $450 per quarter and that vocational certificates increase earnings by about $250 per quarter. Degree completers have higher hourly wages, are more likely to be employed, and work more hours following release. For vocational programs, earnings increases are driven by certificates in construction and manufacturing. [The research presented presented in this report uses confidential data from the Education Research and Data Center (ERDC) located within the Washington Office of Financial Management (OFM).]

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.

Civic learning is an increasingly salient topic in research, policy, and practice. However, the recent empirical evidence on access to civic learning opportunities is limited. We build on prior research using survey items from the 2018 National Assessment of Educational Progress civics assessment and provide descriptive evidence on disparities in access to three categories of civics content and three evidence-based instructional approaches. We highlight inequalities in opportunities by student characteristics, school characteristics, and state characteristics among a national sample of more than 10,000 8th-grade students enrolled in a course with at least some civics focus (controlling for variation in the extent of civics focus). Our findings conflict with most of the prior evidence regarding disparities in access by race, ethnicity, or socioeconomic background, favoring Black students, Hispanic students, and students of relatively lower socioeconomic backgrounds. This suggests a shift in recent years, potentially due to an increased focus on equity. English learners and students with disabilities also reported greater access than their counterparts. Other findings include inequalities across school types, school location (city students reporting greater opportunity than both rural and suburban students), census region, and state testing policy. Additional findings are presented, and implications and opportunities for future research are discussed.

The United States retains many aspects of a healthy open society, but there are indicators of trouble and deep divisions around the meaning and importance of democratic values. This debate has significant repercussions for universities and their academic communities. In the most-simple terms, there is a red and blue state divide over the role and importance of public institutions, including universities -- red representing largely rural states in which most voters vote Republican and blue being majority Democratic voters, often with one of the two parties having majorities in their respective state legislatures. Then there are so-called purple states in which both parties are vying for dominance, but they are fewer in number. This brief discusses this contemporary dynamic and its implication for higher education and science policy.

This brief discusses cases of neo-nationalist violations of academic freedom in Hungary and Poland. The most prominent case of neo-nationalist violation of academic freedom in Hungary is the fate of the Central European University (CEU). The circumstances of CEU's forced move out of Hungary came before the European Court of Justice regarding it a possible violation of EU law. The Court cited the General Agreement on Trade in Services (GATS) under one of the three pillars of the World Trade Organisation (WTO) 1994 agreement, free trade, and the determination that CEU was a form of international educational services that should not be denied to the people of Hungary. Poland has a similar hostile environment to academics and academic freedom, although with a glimmer of hope following recent elections. The brief also discusses how such open breaches of academic freedom as in Hungary or Poland, in which politicians directly try to exert influence on research institutions and professors, are fortunately rather rare in Germany. However, a confluence of factors perhaps obscures the differences between "academic freedom" and the "freedom of opinion." In Germany, academic freedom includes the search for topics, rigorous methodical investigation, and professional norms to express findings and competent opinions, whereas the free speech is outside of these professional norms. The brief concludes with a discussion of the role of universities and the future of democracy in the context of ensuring a space for free and open debate.

Starting this year, tens of thousands of Russian freshmen found themselves attending a new mandatory course -- "Foundations of Russian Statehood." Swiftly designed under the auspices of Putin's administration, this ideologically charged course aims to position Russia as a unique civilization-state, bolstering Putin's political narrative and providing justification for the full-scale invasion of Ukraine. Consider, for example, this excerpt from the course's instructional video: "The 'Russian world' extends beyond current Russian borders, transcending ethnicities, territories, religions, political systems, and ideological preferences." As this curriculum becomes standard in Russian universities, it contributes to the emerging trend of weaponizing Russian universities and turning them into instruments in Russia's war of attrition with Ukraine and its broader stand-off with the West. This report discusses this weaponization process and the impact it is having on Russian universities, faculty, students, and the academic communities they belong to. It is regrettably a story of back to the future, reminiscent of the Soviet era of repression and attempts at control and manipulation of academics.

