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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.

Nearly two dozen states now administer online exams. These tests have real consequences: their results feed into accountability systems, which have been used for more than a decade to hold schools and districts accountable for their students' learning. We examine the rollout of computer-based testing in Massachusetts over 2 years to investigate test mode effects. Crucial to the study design is the fact that the state administers the same exam (PARCC) in online and offline formats each year during the transitional period. We find mode effects of about 0.10 standard deviations in math and 0.25 standard deviations in English language arts (ELA). Our preferred estimates of the effects of online testing in the second year of administration suggest that mode effects for second-time test takers were about one third as large as the first year in math and about half as large in ELA. There is little evidence of systematic variation in mode effects by student demographic groups, although on ELA tests they are larger for students scoring at the bottom of the achievement distribution.

Community college transfer students encounter challenges progressing toward a bachelor's degree, leading to widespread transfer credit loss. This in turn may lower students' chances of credential completion and increase the time and costs for students, their families, and taxpayers. In this study we review three definitions of credit transfer inefficiency--"credit transferability," "credit applicability," and "excess credits among completers"--focusing on the last to examine why students who start at a community college and transfer to a four-year institution so often end up with excess credits that do not count toward a bachelor's degree. To shed light on credit transfer inefficiency, we examine the course-taking behaviors of community college transfer students who earn bachelor's degrees with numerous excess credits compared with transfer students who earn bachelor's degrees with few excess credits. We employ data-mining techniques to analyze student transcripts from two state systems, enabling us to examine a large number of variables that could explain the variation in students' excess credits at graduation. These variables include not only student demographics but also the types and timing of courses taken. Overall, we find more excess credits associated with several factors, including taking larger proportions of 100- and 200-level courses and smaller proportions of 300-level courses throughout students' progression toward completion, and taking 100-level courses in any subject--and specifically 100-level math courses--immediately after transferring to a four-year institution. Findings suggest that institutions could help students reduce credit transfer inefficiency by encouraging them to explore and choose a bachelor's degree major early on so they can take the required lower division (100- and 200-level) courses at the community college, thereby enabling them to take mostly upper division 300- and 400-level courses in their desired major field once they transfer to a four-year institution.

In this study, we compare the teacher quality distributions in charter schools and traditional public schools, and examine mechanisms that might explain cross-sector differences in teacher effectiveness as measured by teacher value-added scores using school and teacher level data from Florida. We have three main findings. First, we find that teachers working in above-average poverty charter schools have significantly higher value-added scores compared to traditional public school teachers working in similar settings, which is mainly driven by the right tail of the value-added score distribution, yet we find no such differences in below-average poverty settings. Second, we find that cross-sector differences in observed teacher characteristics such as experience and educational attainment fail to explain any of the observed gaps in teacher effectiveness in higher-poverty settings. Instead, we find that differences in returns to experience on teacher productivity, which is significantly higher in the charter sector, explains most of the observed cross-sector effectiveness gaps. Third, we find considerable differences in teacher support and teacher influence on instructional policies and practices between charter schools and traditional public schools, which might help explain the higher returns to experience on teacher effectiveness as well as the observed effectiveness gaps between charter schools and traditional public schools serving disadvantaged students.

Affirmative action in higher education can lead to mismatch, where students admitted through preferential treatment struggle academically due to inadequate preparation before college. Although some students may face initial challenges, by providing access to quality education for talented individuals who might have otherwise been overlooked due to systemic disadvantages, these programs may enable students to bridge the gap and catch up to their peers. In this study, we examine the effects of a quota-type affirmative action policy on gaps in college outcomes between potential beneficiaries and non-beneficiaries. Using comprehensive administrative data from a leading Brazilian university which implemented affirmative action in 2005, we find that compared to their non-quota peers, potential quota beneficiaries are less likely to progress smoothly through college and less likely to graduate, a result that is mostly driven by those who would not be admitted to the university otherwise. Notably, however, most of these differences shrink as the students progress through college, suggesting a catch-up effect between those groups. While potential quota students initially face challenges, resulting in a reduced course load in their early college years, they compensate by taking more credits in later years to ultimately graduate. [Additional funding for this report was provided by the Heinz College at Carnegie Mellon University, the Federal University of Bahia (UFBA), and the World Institute for Development Economics Research (UNU-WIDER).]

