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Nearly two decades into the "completion agenda" in higher education, many community colleges have adopted collegewide reforms designed to improve stubbornly flat rates of student success and address persistent equity gaps. The longer-term effects of such collegewide reforms may take years to observe. In the meantime, college leaders need to know whether changes they make in the short run are associated with longer-term student success. Measuring the progress and effects of institutional reform is particularly vital in economically important STEM fields. Drawing on administrative records from transfer-intending community college starters across three states, this study develops and explores potential indicators of early STEM program momentum. We find that a relatively simple set of STEM momentum metrics--notably early completion of calculus or non-math STE coursework specified in statewide STEM transfer pathways and, to a lesser degree, the prerequisites to such courses--are reliable indicators of subsequent STEM transfer and bachelor's degree attainment. Our findings provide support for the use of the STEM momentum metrics to formatively evaluate reforms aimed at strengthening STEM transfer outcomes and closing equity gaps in STEM bachelor's degree attainment.

As part of its regulatory roles, the Australian Government Tertiary Education Quality and Standards Agency (TEQSA) is required to assess evidence of 'scholarship' that is put forward by providers, whether evidence of scholarship by individuals, such as teaching staff within the provider, or for the provider as a whole. TEQSA is seeking to review whether its current approach to assessing claims of scholarship and scholarly activity (as described in the Guidance Note on Scholarship) is adequate, or if the approach needs to be reconceptualised. The purpose of this discussion paper is to set out, for consideration by the sector and other stakeholders, draft principles that are proposed to guide providers in making claims related to scholarship, and to inform TEQSA's assessments of such claims. TEQSA's Guidance Note describes 'scholarship' as 'activities concerned with gaining new or improved understanding, appreciation and insights into a field of knowledge, and engaging with and keeping up to date with advances in the field.' This includes advances in ways of teaching and learning in the field and advances in professional practice, as well as advances in disciplinary knowledge through original research.' This discussion paper proposes a set of principles that would guide providers when offering evidence of their capacity to meet the requirements of the Higher Education Standards (HES) Framework in relation to scholarship. [For "Guidance Note: Scholarship. Version 2.5," see ED610488.]

The Community Eligibility Provision (CEP) is a policy change to the federally-administered National School Lunch Program that allows schools serving low-income populations to classify all students as eligible for free meals, regardless of individual circumstances. This has implications for the use of free and reduced-price meal (FRM) data to proxy for student disadvantage in education research and policy applications, which is a common practice. We document empirically how the CEP has affected the value of FRM eligibility as a proxy for student disadvantage. At the individual student level, we show that there is essentially no effect of the CEP. However, the CEP does meaningfully change the information conveyed by the share of FRM-eligible students in a school. It is this latter measure that is most relevant for policy uses of FRM data. [Portions of this paper were previously circulated under the title "Using Free Meal and Direct Certification Data to Proxy for Student Disadvantage in the Era of the Community Eligibility Provision" (ED595218). The authors have since split the original paper into two parts. This is the first part.]

Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as sufficient predictors. This study compares the out-of-sample predictive power of early momentum metrics (EMMs)--13 near-term success measures suggested by the literature--with that of metrics from ML-based models that employ approximately 500 predictors for community college credential completion. Using transcript data from approximately 50,000 students at more than 30 community colleges in two states, I find that the EMMs that were modeled by logistic regression accurately predict completion for approximately 80% of students. This classification performance is comparable to that of the ML-based models. The EMMs even outperform the ML-based models in probability estimation. These findings suggest that EMMs are useful predictors for credential completion and that the marginal gain from using an ML-based model over EMMs is small for credential completion prediction when additional predictors do not have strong rationales to be included in an ML-based model, no matter how large the number of those predictors may be.

This study compares the differences in the mismatch between the education and occupations of immigrants in Canada and the United States, operationalized by over-education. It further explores how the cross-country differences may be related to the supply of and demand for university-educated immigrants and the way they are selected. Using comparable data and three measures of over-education, this study found that university-educated recent immigrants in Canada were much more likely to be overeducated than their U.S. peers. The over-education rate gap between recent immigrants and the native-born was much more pronounced in Canada than in the United States. In addition, while labour market demand was associated with a lower level of over-education in both countries, a greater supply of university-educated recent immigrants was positively associated with a likelihood of over-education among recent immigrants in Canada, but not in the United States. Furthermore, in Canada, the over-education rate was significantly lower among immigrants who were admitted through some form of employer selection (e.g., immigrants who worked in skilled jobs in Canada before immigration) than those who were admitted directly from abroad. Overall, this study provides insight into how the immigration system interacts with broader aspects of the labour market to shape the labour market outcomes of immigrants.