Since 2020, the federal government has distributed almost $2 billion to American school districts to mitigate the effects of COVID-19 pandemic school closures. Released in three separate tranches through the Elementary and Secondary School Emergency Relief (ESSER) fund, the Trump and Biden administrations outlined parameters for spending this unprecedented amount of money and ensured that most of it went directly to local school districts, with a comparative sliver going to state education agencies. This report gives an overview of the most common ESSER expenditures to date and assesses the factors that might influence whether district ESSER investments will make a difference for students. It also provides recommendations for how stakeholders should evaluate the ESSER experiment once it officially ends.

China's higher-education system has been shaped in recent years by a trio of factors: the COVID-19 pandemic, the ambitions of Chinese leader Xi Jinping to make his country into an innovation superpower that is loyal to the Communist Party, and western alarm about those ambitions. But a fourth development, the slowing of China's formerly super-charged economy, could play a more prominent role going forward. This article examines these four factors.

In a letter to Weierstrass Riemann asserted that the number $N_0(T)$ of zeros of $\zeta(s)$ on the critical line to height $T$ is approximately equal to the total number of zeros to this height $N(T)$. Siegel studied some posthumous papers of Riemann trying to find a proof of this. He found a function $\mathop{\mathcal R }(s)$ whose zeros are related to the zeros of the function $\zeta(s)$. Siegel concluded that Riemann's papers contained no ideas for a proof of his assertion, connected the position of the zeros of $\mathop{\mathcal R }(s)$ with the position of the zeros of $\zeta(s)$ and asked about the position of the zeros of $\mathop{\mathcal R }(s)$. This paper is a summary of several papers that we will soon upload to arXiv, in which we try to answer Siegel's question about the position of the zeros of $\mathop{\mathcal R }(s)$. The articles contain also improvements on Siegel's results and also other possible ways to prove Riemann's assertion, but without achieving this goal., Comment: 18 pages, 4 figures

Emotional, behavioral, and mental health challenges make it difficult for many children and adolescents to engage and succeed at school. Research indicates that at least 20% of all children and adolescents have been diagnosed with one more mental health disorders. Behavioral problems, anxiety, and depression are the most diagnosed mental health issues, and they often co-occur. Moreover, these conditions are being diagnosed at increasingly younger ages. In the past several years there has been a rise in the number of adolescents and young adults with serious mental health issues such as major depression and suicidal ideation, and the COVID-19 pandemic has exacerbated mental health problems for children and adolescents. Schools offer promise for providing intensive clinical support to the most at-risk students, and schools are necessary environment to explore the implementation of multi-modal youth mental health services. This paper provides an analysis of an intensive, in-school mental health services model developed and implemented by Effective School Solutions (ESS), a New Jersey based provider of high acuity school based mental health services for K-12 students. We analyze this multi-modal model for its effectiveness in improving educational outcomes for over 3,000 students identified as requiring intensive clinical mental health support across the 2021-22 school year. This analysis reveals that those students receiving High- versus Low-fidelity programming (i.e., multiple sessions per week for at least half of the school year versus for less than half of the school year) had better educational outcomes. Students receiving High-fidelity programming had greater improvements in grade point average (GPA) and greater reductions in absences across the school year. A higher number of in-school clinical sessions per week significantly predicted a greater increase in GPA and a greater reduction in total disciplinary incidents (including out of school suspensions) across the school year. This report provides initial promising evidence that in-school intensive mental health clinical services yield positive effects on students' educational outcomes. Though future research is needed to validate and extend these findings, schools may consider implementing such services onsite to meet students where they are and to optimize students' mental, behavioral, and educational well-being. [This white paper report was published by the Yale Child Study Center."]

