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Since establishing its first campus in 1868, the University of California (UC), California's land-grant university, developed into the nation's first multi-campus system in the United States, and is today widely recognized as the world's premier network of public research universities. This short essay provides an historical brief on the role that shared governance, and specifically the role of the Academic Senate, played in creating an academic culture of excellence and high achievement in pursuing its tripartite mission of teaching and learning, research and knowledge production, and public service. A key component in understanding the critical role of the Senate in UC's evolution from a single campus in Berkeley to now a ten-campus system is the university's unusual designation as a public trust in the state constitution that, beginning in 1879, protected the university at critical times from external political pressures and allowed the university to develop an internal academic culture guided by the Academic Senate. By the 1920s, the emergence of California's unique and innovative public system of higher education, with UC as the sole public provider of doctoral degrees and state funded research, also helps explain the ability of the UC system to maintain its mission and formulate what is termed a "One University" model. The Academic Senate has created coherency and shared values within UC, and a culture and expectation for faculty performance that is unique among universities around the world. This essay also offers a brief reflection on the Academic Senate's past influence, its current status, and prospective role. The overall intent is to provide context for the current academic community and higher education scholars regarding the past and future role of faculty in university governance and management, and what distinguishes UC in the pantheon of major research universities.

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."]

Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore, previous research has shown a complex relationship between response time and accuracy, necessitating a functional analysis to understand the patterns that manifest from this relationship. In this study, response time data are incorporated into an item response model for two purposes: (a) to examine how individuals' speed within an experimental condition affects their response accuracy on an item, and (b) to detect the differences in individuals' speed between conditions in the presence of within-condition effects. For these two purposes, by-variable smooth functions are employed to model differential and functional response time effects by experimental condition for each item. This model is illustrated using an empirical data set to describe the effect of individuals' speed on their reading comprehension ability in two experimental conditions of reading medium (paper vs. digital) by item. A simulation study showed that the recovery of parameters and by-variable smooth functions of response time was satisfactory, and that the type I error rate and power of the test for the by-variable smooth function of response time were acceptable in conditions similar to the empirical data set. In addition, the proposed method correctly identified the range of response time where between-condition differences in the effect of response time on the probability of a correct response were accurate. [This is the online version of an article published in "Journal of Educational Measurement."]

This report presents a holistic approach to understanding and comparing vocational education and training (VET) systems. The approach has been developed jointly by a group of interdisciplinary VET researchers over a 5-year period as part of Cedefop's research on the future of VET and has been reviewed several times. The framework introduces 50 dimensions for analysing VET systems, as well as parts of them, structured according to three overlapping main perspectives: epistemological and pedagogical, education system, and socioeconomic or labour market. The framework is particularly suited to 'clearing the ground' for policy work and provides a model for how research can support policy. This model can be flexibly adapted and applied in any comparative research or international policy learning activity related to VET. [The research was carried out by a consortium led by 3s Unternehmungsberatung (Austria). The consortium includes Ockham IPS (the Netherlands) and the Fondazione Giacomo Brodolino (Italy). The German Federal Institute of Vocational Education and Training (BIBB) supports the project as sub-contractor. For "The Changing Nature and Role of Vocational Education and Training in Europe. Volume 1: Conceptions of Vocational Education and Training--An Analytical Framework. Cedefop Research Paper. No 63," see ED586251.]

Research has shown educators' implicit biases to be a key factor in creating and perpetuating disparities in students' experiences of schooling, learning, and longer-term outcomes, including job opportunities, wealth, and health. Current school reform and transformation efforts are aimed at addressing institutionalized racism in school policies, practices, and cultural systems by implementing implicit bias training for teachers and staff. In this paper, we explain how a school home visits program, Parent Teacher Home Visits (PTHV), is a promising intervention for counteracting implicit biases and improving outcomes for families and students. The PTHV "relational" home visit model focuses on promoting mutually supportive and accountable relationships between educators and families. We present data from a study examining the experiences of 107 educators and 68 family members who participated in PTHV, showing how educators shifted their deficit assumptions about families and students. Although the PTHV model was not created to address implicit biases, we found that the key components of these home visits align with strategies that psychological research has demonstrated effectively counteracting implicit biases and reducing discriminatory behaviors.

Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new measure of student risk for use in education policies, which we call Predicted Academic Performance (PAP). PAP is a flexible, data-rich indicator that identifies students at risk of poor academic outcomes. It blends concepts from emerging "early warning" systems with principles of incentive design to balance the competing priorities of accurate risk measurement and suitability for policy use. PAP is more effective than common alternatives at identifying students who are at risk of poor academic outcomes and can be used to target resources toward these students--and students who belong to several other associated risk categories--more efficiently.

This paper provides new evidence on educational inequality and reviews the literature on the causes and consequences of unequal education. We document large achievement gaps between children from different socio-economic backgrounds, show how patterns of educational inequality vary across countries, time, and generations, and establish a link between educational inequality and social mobility. We interpret this evidence from the perspective of economic models of skill acquisition and investment in human capital. The models account for different channels underlying unequal education and highlight how endogenous responses in parents' and children's educational investments generate a close link between economic inequality and educational inequality. Given concerns over the extended school closures during the COVID-19 pandemic, we also summarize early evidence on the impact of the pandemic on children's education and on possible long-run repercussions for educational inequality.

This paper examines the scalability of the results from the Tennessee Student-Teacher Achievement Ratio (STAR) Project, a prominent educational experiment. We explore how the misalignment between the experimental design and the econometric model affects researchers' ability to learn about the intervention's scalability. We document heterogeneity in compliance with class-size reduction that is more extensive than previously acknowledged and discuss its consequences for the evaluation of the experiment. Guided by this finding, we implement a new econometric framework incorporating heterogeneous treatment effects and endogenous class size determination. We find that the effect of class size on test scores differs considerably across schools, with only a small fraction of schools having significant benefits from reduced class sizes. We discuss the challenges this poses for the intervention's scalability and conclude by analyzing targeted class-size interventions.

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular methodological framework for the analysis of educational data generally, and large-scale surveys more specifically. The report argues that Bayesian statistical methods can provide a more nuanced analysis of results of policy relevance compared to standard frequentist approaches commonly found in large-scale survey reports. The data utilised for this report comes from the OECD Teaching and Learning International Survey (TALIS). The report provides steps in implementing a Bayesian analysis and proposes a workflow that can be applied not only to TALIS but to large-scale surveys in general. The report closes with discussion of other Bayesian approaches to international large-scale survey data, in particularly for predictive modelling.

Global university rankings influence students' choices and higher education policies throughout the world. When rankers not only evaluate universities but also provide them with consulting, analytics, or advertising services rankers are vulnerable to conflicts of interest that may potentially distort their rankings. The paper assesses the impact of contracting with rankers on university ranking outcomes using difference-in-difference research design. The study matches data on the positions of 28 Russian universities in QS World University Rankings between 2016 and 2021 with information on contracts these universities had for services from QS -- a company that produces these rankings. The study estimates the effects of the conflicts of interest with two difference-in-difference models. The first model compares the difference in five-year change in rankings between QS rankings and Times Higher Education (THE) rankings across two groups of universities -- those that frequently (five times or more) contracted for QS services, and those that never or seldomly contracted for QS services. The second model compares the difference in five-year change in faculty-student ratios -- between scores in QS rankings, THE rankings, and scores recorded by national statistics -- across the same two groups of universities. The results suggest universities with frequent QS-related contracts had an increase of 0.75 standard deviations (~140 positions) in QS World University Rankings and an increase of 0.9 standard deviations in reported QS faculty-student ratio scores over five years, regardless of changes in the institutional quality. The study calls for universities, governments, and prospective students to reconsider their use of global rankings where conflicts of interest may be generated by the ranker's business activities.