This paper examines evidence from the HESA DLHE six-month Censuses and 3½ year ('longitudinal') surveys relating to three aspects of the flows of those who have left university with Higher Education Engineering qualifications, to test the robustness of the conclusions of SKOPE Research Paper No. 122 (Dixon, 2015), which showed strong evidence that most Engineering graduates do not go on to work in the sectors of the economy that might be expected, in particular in the 'natural' Manufacturing sub-sector. Specifically, the paper examines three questions: (1) whether evidence of starting salary levels for those from particular disciplines going into particular sectors could explain the relative flows (on the assumption that higher salaries for graduate vacancies in a particular sector would attract more applications); (2) whether evidence of sector destinations three years on from the (six-month after graduation) Census data analysed in Dixon (2015) would show up significantly different levels of 'leakage'; and (3) whether those entering employment having completed Taught Masters (as opposed to First Degree) courses in particular Engineering disciplines would tend (in the light of their apparent greater interest and deeper understanding in the specific discipline) to enter the "expected" sectors more than their Bachelors colleagues. The "bottom line" answers to these questions is that -- with rather minor exceptions -- none of the relevant broader evidence from HESA DLHE data over a ten-year period significantly questions the very considerable 'leakage', away from the 'natural' Manufacturing sub-sector, that was found and presented in Dixon (2015). (1) There is "some" correlation between the "average salaries offered" (by employers in each 'destination' sector to cohorts from each Engineering discipline examined) and the "size of the flows" from each discipline into each sector, but it is limited and rarely strong. While there might be reasons why average salary differences might not be large enough to provide a sufficient incentive for Engineering graduates to choose one sector over another, evidence of considerably greater correlation would have been helpful to justify the traditional response of classical economics to employers' concerns about shortages: "offer more money"! (2) While there are sample size issues constraining the statistical precision of comparisons between the two DLHE surveys, these have been addressed, and comparisons of the "linear flows" of graduates from each discipline into the natural Manufacturing sub-sector show (a) comparatively very small differences, and (b) on balance, slightly "greater" 'leakage' three years on; and (3) More MSc's in "Automotive" and "Aerospace Engineering" have, over the ten years examined, then gone into the "Manufacture of Motor Vehicles"... and "Air and Space craft manufacture" (respectively) than BEng's from these disciplines. However, for the other disciplines compared, there is little difference, and -- in terms of entry into Manufacturing as a whole, for the most recent year in the period - the fraction of the disciplinary cohorts entering "any type of Manufacturing" is slightly "higher" for MSc's than First Degree (FD) graduates in "three" Engineering disciplines, though "lower" for MSc's than FD's in "four"! This new evidence, therefore, only serves to "strengthen" the great importance of NOT assuming linear flows of Engineering graduates into the "natural" Manufacturing sub-sectors corresponding to their discipline, in particular in policy responses to reports of shortages from such sub-sectors.

Internationally, Australia's tertiary education system, comprising the higher education and vocational education and training (VET) sectors, is highly regarded, with both sectors subject to ongoing national review and reforms. This paper explores in detail the multiple issues that lie at what might be termed the "boundaries and connections" between these sectors. The purpose of this occasional paper is twofold, the first being to provide a brief illustration and commentary on the relative trend change and potential trajectories of Australia's vocational education and training (VET) sector by comparison with the higher education sector. This provides the necessary context for the second objective, which is to explore in detail the multiple issues that lie at what might be described as the "boundaries and connections" between these two components of the tertiary education sector.

This paper focuses on the authors' experiences teaching on Ohio University's Learning Network (OULN), which uses interactive television and real-time face-to-face interaction as a distance-education (DE) delivery tool. One of the authors is a sociology professor, and the other is her former student and an experienced OULN system operator. The transition to DE from a traditional, less technological approach presents numerous challenges as well as opportunities. This paper compares the semester-long progress of two different sociology courses that used the OULN. It presents an analysis of each class's strengths and weaknesses, along with qualitative data based on interviews with each class's students, as recorded in a diary that the authors kept throughout the semester on the progress of each class. One class experienced more success than the other, which presented numerous teaching challenges. The paper concludes by offering guidance for integrating traditional teaching methods, including group work, into DE environments.