Private school choice options are being proposed and adopted in numerous states across the country. As of the spring of 2019, 62 private school choice programs were in operation in 29 states and the District of Columbia, serving more than 400,000 children. Although growth in private school choice programs and enrollment has been considerable over the past decade, the percentage of private schools participating in school choice options varies considerably by program. Understanding how program design impacts the supply of private schools participating in these programs will be critical for policymakers as they work to create and expand education choice options for families. This report considers whether certain regulations governing school choice programs reduce specialization and diversity in the supply of private schools that participate. Expanding on the prior analysis of the impact of regulations in three locations, the authors chart how schools self-identify prior to and after switching into private school choice program environments in each of the five locations. The authors found that private school leaders in all five locations are more likely to classify their schools as less specialized than they were prior to entering the programs. The authors also found evidence to suggest that more homogenization occurred in more highly regulated voucher programs. These findings suggest a potential homogenizing effect of regulations on school supply, limiting the diversity of the private school market. These findings also suggest policymakers should carefully weigh the costs of regulating private school choice programs, as overregulation could reduce specialization and diversity of school supply in a given school choice program, limiting the options that are available to families.

This study develops, validates, and applies a typology of teachers using labor market data. We construct our typology by applying a correlated topic model to 17,000 personal statements teachers submitted as part of their applications to open positions in Wisconsin public schools. We identify seven types of teachers active on the labor market: Inclusivists, Idealists, Nurturers, Generalists, Classroom Experts, Guides, and External Experts. Using a combination of quantitative and qualitative methods, we explore trends within and among types as well as demographic relationships and labor market behaviors. This research provides novel insights into the philosophies, mission, vision, and values of teachers; links these characteristics to teachers' job market preferences; and provides a sound psychometric foundation for these measures of teacher type to be applied in subsequent research.

The aim of the paper is to identify and analyse patterns and trends in enrolment in upper secondary initial vocational education and training (IVET) in Europe over the period 1995 to 2015. The research produced findings on comparability of the international data as well as trends in enrolment in upper secondary IVET and its share of enrolment in upper secondary education. It found that, in countries where there has been a decline in VET enrolment, most of this is due to a declining youth population. It also found that many fluctuations in enrolment figures are artificial in the sense that they are the result of changing national classification and/or reporting practices. When correcting for these factors, findings show that the development of absolute enrolment in VET, as well as its share of enrolment in upper secondary education, has been quite stable in most countries. [The research was carried out by a consortium led by 3s Unternehmensberatung GmbH, and includes the Danish Technological Institute, the Institute of Employment Research (University of Warwick), the Institute of International and Social Studies (Tallinn University) and Fondazione Giacomo Brodolini. The Federal Institute for Vocational Education and Training (BIBB) in Germany is supporting the project as a subcontractor.]

Capitalizing on the findings in our preceding study of a purely theoretical model, this paper aims to empirically examine whether and to what extent public universities' institutional missions have transformed in recent years in the States of California and New York by quantifying a degree of functional diversification of universities. We focus on research funding and productivity, and public service activities, and have developed a Concentration Equality Index (CEI) to help in this analysis. We then apply the CEI over time to a selected group of public university-system campuses within the State University of New York (SUNY) system, the City University of New York (CUNY), and the California State University (CSU) and the University of California (UC) systems. Among our findings: a select group of CSU campuses which all have roles at teaching-intensive schools, have gained increasingly versatile roles with rapidly expanded spending capacity in research and public service. These focal shifts resulted in some CSU campuses transforming into "UC-like universities", that is, a trend toward an institution with multi-functional operations of equally weighted instruction, research, and public service. In contrast, several campuses of both SUNY and CUNY systems have come to place varied weights on chosen missions rather than evening out their roles in instruction, research, and public service.