In the field of education, we bump constantly into buzzwords, pass unclear phrases in the hall, and greet acronyms as good friends. Yet rarely is it that we unpack or critically examine what is meant when phrases are uttered. What does it actually "mean" to "enhance institutional effectiveness"? To "foster synergy"? To "improve student learning"? In the field of assessment, there is a stated desire for "more use of assessment results," to "close the loop." There is agreement that the purpose and intention for engaging in assessing student learning is to ultimately "improve student learning" but there is no clear framework for what "improving student learning" entails or what it means to "close the loop." However, there does seem to be agreement that whatever "use" might mean, there is not enough of it happening let alone with regularity (Kuh et al., 2015). This paper provides an overview of an alternative conception of use through the lens of evidence-based storytelling--an approach that has been used at the National Institute for Learning Outcomes Assessment (NILOA) to refine and encourage evidence-based stories in assessment (Jankowski & Baker, 2019). This occasional paper serves two main purposes: to re-examine what is meant by use of assessment results and to unpack evidence-based storytelling and its connection to assessment.

This article is a follow-up to a recent ROPS [Research & Occasional Paper Series] article on strategic budgeting at colleges and universities. In recent years, several colleges and universities have explored alternative strategies for developing operating budgets. In part, this exploration was driven by the desire for transparency among various constituent groups and the need to tie budgeting to campus strategic planning. While developing a new budgeting process can be a very intense and involved process, the ability to implement a new budget process requires the same level of commitment and involvement. A successful implementation process involves an effective communication process combined with training and the commitment of senior campus leadership.

Despite the growing evidence on promising approaches to postsecondary instruction--and particularly on the benefits of student-centered, conceptually oriented instruction for underprepared students--there has been limited investment in supporting these approaches' widespread implementation. Most postsecondary instructors have limited training in pedagogy, and broad-access colleges have relatively few resources to invest in improving instruction and building high-quality curriculum. Moreover, the field has few documented models of scalable professional development that results in demonstrated improvements in teaching and student learning. To help address this gap in the literature, this paper describes the professional development model used in CUNY Start, a program developed at the City University of New York to support entering students identified as academically underprepared in literacy and mathematics. Using interview and survey data collected as part of a larger random assignment evaluation of CUNY Start, the paper explores how CUNY Start's multifaceted, coordinated system of professional development supports postsecondary instructors in enacting a student-centered, conceptually oriented instructional approach. CUNY Start's professional development model has several notable features: a staffing approach that values instructional expertise, an apprenticeship for new hires, coaching through classroom observations, and cross-college meetings. While this model is distinct from traditional approaches to professional development in higher education, elements of it can be applied in other higher education settings. The paper concludes by discussing how colleges and departments might structure professional development around a set of student learning goals, offer a system of ongoing supports, and create a staffing model that supports the development of instructional expertise. [The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305H140065 to MDRC.]

In recent years a number of colleges and universities have explored alternative strategies for developing operating budgets. In part this exploration was driven by the desire for transparency among various constituent groups and the need to tie budgeting to campus strategic planning. With the advent of declining federal and state support, along with changing student demand, the need for a more strategic approach to budgeting has gained momentum. This paper highlights the various budgetary approaches currently in use and provides examples of their application in a variety of university settings. Particular emphasis is given to the process by which universities develop new models.

Formal leadership development programs enhance what students learn in the classroom by giving them powerful tools for personal and professional success. They are also a differentiator for many institutions. They help schools attract more high-ability students, distinguish themselves from peer institutions, and increase the value of a student's education. Leadership development helps students strengthen their communication and collaboration skills, develop resilience, become more adaptable, and prepare for a world in which they will be expected to be agile and innovative. This paper lays out five key practices for high-impact leadership development: (1) A proven leadership model and development framework; (2) Formative evaluation of students; (3) Relevant, meaningful leadership experiences; (4) Impactful coaching; and (5) Tools and methods that provide a rich, engaging experience. Student leadership development programs that include these 5 elements are much more likely to be successful in nurturing individual growth, improving post-graduation opportunities, and increasing student and alumni engagement with the university.