The change of government in 2010 provoked a large structural change in the English education landscape. Unexpectedly, the new government offered primary schools the chance to have "the freedom and the power to take control of their own destiny", with better performing schools given a green light to convert to become an academy school on a fast track. In England, schools that become academies have more freedom over many ways in which they operate, including the curriculum, staff pay, the length of the school day and the shape of the academic year. However, the change to allow primary school academisation has been controversial. In this paper, we study the effect for the first primary schools that became academies. While the international literature provides growing evidence on the effects of school autonomy in a variety of contexts, little is known about the effects of autonomy on primary schools (which are typically much smaller than secondary schools) and in contexts where the school is not deemed to be failing or disadvantaged. The key finding is that schools did change their modes of operation after the exogenous policy change, but at the primary phase of schooling, academisation did not lead to improved pupil performance. An appendix provides information on the way in which the sample of pupils and schools are selected for the analysis of primary academies and on issues related to the school income and expenditure data analysed in the paper. [This paper was produced as part of the Centre for Economic Performance's Education and Skills Programme.]

The rise of the accountability movement in education has resulted in the proliferation of school report cards, school ratings and rankings, and other kinds of performance reporting for public consumption and policy use. To understand the strengths and limitations of school rating systems and the role they play in shaping public perceptions and school improvement practices, this paper situates rating systems within the broader field of comparative organizational assessments and neo-institutional theory; describes school rankings and rating systems in use by states and consumer-oriented enterprises; and details four aspects of school ratings (measurement, transformation, integration, and presentation) that affect their use and interpretation.

This paper provides the first population-based evidence on how much standardized test scores vary among public school districts within each state and how segregation explains that variation. Using roughly 300 million standardized test score records in math and ELA for grades 3 through 8 from every U.S. public school district during the 2008-09 to 2014-15 school years, we estimate intraclass correlations (ICCs) as a measure of between-district variation. We characterize the variation in the ICCs across states, as well as the patterns in the ICCs over subjects, grades and cohorts. Further, we investigate the relationship between the ICCs and measures of racial and socioeconomic segregation. We find that between-district variation is greatest, on average, in states with high levels of both white-black and economic segregation.

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).

The increasing availability of massive administrative datasets linking postsecondary enrollees with post-college earnings records has stimulated a wealth of new research on the returns to college, and has accelerated state and federal efforts to hold institutions accountable for students' labor market outcomes. Many of these new research and policy efforts rely on state databases limited to postsecondary enrollees who work in the same state post-college, with limited information regarding family background and pre-college ability. In this paper, we use recent waves of data from the National Longitudinal Survey of Youth 1997 (NLSY97) to provide new, nationally representative, non-experimental estimates of the returns to degrees, as well as to assess the possible limitations of single-state, administrative-data-based estimates. To do this we evaluate how the national estimates change, depending upon the baseline comparison group, adjustments for pre-college achievement and family background, and alternative ways of addressing interstate mobility. We conclude with a discussion of the relative advantages and disadvantages of survey versus administrative data for estimating returns to college, as well as implications for research and policy efforts based upon single-state administrative databases. The appendices presented here include: (1) Definitions and Additional Notes for Key Variables; (2) Additional Details of Data Cleaning; (3) Comparing Self-Reported and Administrative College Enrollment and Attainment Data; (4) Results of Crosschecking Self-Reported Survey Data and Postsecondary Transcripts Data for the NLSY97; and (5) Selected Studies on the Labor Market Returns to Postsecondary Education. [For the full report: "Estimating Returns to College Attainment: Comparing Survey and State Administrative Data Based Estimates," see ED573076.]

The increasing availability of massive administrative datasets linking postsecondary enrollees with post-college earnings records has stimulated a wealth of new research on the returns to college, and has accelerated state and federal efforts to hold institutions accountable for students' labor market outcomes. Many of these new research and policy efforts rely on state databases limited to postsecondary enrollees who work in the same state post-college, with limited information regarding family background and pre-college ability. In this paper, we use recent waves of data from the National Longitudinal Survey of Youth 1997 (NLSY97) to provide new, nationally representative, non-experimental estimates of the returns to degrees, as well as to assess the possible limitations of single-state, administrative-data-based estimates. To do this we evaluate how the national estimates change, depending upon the baseline comparison group, adjustments for pre-college achievement and family background, and alternative ways of addressing interstate mobility. We conclude with a discussion of the relative advantages and disadvantages of survey versus administrative data for estimating returns to college, as well as implications for research and policy efforts based upon single-state administrative databases. [For "Estimating Returns to College Attainment: Comparing Survey and State Administrative Data Based Estimates: Appendices A, B, C, D, and E," see ED573077.]