Interest in the field of career and technical education (CTE) has experienced a resurgence over the last decade, as the global economy has grown increasingly competitive while students have continued to leave school underprepared for well-paying twenty-first century jobs. Together and separately, the education and workforce sectors have sought to address these challenges and better prepare students for viable economic futures. The results have been many new, innovative programs at both the secondary and postsecondary education levels that seek to give students technical training for specific careers, general training to prepare them for the workplace, and work-based learning opportunities where they can develop connections to employers and the workforce. While there are still many under-researched areas in CTE, this paper attempts to capture the evidence that has emerged--identifying areas where there is more evidence as well as areas where gaps in evidence still exist. The studies that have been conducted on CTE have demonstrated that it shows promise, but it is imperative to continue building evidence, particularly where there is policy interest and momentum but little data. Doing so will help demonstrate how those programs and models serve students and ensure that the continued scaling up of CTE is supported by a rigorous evidence base. This paper begins with an overview of the issues in the education system and the labor market that have led to the current revival of CTE. It argues that the skills today's employers need are not the ones schools are providing. The paper continues with a description of how various policies have fostered the growth of CTE. In the next section, it provides details on the types of programs and institutions that offer CTE, and the evidence base to support each of them. The paper provides evidence on the effectiveness of CTE at different educational levels, and for specific subgroups, including students with disabilities, and by gender. Further, the paper provides an overview of the available evidence to support different kinds of programs offered at both secondary and postsecondary education levels, touching on the amount of evidence available in each area and the level of rigor used in the studies that generated that evidence. The paper concludes by suggesting that while CTE instruction at the secondary and postsecondary levels could bolster students' economic mobility by helping them gain postsecondary credentials and obtain higher-paying jobs, there are challenges involved in turning that promise into reality. Investments in evidence-based practices can give CTE programs a better chance at success.

The purpose of this technical assistance paper is to assist education leaders and administrators in the consistent implementation of the Florida Career and Professional Education (CAPE) Act in Section 1003.491, Florida Statutes (F.S.). This technical assistance paper addresses questions on recent legislation, funding, and data reporting. [For the previous report, see ED616038.]

The iterative character of work in machine learning (ML) and artificial intelligence (AI) and reliance on comparisons against benchmark datasets emphasize the importance of reproducibility in that literature. Yet, resource constraints and inadequate documentation can make running replications particularly challenging. Our work explores the potential of using downstream citation contexts as a signal of reproducibility. We introduce a sentiment analysis framework applied to citation contexts from papers involved in Machine Learning Reproducibility Challenges in order to interpret the positive or negative outcomes of reproduction attempts. Our contributions include training classifiers for reproducibility-related contexts and sentiment analysis, and exploring correlations between citation context sentiment and reproducibility scores. Study data, software, and an artifact appendix are publicly available at https://github.com/lamps-lab/ccair-ai-reproducibility ., Comment: 9 pages, 4 figures

The United States has been cultivating STEM talent for decades with great success, but that robust talent pipeline is threatened by a growing STEM teacher shortage. Left unaddressed, that shortage could curtail employment in STEM professions and the many related careers that increasingly require some degree of scientific and technological literacy. While the STEM teacher shortage is a national problem, the effects are likely to be felt more acutely in a state such as Massachusetts with a high concentration of STEM jobs. This paper provides an overview of the causes of the STEM teacher shortage and offers three recommendations to address it.

A large share of Wisconsin's 400+ school districts are rural, and nearly half of all students enrolled in public schools statewide attend rural schools. Persistent challenges faced by rural districts in attracting and retaining educators, however, are contributing to an increasingly dire situation for the state's rural communities. This report summarizes findings from a yearlong research project investigating strategies being used by rural districts to address educator shortages, including a diverse set of "grow your own" (GYO) initiatives which involve school districts working with educator preparation programs (EPPs) and other local partners to identify, recruit, and prepare local candidates to become educators. The mixed-methods research design draws upon two statewide surveys (of rural superintendents and local site coordinators of the Educators Rising GYO program), along with site visits to five rural districts, to accomplish two main goals: (1) to identify strategies being used by rural districts to attract, recruit, and hire teachers; and (2) to describe the landscape of GYO initiatives being utilized by rural Wisconsin districts and local partners to address educator shortages. Broadly speaking, the work suggests that rural school districts are not waiting on state or federal policymakers to solve longstanding staffing challenges for them, but instead are actively engaged in implementing a mix of national GYO programs such as Educators Rising and "homegrown" GYO initiatives as one solution to chronic educator shortages. Not surprisingly, a distinct set of both successes and challenges have emerged as rural districts attempt to implement, launch, sustain, and scale up GYO initiatives that meet their needs. [Paper's original version August 2023; revised version September 2023. This work was made possible by a research grant from UW-Madison's Tommy G. Thompson Center for Public Leadership.]