A singular vision has propelled higher education and ministries of education in Asia since the new millennium. It is a vision launched by the once rising tide of a globalized world order that spilled into higher education: in order to be competitive on the world scene, each Asian country had to build "World Class Universities," which could be compared and rank-ordered with the pre-eminent research universities of America, Britain and elsewhere. And if the pre-eminent American and British research universities could not be quickly surpassed, punctuated jumps up the status ladder of global higher education would establish an "heir-apparent" trajectory. Now, however, the rising tide of globalism has perhaps crested. Indeed, as some scholars of globalism and higher education point out, in certain aspects of national policy the rising tide is turning into a receding one. Nation-states are recoiling from an elite-driven, transnational world order into an "inside economy" that is concerned with its own issues of development and sustainability, quite apart from measuring itself against the rest of the world. In time, higher education in Asia is likely to follow suit. Globalism created the vision of "World Class Universities" ranked in an imitative hierarchical order; its demise suggests the need for other ideals that can drive the quest for excellence in higher education in Asia. The bedrock of educational quality for the New Flagship University in Asia is excellence in all of the forms of knowledge and understanding of human experience. The stronger the excellence in each form, the better the university's earned standing amongst its peers. But this is not a relative relationship, like the World Rankings, where worth is measured against other institutions in a game of winners and losers. Rather, it is measurement against the standards of excellence inherent in each form itself.

Childcare quality is often thought to be important for influencing children's subsequent attainment at school. The English Government regulates the quality of early education by setting minimum levels of qualifications for workers and grading settings based on a national Inspectorate (OfSTED). This paper uses administrative data on over two million children to relate performance on national teacher assessments at ages 5 and 7 to the quality characteristics of the nursery they attended before starting school. Results show that staff qualifications and childcare quality ratings have a weak association with teacher assessments at school, based on comparing children who attended different nurseries but attended the same primary school. Our results suggest that although children's outcomes are related to the nursery they attend, which nurseries are good cannot be predicted by staff qualifications and OfSTED ratings; the measures of quality that Government has focused on. Supplementary tables are appended. [This paper was produced as part of the Centre for Economic Performance's Education and Skills Programme.]

This white paper explores the variation among Part C exiting categories as reported by the 50 states and Washington, D.C., using 2012-13 exiting data. Examining factors that may contribute to variation can lead to improved Part C exiting data quality within and across states. Examination of the Part C exiting data shows that 8 of the 10 categories (categories 1, 2, 4, 5, 6, 8, 9, and 10) had relatively wider variation among states. The paper investigates state characteristics that may influence exiting data variation, as well as possible strategies for improving data quality. This white paper includes four sections. Part 1 summarizes Part C exiting definitions. Part 2 reviews broad, general trends in exiting data variation. Part 3 examines potential reasons for variation, with possible strategies to improve exiting data quality. Finally, Part 4 summarizes the findings of examination of exiting data variation and highlights key findings for state data personnel. [The IDEA Data Center is one of the centers in the Technical Assistance and Dissemination Network (TA&D Network), funded by the Office of Special Education Programs (OSEP).]

Many postsecondary institutions, and community colleges in particular, require that students demonstrate specified levels of literacy and numeracy before taking college-level courses. Typically, students have been assessed using two widely available tests--ACCUPLACER and Compass. However, placement testing practice is beginning to change for three reasons. First, the Compass test will no longer be offered as of the end of 2016. Second, questions have been raised about the validity of commonly used placement tests. Third, there are emerging discussions about the need to consider other aspects of students' readiness to succeed in college, especially so-called noncognitive skills. In this paper, we discuss the history of college placement testing, with a focus on nonselective colleges. We describe the limitations of placement tests, the consequences of placement errors, and the movement toward changing systems of placement. The use of multiple measures is suggested as an approach that will result in more accurate placement. A typology of approaches to assessment and placement is described, including the identification of individual measures (e.g., alternative math and English tests, noncognitive assessments, and high school transcript information), ways to use them in combination (e.g., waivers, decision rules, and placement formulae), and how colleges might use assessment results in more varied ways (e.g., for placement into different course types or services). Finally, we include a discussion of emerging issues affecting assessment and placement practices.

The digital revolution and automation are accelerating changes in the labour market and in workplace skills, changes that are further affected by fluctuations in international and regional economic cycles and employment opportunity. These factors pose a universal policy challenge for all advanced economies and governments. In the workplace, people seek to acquire contemporary and relevant skills to gain employment and retain transferable skills to maintain employment. The central purpose of this paper is to investigate how other nations or regions are dealing with these issues. What approaches are they taking to understanding the mix and dynamics of the skills attained by individuals and, more broadly, the totality of skills that in aggregate constitute a highly capable and adaptable labour force, one that supports firm viability and greater national productivity. This research has examined a range of initiatives and approaches being developed or in use in selected countries, including the United States, Singapore and New Zealand, and agencies/organisations; for example, the European Commission and the Skills for the Information Age Foundation. In doing so, it showcases the good practices used to ensure that occupational-level skills information remains current and widely accessible. [For "Identifying Work Skills: International Case Summaries. Support Document," see ED579875.]