In preparation for online administration of the ACT® test, ACT conducted studies to examine the comparability of scores between online and paper administrations, including a timing study in fall 2013, a mode comparability study in spring 2014, and a second mode comparability study in spring 2015. This report presents major findings from these studies, focusing on the mode comparability studies.

While destination-country education provides many potential advantages for immigrants, empirical studies in Australia, Canada and the United States have produced mixed results on the labour outcomes of immigrants who are former international students. This study uses large national longitudinal datasets to examine cross-cohort trends and within-cohort changes in earnings among three groups of young university graduates: immigrants who are former international students in Canada (Canadian-educated immigrants), foreign-educated immigrants who had a university degree before immigrating to Canada and the Canadian-born population. The results show that Canadian-educated immigrants on average had much lower earnings than the Canadian-born population but higher earnings than foreign-educated immigrants both in the short term and in the long term. However, Canadian-educated immigrants are a highly heterogeneous group, and the key factor differentiating their post-immigration earnings from the earnings of the Canadian-born population and foreign-educated immigrants is whether they held a well-paid job in Canada before becoming permanent residents.

In lower- and middle-income countries, including Ghana, students in rural areas dramatically underperform their urban peers. Rural schools struggle to attract and retain professionally trained teachers (GES 2012; World Bank 2012). We explore one potential solution to the problem of teacher recruitment: distance instruction. Through a cluster randomized controlled trial, we estimate the impact of a program that broadcasts live instruction via satellite to rural primary school students. The program equipped classrooms in 70 randomly selected Ghanaian schools with the technology required to connect to a studio in Accra. An additional 77 schools served as the control. Instructors in Accra provided math and English lessons to classrooms in the treatment group. The model is interactive, and students in satellite classes could communicate in real time with their remote teachers. We estimate significant gains (p<0.05) in rural students' numeracy and foundational literacy skills. We find no impact on attendance and classroom time-on-task (as measured through unannounced classroom observations), suggesting that these gains may result from improved instructional quality rather than from increased instruction time.

There is no comprehensive database of U.S. district-level test scores that is comparable across states. We describe and evaluate a method for constructing such a database. First, we estimate linear, reliability-adjusted linking transformations from state test score scales to the scale of the National Assessment of Educational Progress (NAEP). We then develop and implement direct and indirect validation checks for linking assumptions. We conclude that the linking method is accurate enough to be used in analyses of national variation in district achievement, but that the small amount of linking error in the methods renders fine-grained distinctions among districts in different states invalid. Finally, we describe several different methods of scaling and pooling the linked scores to support a range of secondary analyses and interpretations.

The percentage of students retaking college admissions tests is rising (Harmston & Crouse, 2016). Researchers and college admissions offices currently use a variety of methods for summarizing these multiple scores. Testing companies, interested in validity evidence like correlations with college first-year grade-point averages (FYGPA), often use the most recent test score available (Allen, 2013; Mattern & Patterson, 2014). In contrast, institutions report using a variety of composite scoring methods for applicants with multiple test records, including averaging and taking the maximum subtest score across test occasions ("superscoring"). We compare four scoring methods (average, highest, last, and superscoring) on two criteria. First, we compare correlations between scores from each scoring method and FYGPA. We find them similar (?? ˜ 0.40). Second, we compare scores from each scoring method based on whether they differentially predict FYGPA across the number of testing occasions (retakes). We find that retakes account for additional variance beyond standardized achievement and positively predict FYGPA across all scoring methods. We also find that superscoring minimizes this differential prediction--although it may seem that superscoring should inflate scores across retakes, this inflation is "true" to the extent that it accounts for the positive effects of retaking for predicting FYGPA. Future research should identity what factors, such as academic motivation and socioeconomic status, are related to retesting and consider how these should be considered in college admissions.