High-impact practices, such as learning communities, capstones, undergraduate research, and community-based experiences, are effective pedagogies. Most of these practices have been around for decades. By clustering the effective elements of these activities through the term "high-impact practices," we bring together elements which we know are effective pedagogies, without weight to any one practice over another. The vast majority of campuses can proudly point to multiple high-impact practices happening somewhere within their institutions, not just one or two. Thus, to talk singularly about high-impact practices--and the assessment of them--would be like evaluating just one tire on a car. To ultimately understand what makes an institution move requires looking at all of the moving parts. And given the intense focus across institutions of higher education on identifying, tagging, and touting their high-impact practices, assessment is what will separate the committed practitioners from the casual adopters. A good assessment plan for high-impact practices starts with acknowledging three things. One, the name alone does not make them high-impact. Two, evidence of effect requires assessing more than outcomes, alone. And three, assessment must be, at every stage, attentive to equity. Building upon these three ideas, this Occasional Paper outlines a process of effectively assessing high-impact practices at your institution.

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 paper describes a method for pooling grouped, ordered-categorical data across multiple waves to improve small-sample heteroskedastic ordered probit (HETOP) estimates of latent distributional parameters. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in each of a small number of ordered "proficiency" levels. HETOP models can be used to estimate means and standard deviations of the underlying (latent) test score distributions, but may yield biased or very imprecise estimates when group sample sizes are small. A simulation study demonstrates that pooled HETOP models can reduce the bias and sampling error of standard deviation estimates when group sample sizes are small. An analysis of real test score data suggests the pooled models are likely to improve estimates in applied contexts.

Under the Integrated Planning and Advising for Student Success (iPASS) initiative, 45 two- and four-year colleges have undertaken reforms that aim to provide students with seamless, holistic advising experiences that lead to improved academic outcomes. Colleges participating in iPASS have adopted a data-oriented approach to select and integrate new technologies into their advising practices to facilitate better interactions between students, faculty, advisors, and other student services staff. Based on research on iPASS and other advising redesign efforts, the Community College Research Center (CCRC) developed an evidence-based framework for advising redesign called SSIPP, which emphasizes a "sustained," "strategic," "integrated," "proactive," and "personalized" approach to advising. This paper describes the key principles of the SSIPP framework and illustrates how these principles have been adopted in reforms. The information and recommendations shared here are derived primarily from qualitative research conducted when iPASS reforms were being developed. The focus is on examples of practice and lessons learned.

The authors illustrate models and procedures that can be applied to calculate overall composite scores in order to identify an indicator of English language proficiency, based on composite scores for English learners with 504 or individualized education plans who are missing one or more domain scores on the Assessing Comprehension and Communication in English State-to-State for English Language Learners assessment for state monitoring, achievement, and accountability determinations. As a technical reference, the appendix includes tables and statistical programming code used to compute the different methods. The analyses and results provide clear and concise frameworks for approaching accountability criteria and decisions.

This white paper presents a selection of model schools who all have, to some degree, fostered deeper learning. Schools were selected by internet search, or through references in "deeper learning" reports and documents. It should be noted that information in these reviews is based on information from school web-sites, in some cases the web sites of state education agencies, media reports and ratings, such as those published by "US News and World Report" or "Newsweek." It is hoped that this paper will serve as a resource directory of sorts, giving interested parties the opportunity to read more widely about these schools, consult the referenced documents, or to contact the schools directly. [For "Innovation and Deeper Learning: Volume 2," see ED604592.]

A growing number of U.S. companies across a range of industries are designing apprenticeship programs to give workers access to on-the-job learning opportunities that allow them to transition into in-demand jobs and careers. This discussion paper provides a snapshot of the current state of apprenticeship in the United States based on interviews with national experts and key stakeholders engaged in apprenticeship implementation, including employers, community colleges, unions, and intermediaries. It explores what is needed to build successful programs and highlights current federal and state policy efforts to encourage registered apprenticeship expansion, noting barriers and lessons learned. Four recommendations for how to grow registered apprenticeship opportunities in the United States are: (1) Provide standardized models; (2) Reduce complexity; (3) Measure Value; and (4) Learn from Innovative Models. A sidebar presents examples of state incentives and supports for apprenticeship programs in Colorado, Maryland, and South Carolina. [This paper was produced with funding from the Nestlé USA corporation.]