ACECQA has published the second in its series of occasional papers, analysing one of the most challenging quality areas -- Children's Health and Safety. Quality Area 2 addresses one of the primary objectives of the National Quality Framework -- to ensure the health, safety and wellbeing of children attending education and care services. The paper examines performance across service types, socio economic and remoteness classifications, jurisdictions and management types. It also breaks down Quality Area 2 and highlights that standard 2.3 (each child is protected) and element 2.3.3 (incident and emergency planning) are the most challenging aspects of the Quality Area. One of the findings from the analysis is that services in remote and very remote areas may benefit from more support to understand and comply with the requirements of Quality Area 2. The paper also summarises recent state, territory and Commonwealth initiatives around child safe organisations, as well as some examples of the types of compliance and enforcement action that state and territory regulatory authorities have taken relating to children's health and safety.

Calls to increase the number of undergraduate STEM credential recipients have largely failed to differentiate between sub-baccalaureate and four-year credentials at the undergraduate level, which is problematic for workforce development. In this paper, the authors develop a classification system for sub-baccalaureate STEM credentials that is incorporated into an analysis of administrative data from the Virginia Community College System. The authors first describe sub-baccalaureate STEM students and then examine the relationships between STEM matriculation and short-term outcomes for six cohorts. The authors use Mincerian regressions to estimate the earnings associated with completing a STEM credential four years after initial enrollment. In addition to confirming that students with career-oriented credentials drive short-term STEM earnings benefits, and that full-time students are more likely to complete credentials than their part-time peers, this study also finds relative homogeneity between STEM and non-STEM community college students, suggesting that ability may not be the primary factor inhibiting middle-skill STEM workforce preparation. The authors conclude by discussing the findings and suggesting how these data could be useful in better aligning Virginia's economic development plans and postsecondary educational offerings. A table on VCCS STEM Majors by Program Category and Credential Orientation is appended.

We investigate the extent to which graduate returns vary according to the class of degree achieved by UK university students and examine changes over time in estimated degree class premia. Using a variety of complementary datasets for individuals born in Britain around 1970 and aged between 30 and 40, we estimate an hourly wage premium for a "good" (relative to a "lower") class of degree of 7% to 9%, implying a wide spread around the average graduate premium. We also estimate the premium for a good relative to a lower degree for different cohorts (those born between the mid-1960s and early-1980s) and find evidence that the premium for a good degree has risen over time as the proportions of cohorts participating in higher education have increased. Tables and a list of university types are appended.

One in five school-age children in the U.S. speaks a language other than English at home (Zeigler & Camarota, 2014). Roughly half of these emerging bilingual students (Garcia, 2009) are classified as English learners (ELs) when they enter school, meaning they do not meet state or district criteria for English proficiency (NCES, 2015). As the fastest growing official subgroup of students, ELs are transforming schools across the country, in cities as well as suburban and rural communities; in traditional immigrant-receiving areas as well as in new immigrant destinations. Emerging bilingual students, and the subset of them that are classified as ELs, bring with them important linguistic, social, cultural, and intellectual assets that can enrich and strengthen education for all students (González, Moll & Amanti, 2013). But questions persist around how best to ensure that students who are not yet proficient in English can thrive in school, academically, linguistically, and socially. Should ELs be taught in bilingual classrooms that promote fluency in their home language while ensuring access to core academic content and developing English language skills? Or should they be taught in English immersion classrooms in order to maximize exposure to English? How do we ensure that emerging bilingual students develop both English proficiency and strong academic skills, while maintaining and developing literacy in their home language? How can schools best build on ELs' linguistic assets and support their educational needs?

Of the copious research on the labor market returns to college, very little has adequately modeled the pathways of non-completers or compared their outcomes with those of award holders. In this paper, we present a novel method for linking non-completers with completers according to their program of study. This method allows us to calculate the labor market returns to programs of study, accounting both for those who obtain an award and those who do not. We use a large dataset of community college transcripts matched with earnings data. We find that different classification systems--by algorithm, intent, or goal--yield very different enrollment patterns across programs. These classifications make a substantial difference to earnings patterns. Our results show that returns vary not only by program completion, but they also vary by program non-completion. Consequently, combining completers and non-completers yields a new pattern of returns. For some awards, this leads to wider earnings differentials. However, we find that the variance in returns by subject of study is reduced when we combine data on completers and non-completers. Finally, we find that progression in a program per se does not lead to higher earnings for students who do not complete (even as it demonstrably does for students who complete their program). If validated, these findings have significant implications for policies on program choice and on student retention policies. A supplementary figure is appended.