A growing body of research provides evidence that quality early childhood experiences can affect a host of life outcomes. Equally well documented is the variation in the quality of prekindergarten programs (pre-K) offered to children. In this study I employ a fuzzy regression discontinuity approach to evaluate the efficacy of Transitional Kindergarten (TK) on student outcomes in the San Francisco Unified School District. TK is a highly regulated, state funded, early education program. Importantly, universal prekindergarten was already established in San Francisco, making this study a comparison of prekindergarten opportunities. This study tests whether a more highly regulated pre-K program, situated solely in schools, can provide benefits to young five year olds over a modern, robust universal pre-K market. I find that students who attended TK outperform their peers on a variety of foundational literacy skills, with some evidence that the gains are larger for minority children. TK, however, had little effect on the rate of absences in kindergarten and first grade

The purpose of this work was to examine the effect of classroom teachers who earn certification as a National Board Certified Teacher (NBCT) by the National Board for Professional Teaching Standards on mathematics and reading achievement and behavioral outcomes (attendance and discipline referrals) for students in Grades 4 and 5. Two studies were conducted separately to examine the effect of NBCTs in North Carolina and Kentucky, which are two states with relatively high concentrations of NBCTs. In each study, propensity score matching was used to match students of NBCTs to similar students of non-NBCTs. Within each grade and within each study, propensity score matching yielded similar student groups (those taught by NBCTs and those not taught by NBCTs) on observed characteristics such as prior-year outcomes and demographics. For each grade level, the academic and behavioral outcomes of students of NBCTs were compared with the outcomes of the matched students taught by non-NBCTs. In North Carolina, there were no statistically significant student achievement differences at either grade between students of NBCTs and students of non-NBCTs. However, Grade 5 students of NBCTs had higher attendance rates than students of non-NBCTs by 0.02 standard deviations. There were no statistically significant effects on the likelihood of a student receiving an in-school or out-of-school suspension in North Carolina. In Kentucky, Grade 5 students taught by NBCTs scored higher than students of non-NBCTs on state student achievement in mathematics and reading by 0.06 standard deviations. There were no statistically significant differences in the behavioral outcomes between the student groups at either grade level in Kentucky.

It is widely believed that teacher turnover adversely affects the quality of instruction in urban schools serving predominantly disadvantaged children, and a growing body of research investigates various components of turnover effects. The evidence at first seems contradictory, as the quality of instruction appears to decline following turnover despite the fact that most work shows higher attrition for less effective teachers. This raises concerns that confounding factors bias estimates of transition differences in teacher effectiveness, the adverse effects of turnover or both. After taking more extensive steps to account for nonrandom sorting of students into classrooms and endogenous teacher exits and grade-switching, we replicate existing findings of adverse selection out of schools and negative effects of turnover in lower-achievement schools. But we find that these turnover effects can be fully accounted for by the resulting loss in experience and productivity loss following the reallocation of some incumbent teachers to different grades. Supplemental tables are appended.

As pushes for increased accountability in higher education continue, postsecondary institutions are interested in identifying early on students who are at risk of leaving their institution. With this in mind, this study sought to identify incoming first-year student information (such as that available on the ACT student record) that postsecondary institutions might use for determining students who are at-risk of leaving their institution in year two. Specifically, student characteristics were examined in relation to two types of attrition for the institution--students dropping out of college and students transferring to another institution--in comparison to students returning in year two. Data were available for more than 630,000 ACT-tested 2014 high school graduates who enrolled in college in fall 2014 at nearly 1,150 two- and four-year institutions. Initial and subsequent enrollment was tracked using National Student Clearinghouse data. Data on student-level characteristics evaluated included academic preparation and achievement measures; college intentions about living on campus, enrolling full-time, and working while in college; educational goals; the number of college preferences met by the initial institutions; the distance between home and initial institution attended; and demographic characteristics. Student's college intentions, college preference matches, and distance from home were included in the study as possible proxies for barriers to social and academic integration at the initial institution attended. Hierarchical multinomial regression models accounting for institution attended were used to estimate retention and attrition rates. Results were examined by type of institution. Study findings suggest that multiple academic and non-academic factors are useful for predicting student attrition. First, at both two- and four-year institutions, students who were less academically prepared for college were more likely than those who better prepared to drop out of college. Academic readiness was also negatively related to transfer at four-year institutions but was somewhat positively related to transfer at two-year intuitions. College intentions also played a role in identifying who was likely to leave their initial institution. For example, students who indicated that they planned to work more hours while in college were more likely to drop out of college than those intending to work fewer hours. Additionally, the fewer the number of college preferences met by the initial institution attended the more likely a student was to drop out or transfer to another institution. Attending an institution farther away from home was also associated with higher transfer rates. Unfortunately, even after statistically controlling for academic measures and other student characteristics, students from certain underserved demographic groups (e.g., first-generation students and economically disadvantaged students) continued to be somewhat more likely than their peers to drop out. In secondary analyses, retention and attrition rates were found to vary across college majors and by institutional characteristics. Study findings illustrate how institutions can use incoming student information from the ACT record to help identify students who are at-risk of leaving their institution, allowing for the opportunity to intervene early with these students. The ACT student record contains additional data elements beyond those examined in this study that can help institutions build multidimensional models of student success in order to better identify students who might benefit from additional academic and student support services upon entering college.