To comply with the Every Student Succeeds Act of 2015 and related U.S. Department of Education peer review guidance, state education agencies must provide evidence demonstrating clear alignment (technically referred to as correspondence) between their K-12 English language proficiency standards and their academic content standards. This technical paper provides evidence of match, breadth, consistency [balance of representation], and depth of correspondence between WIDA consortium member state academic content standards in English language arts, mathematics, science, and social studies, as of Fall 2022, and the components of the WIDA English Language Development Standards Framework, 2020 Edition--specifically the four WIDA Key Language Uses and their grade-level cluster and content area instantiation in the WIDA Language Expectations. It also illustrates the relationship between the grade-level cluster Language Expectations and Proficiency Level 5 of the Proficiency Level Descriptors. State correspondence evidence helps ensure that K-12 students identified as English learners (referred to as multilingual learners by WIDA) have the opportunity to learn the critical elements of language that facilitate access to and achievement of academic content. [For the summary report, see ED631052.]

Seeking answers to questions within long scientific research articles is a crucial area of study that aids readers in quickly addressing their inquiries. However, existing question-answering (QA) datasets based on scientific papers are limited in scale and focus solely on textual content. To address this limitation, we introduce SPIQA (Scientific Paper Image Question Answering), the first large-scale QA dataset specifically designed to interpret complex figures and tables within the context of scientific research articles across various domains of computer science. Leveraging the breadth of expertise and ability of multimodal large language models (MLLMs) to understand figures, we employ automatic and manual curation to create the dataset. We craft an information-seeking task involving multiple images that cover a wide variety of plots, charts, tables, schematic diagrams, and result visualizations. SPIQA comprises 270K questions divided into training, validation, and three different evaluation splits. Through extensive experiments with 12 prominent foundational models, we evaluate the ability of current multimodal systems to comprehend the nuanced aspects of research articles. Additionally, we propose a Chain-of-Thought (CoT) evaluation strategy with in-context retrieval that allows fine-grained, step-by-step assessment and improves model performance. We further explore the upper bounds of performance enhancement with additional textual information, highlighting its promising potential for future research and the dataset's impact on revolutionizing how we interact with scientific literature., Comment: preprint

Occlusal contacts are the locations at which the occluding surfaces of the maxilla and the mandible posterior teeth meet. Occlusal contact detection is a vital tool for restoring the loss of masticatory function and is a mandatory assessment in the field of dentistry, with particular importance in prosthodontics and restorative dentistry. The most common method for occlusal contact detection is articulating paper. However, this method can indicate significant medically false positive and medically false negative contact areas, leaving the identification of true occlusal indications to clinicians. To address this, we propose a multiclass Vision Transformer and Fully Convolutional Network ensemble semantic segmentation model with a combination hierarchical loss function, which we name as Hierarchical Fully Convolutional Branch Transformer (H-FCBFormer). We also propose a method of generating medically true positive semantic segmentation masks derived from expert annotated articulating paper masks and gold standard masks. The proposed model outperforms other machine learning methods evaluated at detecting medically true positive contacts and performs better than dentists in terms of accurately identifying object-wise occlusal contact areas while taking significantly less time to identify them. Code is available at https://github.com/Banksylel/H-FCBFormer., Comment: 15 pages, 5 figures, 2 tables, 5 equations, peer reviewed and accepted to Medical Imaging Understanding and Analysis (MIUA 2024)

In recent years, the rapid increase in scientific papers has overwhelmed traditional review mechanisms, resulting in varying quality of publications. Although existing methods have explored the capabilities of Large Language Models (LLMs) for automated scientific reviewing, their generated contents are often generic or partial. To address the issues above, we introduce an automated paper reviewing framework SEA. It comprises of three modules: Standardization, Evaluation, and Analysis, which are represented by models SEA-S, SEA-E, and SEA-A, respectively. Initially, SEA-S distills data standardization capabilities of GPT-4 for integrating multiple reviews for a paper. Then, SEA-E utilizes standardized data for fine-tuning, enabling it to generate constructive reviews. Finally, SEA-A introduces a new evaluation metric called mismatch score to assess the consistency between paper contents and reviews. Moreover, we design a self-correction strategy to enhance the consistency. Extensive experimental results on datasets collected from eight venues show that SEA can generate valuable insights for authors to improve their papers.