Of the copious research on the labor market returns to college, very little has adequately modeled the pathways of non-completers or compared their outcomes with those of award holders. In this paper, we present a novel method for linking non-completers with completers according to their program of study. This method allows us to calculate the labor market returns to programs of study, accounting both for those who obtain an award and those who do not. We use a large dataset of community college transcripts matched with earnings data. We find that different classification systems--by algorithm, intent, or goal--yield very different enrollment patterns across programs. These classifications make a substantial difference to earnings patterns. Our results show that returns vary not only by program completion, but they also vary by program non-completion. Consequently, combining completers and non-completers yields a new pattern of returns. For some awards, this leads to wider earnings differentials. However, we find that the variance in returns by subject of study is reduced when we combine data on completers and non-completers. Finally, we find that progression in a program "per se" does not lead to higher earnings for students who do not complete (even as it demonstrably does for students who complete their program). If validated, these findings have significant implications for policies on program choice and on student retention policies. Appended is Figure A.1: Assignment of Students to Programs.

School districts and state departments of education frequently must choose between a variety of methods to estimating teacher quality. This paper examines under what circumstances the decision between estimators of teacher quality is important. We examine estimates derived from student growth percentile measures and estimates derived from commonly used value-added estimators. Using simulated data, we examine how well the estimators can rank teachers and avoid misclassification errors under a variety of assignment scenarios of teachers to students. We find that growth percentile measures perform worse than value-added measures that control for prior year student test scores and include teacher fixed effects when assignment of students to teachers is nonrandom. In addition, using actual data from a large diverse anonymous state, we find evidence that growth percentile measures are less correlated with value-added measures with teacher fixed effects when there is evidence of nonrandom grouping of students in schools. This evidence suggests that the choice between estimators is most consequential under nonrandom assignment of teachers to students, and that value-added measures controlling for teacher fixed effects may be better suited to estimating teacher quality in this case.

When lotteries are infeasible, researchers must rely on observational methods to estimate charter effectiveness at raising student test scores. Considerable attention has been paid to observational studies by the Stanford Center for Research on Education Outcomes (CREDO), which have analyzed charter performance in 27 states. However, the sensitivity of CREDO's findings to its methodology has not been subject to a thorough, independent evaluation. Our analysis of the CREDO estimates of charter effectiveness in Florida between 2001 and 2009 reveals four main findings that increase confidence in its results: (1) Its use of multiple observations when matching students does not materially affect results; (2) Student participation in programs such as special education and free/reduced price lunch is inconsistently measured across sectors, but matching on these variables only modestly affects CREDO's estimates; (3) Exogenous instrumental variable estimates of charter effectiveness produce qualitatively similar results to CREDO's observational estimates; and (4) Impact estimates differ for oversubscribed and undersubscribed charters, which helps explain why lottery-based studies tend to find larger charter impacts than CREDO does. The following are appended: (1) Other Potential Concerns with CREDO's Methodology; (2) Differential Program Participation; (3) Analysis of Transfer Students Only; and (4) Summary Statistics for Over and Undersubscribed Charter Schools.

The fields of science, technology, engineering, and mathematics, more ubiquitously known by the acronym "STEM," have received a substantial amount of attention in recent years. As part of a research study investigating the alignment (or lack thereof) between the goals and priorities of educators and employers, we found it difficult to ascertain precisely what constituted a STEM occupation and to reconcile vastly different job, wage, and educational attainment projections. In this paper we explore the ways in which agencies and labor market researchers define STEM in six widely cited reports, and how these definitions influence the estimated and projected number of STEM jobs, estimates of how much these jobs pay, and what levels of education are necessary to attain these jobs. We find that agencies and researchers use different methods to classify STEM jobs (e.g., work tasks performed, knowledge, skills, education, type of work), which result in STEM job estimates ranging from 5.4 million to 26 million. Wage estimates exhibit a similarly wide range, from $50,000 to $96,000. In addition, jobs that require some STEM knowledge are frequently excluded from labor market analyses of STEM occupations, resulting in the under-counting of STEM-related jobs, the over-estimation of potential wages, and under-valuing of a sub-baccalaureate degree. Finally, we emphasize how groups of occupations (e.g., STEM) and industries (e.g., manufacturing) cannot be conflated with specific occupations. We recommend that researchers and agencies adopt a universal definition of STEM occupations and/or be more precise when speaking about the labor market in STEM related fields.