This paper illustrates similarities and differences between two international surveys that assess adults' skills: the Programme for the International Assessment of Adult Competencies (PIAAC) and the Skills Towards Employment and Productivity (STEP) survey. In particular, the paper highlights the issues that can arise for researchers interested to jointly analyse the data from the two surveys and to compare their results. The paper finds that, in spite of the many similarities, important differences exist between PIAAC and STEP, both in the way the data are collected, and in the way the proficiency of respondents is estimated. These issues can indeed affect the cross-country comparability of results from the two surveys. There is instead little evidence that the literacy assessment used in the two surveys is not adequate to form a basis for a valid assessment of adults' proficiency on a global scale.

The Kauffman School is a public charter school that serves students from low-income neighborhoods in Kansas City, Missouri. This paper used a matched comparison group design to estimate the impacts of the Kauffman School on student achievement, attendance, and suspensions. We found that the Kauffman School had positive and statistically significant impacts on student achievement in mathematics, reading, and science. This paper also used surveys, interviews, focus groups, and classroom observations to describe the hallmarks and operations of the Kauffman School and explore possible mechanisms for its effects, informing the literature on school effectiveness. We found evidence that the Kauffman School's hallmarks are largely being implemented faithfully, and that key stakeholders believe the Kauffman School's methods are having a positive influence on students' behavior, attitudes, and performance. The following are appended: (1) Data Preparation Details for Impact Analysis; (2) Data for Analysis of School Hallmarks; (3) Sample Selection for Impact Analysis; (4) Multiple Imputation Methodology; (5) Propensity-Score Matching Methodology; (6) Additional Attendance and Suspension Impact Estimates; and About the Series.

With the advent of outcomes-based funding policies, state policymakers are increasingly committed to basing public college and university funding on how institutions perform on valued measures such as program progress and degree completion. This rising emphasis is considered here in the historical context of three earlier state funding approaches: "base-plus" approaches, enrollment-based formula-funding approaches, and early performance-based funding approaches. After detailed reviews of these funding approaches and the newer outcomes-based approach, the four models' respective strengths and weaknesses are reviewed comparatively. This paper then identifies some central conclusions for policymakers in this arena. [This paper was prepared for HCM Strategists, LLC.]

The number of countries that regularly participate in international large-scale assessments has increased sharply over the past 15 years, with the share of countries participating in the Programme for International Student Assessment growing from one-fifth of countries in 2000 to over one-third of countries in 2015. What accounts for this increase? This paper explores the evidence for three broad explanations: globalization of assessments, increasing technical capacity for conducting assessments, and increased demand for the microeconomic and macroeconomic data from these assessments. Data were compiled from more than 200 countries for this analysis, for six time periods between 2000 and 2015, yielding more than 1,200 observations. The data cover each country's participation in each of six cycles of PISA as it relates to the country's level of economic development, region, prior experience with assessment, and OECD membership. The results indicate that the odds of participation in PISA are markedly higher for OECD member countries, countries in the Europe and Central Asia region, high- and upper-middle-income countries, and countries with previous national and international assessment experience; the paper also finds that regional assessment experience is unrelated to PISA participation.