A major factor in the overall enrollment decline in elementary and secondary Catholic schools during the past 50 years has been the migration of families from urban parish schools to suburban public education. Nearly 13,000 Catholic schools operated in the early 1960s. By 2016 that number was down to roughly 6,400. The enrollment decline coincided with rising expenses at Catholic schools. Schools in the Chicago-based Cristo Rey Network serve low-income families in urban areas, are doing what many thought impossible. Rather than losing students they are adding them. In its unique model, students receive a college-preparatory education and participate in a work-study program in which they learn employable skills and earn money to help pay for their tuition. Since the first Cristo Rey school was founded in Chicago in 1996, 31 others have opened in 21 states and the District of Columbia, including in Boston and Lawrence, MA, with plans to add eight more by 2020. This paper examines Cristo Rey schools, why they work, how they work and what parts of their education/business design can be successfully transferred to other Catholic high schools. It looks at the Cristo Rey Network, a cooperative organization formed to standardize the Cristo Rey approach, offer resources to the individual schools and help promote the spread of Cristo Rey schools to cities that can support them. Through interviews with founders and early backers this paper reviews the origins of the Cristo Rey method and how it has been replicated in places such as Cristo Rey Boston High School and Notre Dame Cristo Rey High School in Lawrence. And it looks to see see what lessons can be drawn by other Catholic high schools wrestling with sliding enrollment and shrinking income.

In many countries, schools and classrooms are becoming increasingly diverse along a variety of dimensions, including migration; ethnic groups, national minorities and Indigenous peoples; gender; gender identity and sexual orientation; special education needs; and giftedness. To navigate this diversity, adopting a multidimensional and intersectional lens could help education systems promote equity and inclusion in education and foster the well-being and learning of all students. Such an approach could also support education systems in preparing all individuals so that they can engage with others in increasingly complex and diverse societies. To build equitable and inclusive education systems, analysing policy issues regarding governance arrangements, resourcing schemes, capacity building, school-level interventions, and monitoring and evaluation is key. The "Strength through Diversity: Education for Inclusive Societies" project seeks to help governments and education systems address diversity to achieve more equitable and inclusive education systems. This paper presents the project's theoretical and analytical framework.

The traditional apprenticeship model for PhD education involves supervisors mentoring students through a substantive research project and ultimately into academia. Although about half of PhD graduates enter careers beyond academia, this apprenticeship model, with a narrow focus on thesis research has continued to dominate in many countries. While there are variations in terms of coursework requirements, the main assessment continues to be on the PhD thesis, and, in most countries, an oral defense of this thesis. The aims of this working paper are firstly to critique the dominant models of PhD education by using the lens of 'success', and secondly to consider an alternative model of PhD education. A PhD program may be deemed successful if it leads to high employment rates, high satisfaction with types of employment, and graduates who are well equipped for being in the world -- in work and in society. Through examining these indicators of success, I argue that the North American and British PhD models may be failing, and suggest an alternative model based on 'constructive alignment', in which the graduate outcomes are well aligned with teaching and learning methods, and the assessment regime. This alternative model is still based on an apprenticeship approach but requires PhD programs to be tailored to the individual and their desired career pathway, so that alongside and through their research, they can develop a holistic set of graduate attributes -- for 'doctorateness', for possible careers, and for global citizenship. This model has implications not only for the learning opportunities available to PhD students, but also for how we assess PhDs. Universities may need to develop programs to better support the career planning and professional development of PhD students. A portfolio or digital badge assessment approach, whether summative or formative, would allow PhD graduates to demonstrate the depth and breadth of knowledge and skills they have acquired through doctoral study, and better equip them for their chosen career pathway.