The paper referred to in the title is Allard/Almgren 1981 [AA81]. Several months ago Francesco Maggi emailed me saying that the inequalities 5.3(4),(5) of \cite{AA81} were wrong. In fact, as he pointed out, their incorrectness is immediately apparent if one takes $Z=0$ there. Maggi and his coauthor wanted to use these inequalities in their paper \cite{MN}. They were able to obtain a version of these inequalities which suffice for the carrying out the work in \cite{MN}. I started writing this paper in order to provide a version of these inequalities as needed in [AA81]. In thinking about this material I began to realize there were other problems with the paper. As a result I ended up {\em completely rewriting 5.1-5.4 on pages 243-248 of \cite{AA81}}; this rewrite is the contents of this paper. In addition to many annoying misprints many of the needed definitions and proofs in 5.1-5.4 are incomplete or absent. For example, it is not said where $z$ in 5.1(2) comes from; this omission completely surprised me since I remember doing a lot of work to come up with $z$ when \cite{AA81} was being written. Also, much of the necessary material about the reach of a submanifold as in \cite{FE2} is not provided in \cite{AA81}. The table of contents can serve as an index. In particular one sees there where the constants $\epsilon_1$ through $\epsilon_6$ are introduced. This material is extremely technical. One way to navigate this paper would be to start looking at Proposition 9.5 and work backwards.

Testing in production-like test environments is an essential part of quality assurance processes in many industries. Provisioning of such test environments, for information-intensive services, involves setting up databases that are rich-enough to enable simulating a wide variety of user scenarios. While production data is perhaps the gold-standard here, many organizations, particularly within the public sectors, are not allowed to use production data for testing purposes due to privacy concerns. The alternatives are to use anonymized data, or synthetically generated data. In this paper, we elaborate on these alternatives and compare them in an industrial context. Further we focus on synthetic data generation and investigate the use of recurrent neural networks for this purpose. In our preliminary experiments, we were able to generate representative and highly accurate data using a recurrent neural network. These results open new research questions that we discuss here, and plan to investigate in our future research., Comment: This paper was published in the proceedings of RAISE@ICSE in 2019

Human-computer interaction scholars are increasingly touching on topics related to politics or democracy. As these concepts are ambiguous, an examination of concepts' invoked meanings aids in the self-reflection of our research efforts. We conduct a thematic analysis of all papers with the word `politics' in abstract, title or keywords ($n$=378) and likewise 152 papers with the word `democracy.' We observe that these words are increasingly being used in human-computer interaction, both in absolute and relative terms. At the same time, we show that researchers invoke these words with diverse levels of analysis in mind: the early research focused on mezzo-level (i.e., small groups), but more recently the work has begun to include macro-level analysis (i.e., society and politics as played in the public sphere). After the increasing focus on the macro-level, we see a transition towards more normative and activist research, in some areas it replaces observational and empirical research. These differences indicate semantic differences, which -- in the worst case -- may limit scientific progress. We bring these differences visible to help in further exchanges of ideas and human-computer interaction community to explore how it orients itself to politics and democracy.

A draft of a paper by Mandelbaum, "The dynamic complementarity problem", was circulated in 1987, but has never been published. We give an exposition of two important results from that paper which are not readily accessible in the literature. The first is an example of a Skorokhod problem in two dimensions in the quadrant for which there is not uniqueness. The second is a proof of uniqueness for the Skorokhod problem in two dimensions in the quadrant in a critical case.

This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and question answering, significantly reducing the time required for many routine tasks. On the other hand, researchers, whose work is not only time-consuming but also highly expertise-demanding, face increasing challenges as they have to spend more time reading, writing, and reviewing papers. This raises the question: how can LLMs potentially assist researchers in alleviating their heavy workload? This study focuses on the topic of LLMs assist NLP Researchers, particularly examining the effectiveness of LLM in assisting paper (meta-)reviewing and its recognizability. To address this, we constructed the ReviewCritique dataset, which includes two types of information: (i) NLP papers (initial submissions rather than camera-ready) with both human-written and LLM-generated reviews, and (ii) each review comes with "deficiency" labels and corresponding explanations for individual segments, annotated by experts. Using ReviewCritique, this study explores two threads of research questions: (i) "LLMs as Reviewers", how do reviews generated by LLMs compare with those written by humans in terms of quality and distinguishability? (ii) "LLMs as Metareviewers", how effectively can LLMs identify potential issues, such as Deficient or unprofessional review segments, within individual paper reviews? To our knowledge, this is the first work to provide such a comprehensive analysis.