With an increased appreciation of students' social-emotional skills among researchers and policy makers, many states and school districts are moving toward a systematic process to measure Social-Emotional Learning (SEL). In this study, we examine the measurement properties of California's CORE Districts' SEL survey administered to over 400,000 students in grades 3 to 12 during the 2015-16 school year. We conduct analyses through both classical test theory and item response theory frameworks, applying three different polytomous IRT models on both the full student sample and on separate samples from each grade. From these analyses, we summarize the psychometric properties of items at each grade level, compare items' functionality across grades, compare student outcomes from IRT models and the classical approach, make suggestions on approaches to modeling and scaling the SEL survey data, and identify items, by grade, that do not contribute positively to measurement of each outcome. Finally, we discuss policy implications in using SEL measures among educators, administrators, policy makers, and other stakeholders.

The National Student Outcomes Survey (SOS) collects information about students who completed their vocational education and training (VET) in the previous calendar year. The gathered information on the surveyed VET students includes their reasons for training, employment outcomes, satisfaction with training, and further study outcomes. The survey covers students who have completed a qualification (graduates) and those who have completed only part of a course and then left the VET system (subject completers). The National Centre for Vocational Education Research (NCVER) has conducted the survey with government-funded VET students annually since 1999. In 2016, the scope of the survey was expanded to report on the outcomes of graduates whose training was Commonwealth--or state-funded as well as fee-for-service graduates. These graduates were referred to as total VET graduates. An explanation of the difference between total VET and government-funded student outcomes can be found in appendix A. The expanded scope was applied to the 2017 survey for graduates (following a successful trial in 2016) and for the first time for subject completers and the series renamed VET student outcomes. At the time of sample selection, insufficient information is available from the National VET Provider Collection to identify 'actual' subject completers. Instead, a sample of potential subject completers is chosen, which includes students who are continuing in the VET system. The status of respondents is determined through the survey responses. As such, respondents to the SOS include a number of students who were sampled as subject completers based on administrative data reported to the National VET Provider Collection, but self-identify in the questionnaire as graduates. For many years these 'self-reported graduates' (SRGs) were categorised as graduates in survey outputs, because the self-report was deemed to be more reliable than the collection data. However, it became apparent that many SRGs were not, in fact, graduates. In response to this issue, in 2012, NCVER created a logistic model that predicted the eligibility of a SRG being an 'actual' graduate based on their personal and training characteristics (Braysher 2012). This model has since been run annually for each SOS to assign group membership to SRGs. Those SRGs that were not predicted by the model to be a graduate were re-assigned to their original subject completer status. One of the conditions of the initial analysis was that the model should be reviewed at least every four years to assess its ongoing validity and to make possible modifications should demographics and administrative data change and alter the predictive power of the model. The model was reviewed by NCVER in 2015 (unpublished). The review found some changes in data quality, but found no evidence that these changes were affecting the estimates. At the time no changes were recommended to the logistic model or graduate reclassification procedure, but it was recommended that the model be reviewed again at a later stage. In relation to data quality, the proportion of subject completers claiming to be self-reported graduates has declined significantly since 2007, particularly from 2015 to 2017, highlighting the improvement in the quality of the National VET Provider Collection data since the need to run the model arose (appendix B). Hence, it was appropriate to review the model again. This report presents the findings of an additional comprehensive review of the model and methodology.

The aim of the paper is to review scholarly attempts to define or explain vocational education and training and to develop a theoretical model to analyse national definitions or conceptions of VET [vocational education and training] and how they have changed over time. VET takes many forms and is, perhaps, the least unitary of education sectors. Based on a literature review of previous attempts to characterise VET, the paper suggests using a multi-perspective framework which combines: (a) an epistemological and pedagogical perspective; (b) a system and institutional perspective; and (c) a socioeconomic and labour market perspective to analyse VET. These perspectives can help to identify appropriate learning approaches, institutional solutions and forms of cooperation to work towards. In Volume 2 of this series, the approach is empirically tested and the different understandings of VET in 30 European countries are illustrated. [This research paper is the first in a series produced as part of the Cedefop project, "The changing nature and role of VET (2016-18)." The research was carried out by a consortium led by 3s Unternehmensberatung GmbH. For Volume 2, see ED586252. For Volume 3, see ED586256.]

While there are many causes at the root of the academic achievement gap between high- and low-income students, one that is seldom acknowledged is summer learning loss, which disproportionally affects low-income and minority students. With a wide achievement gap across all regions of Massachusetts, private schools in the commonwealth should consider offering summer enrichment programs, which have been shown to promote student achievement, to underserved students as a tool to combat this trend. This paper compares the costs and tuition at typical summer programs run by elite private schools to "mission-based" programs that actively recruit disadvantaged students to offer high-quality, longer-term educational experiences. Findings indicate that elite schools often offer single-summer day programs for $5,500 or more per student for five weeks of instruction, while programming at other schools that extend the program for twelve months, multiple summers or multiple full years can operate at less than half the cost. Not only are these expanded programs cost-efficient, but they fulfill a mission to educate underprivileged students who are most at-risk for summer learning loss.

Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex specifications, raising the possibility that results are sensitive either to sample restrictions or to alternative specifications. Also, the extra requirements might not be justified if results from fixed effects models are broadly similar to those from conventional ordinary least squares models. In this paper we review results from fixed effects models of the earnings gains from completing an associate degree relative to non-completion for community college students. We examine both sampling restrictions and specification issues. We find results to be sensitive to assumptions about missing earnings data and to how time trend specifications are modeled. However, we find no substantively meaningful differences between estimates using fixed effects models and ordinary least squares methods. A main benefit of fixed effects models--controlling for unobservable student characteristics--should be weighed against the difficulty in interpreting coefficients and more intensive data requirements. On the other hand, a distinct advantage of fixed effects models is that they allow for analysis of earning profiles over the period from before to after college. Given the large fluctuations in earnings over this period, this advantage may be significant in yielding evidence on the full returns to college. The following two tables are appended: (1) Robustness Checks on Returns to Associate Degrees; and (2) Percentage Decline in Earnings From Two Quarters Prior to College Entry to Quarter of College Entry (Kentucky, Ohio).

College attendance is a risky investment. But students may not recognize when they are at risk for failure, and financial aid introduces the possibility for moral hazard. Academic performance standards can serve three roles in this context: signaling expectations for success, providing incentives for increased student effort, and limiting financial losses. Such standards have existed in federal need-based aid programs for nearly 40 years in the form of Satisfactory Academic Progress (SAP) requirements, yet have received virtually no academic attention. In this paper, we sketch a simple model to illustrate not only student responses to standards but also the tradeoffs faced by a social planner weighing whether to set performance standards in the context of need-based aid. We then use regression discontinuity and difference-in-difference designs to examine the consequences of SAP failure. In line with theoretical predictions, we find heterogeneous effects in the short term, with negative impacts on persistence but positive effects on grades for students who remain enrolled. After three years, the negative effects appear to dominate. Effects on credits attempted are 2-3 times as large as effects on credits earned, suggesting that standards increase the efficiency of aid expenditures. But it also appears to exacerbate inequality in higher education by pushing out low-performing low-income students faster than their equally low-performing, but higher-income peers. A table on DID Estimated Effects of Failing GPA Performance Standard At End of Year 1, No Covariates is appended.

Improving public sector workforce quality is challenging in sectors such as education where worker productivity is difficult to assess and manager incentives are muted by political and bureaucratic constraints. In this paper, we study how providing information to principals about teacher effectiveness and encouraging them to use the information in personnel decisions affects the composition of teacher turnovers. Our setting is the Houston Independent School District, which recently implemented a rigorous teacher evaluation system. Prior to the new system teacher effectiveness was negatively correlated with district exit and we show that the policy significantly strengthened this relationship, primarily by increasing the relative likelihood of exit for teachers in the bottom quintile of the quality distribution. Low-performing teachers working in low-achieving schools were especially likely to leave. However, despite the success, the implied change to the quality of the workforce overall is too small to have a detectable impact on student achievement. Supplementary tables are appended.

Students who have mastered the ability to create their own learning environments have an advantage over students who rely on traditional environments to structure their learning. Students who understand how to use new tools for school learning typically do not pick up these skills at school--they learn from the habits of parents and peers who work in knowledge fields (Watkins, 2013). Widespread access to many innovations in the digital world has great promise in engaging all students in 21st century learning, but without the active role of schools to remediate the class distinctions, the participation gap will continue to widen in ways that reflect social inequalities. This paper addresses the gap between the potential of new media tools for transforming learning in and out of schools and the school commitment to technologies that support testing and accountability. The authors argue that the gap between schools and digital worlds can be "intentionally bridged" if affordances of widely used new media environments and tools, such as makerspaces, video games, citizen science, fantasy sports and youth media arts organizations are matched with needs that traditional schools often struggle to meet. Matching affordances with needs means that educators do not have to invent entirely new approaches to teaching and learning. Rather, they can leverage learning practices widely used outside schools to answer questions raised by teachers and learners in schools. The authors propose the idea of "participatory culture" as a robust model for how to think about the emerging practices of learning in digital media spaces. The participatory culture framework helps to make sense of learning in and out of schools, and points toward viable paths to integrate the best of new media experience into contemporary school design.

Over the past few years, a multitude of studies have examined the labor market returns to community college credentials, taking advantage of new administrative datasets that link college transcripts to quarterly earnings records and allow for comparisons of students' earnings before and after enrollment. These studies, however, typically follow students for only four to six years after initial entry, meaning they may only be observed for a year or two after graduation. Graduates' early labor market experiences may not fully capture the returns to completion, and may particularly distort comparisons of longer versus shorter duration credential programs. We extend the literature by examining returns to terminal associate degrees and certificates up to 11 years after students initially entered a community college in Ohio. We use an individual fixed-effects approach that controls for students' pre-enrollment earnings and allows the returns to credential completion to vary over time. Additionally, we examine how the returns to credential completion shift as students enter and exit the Great Recession, as well as how credentials affect other labor market outcomes such as employment stability and the likelihood of earning a "living wage." Our results confirm prior findings regarding the positive early returns to associate degrees and long-term certificates. However, the value of an associate degree grows substantially after graduation while the returns to a long-term certificate remain flat. Returns to associate degrees are notably higher during the recession (the patterns for certificates are more muted and vary by gender). Finally, we find that while both associate degrees and long-term certificates increase the likelihood and stability of employment, associate degrees lead to much higher paying jobs and a greater likelihood of earning a living wage. We conclude with a discussion of policy implications.

Organizational life has become less predictable in today's rapidly changing workplace. Workers must make career decisions within an increasingly uncertain organizational, societal, and global environment. Businesses face the same evolving landscape, making it difficult for them to anticipate their employees' needs, desires, and likely career directions. Career pathways systems can provide the structure that is vital for career progression, helping people develop competencies designed to increase employability while helping organizations develop employees strategically, build engagement, and improve retention. In our focus on the workplace, we underscore the need for more holistic, data-driven individual and organizational perspectives on career growth and success; we describe how a career pathways framework can contribute to these goals. We offer directions for future research to promote career growth and success for individuals, and to help employers create or strengthen career pathways systems that will reduce bias and enhance organizational performance by supporting the advancement of their employees.

The authors develop model analyses based on a U.S. Department of Education guide to illustrate procedures a State could use to compare and contrast school-level overall and English Learner accountability determinations for proficiency in reading/language arts under the options allowed by the Every Student Succeeds Act. As a technical reference, the appendix provides detailed tables and statistical programming code used to compute modelled outcomes under the different accountability options. These model analyses are provided only to illustrate how a State could undertake them as part of its efforts to develop and explore a theory of action for assessment of recently arrived English learners.