In July 2010, the Massachusetts Board of Elementary and Secondary Education (BESE) voted to adopt Common Core's standards in English language arts (ELA) and mathematics in place of the state's own standards in these two subjects. The vote was based largely on recommendations by Commissioner of Education Mitchell Chester and then Secretary of Education Paul Reville, and on the conclusions in three studies comparing the state's standards with Common Core's, all financed directly or indirectly by the Bill & Melinda Gates Foundation, and all issued by organizations that are among the primary boosters of Common Core (Achieve, Inc., Thomas B. Fordham Institute, and Massachusetts Business Alliance for Education). Nevertheless, annual state testing for school and district accountability continued as part of the Massachusetts Comprehensive Assessment System (MCAS) mandated by the 1993 Massachusetts Education Reform Act (MERA). To accommodate the adoption of Common Core's standards, tests were based on both the old standards and an annually increasing number of Common Core's standards until 2015, when all of the pre-Common Core standards in ELA and mathematics were archived, and the MCAS tests were presumably only Common Core-based. After the vote to adopt Common Core's standards in 2010, the state joined the testing consortium called Partnership for Assessment of Readiness for College and Careers (PARCC), funded by the United States Department of Education (USED) to develop common tests for its member states (about 25 initially), but with the costs for administering the tests to be borne by the states and local school districts. Since 2011, PARCC has been developing tests that BESE is expected to vote to adopt in the late fall of 2015 as the state's official Common Core-based tests in place of Common Corebased MCAS tests. (Indeed, the commissioner of education and his staff at the Department of Elementary and Secondary Education (DESE) have been implementing a transition to PARCC tests for several years.) BESE's official vote will be guided, again, by the recommendations of the same commissioner of education (who now also chairs PARCC's Governing Board), the current Secretary of Education James Peyser, and the conclusions reached in "external" studies comparing PARCC and MCAS tests as well as in about 20 studies directly authorized by PARCC. Two of the external studies are listed in the state's 2015 application to the USED for a waiver from No Child Left Behind Act requirements and are by organizations that had originally recommended adoption of Common Core. One, issued by the Massachusetts Business Alliance for Education in February 2015, claims that PARCC tests predict college readiness better than MCAS tests did. A second, to be completed by the Fordham Institute and a partner, is to be issued in time for BESE's vote. A third, issued in mid-October 2015 by Mathematica Policy Research (and requested by the state's Executive Office of Education) claims both tests are equally predictive of college readiness, although its report has major shortcomings. This White Paper will be a fourth external report on the question BESE's vote will address; it is motivated by our interest in providing an analysis of how MCAS and PARCC assess reading and writing. Much less national attention has been paid to Common Core-based assessments of reading and writing than of mathematics, yet reading and writing skills are just as important to readiness for college and career as is mathematics. This White Paper's central recommendation is that Massachusetts use a testing system for K-12 that is much less costly, more rigorous academically, and much more informative about individual student performance, and with much less instructional time spent on test preparation and administration, than the current PARCC tests. Both the PARCC tests and the current MCAS tests in grade 10 are weak, albeit for different reasons, and neither indicates eligibility for a high school diploma, college readiness, or career readiness. In essence, the authors recommend that BESE reject the PARCC assessment system and vote for the MCAS system but on the condition that the responsibility for developing and administering K-12 standards and tests be assigned to an organization in Massachusetts independent of DESE and the state's education schools. This organization must focus squarely on providing the best possible content standards from disciplinary experts in the arts, sciences, and engineering throughout the state and be capable of providing oversight of high school standards and tests. If carried out, these recommendations would ensure the legacy and future promise of MERA. The following are appended: (1) Critique of Criteria for Evaluating Common Core-Aligned Assessments, (2) Links to Public Hearings and Other Sources of Public Comment on MCAS or PARCC, and (3) A Randomly-Chosen Test Item Used on the 2014 Grade 10 MCAS Math Test. Also provided are additional recommendations, an about the authors section, and endnotes.

Building from findings showing that undergraduate computer science continues to have the highest attrition rates proportionally for women within postsecondary science, technology, engineering, and mathematics disciplines--a phenomenon that defies basic social equity goals in a high status field--this paper seeks to better understand how student experiences in local higher educational settings can influence persistence decisions, particulary for women. Updating and extending work in computer science, our qualitative analysis interprets this wider problem, first, by applying a field theory of practice to more clearly theorize how varying social realms and positions influence student experiences and feelings of belonging. Second, we use an in-depth comparative case study of two introductory or "gateway" computer science courses in two universities to detail how classroom, departmental, institutional, and extra-institutional characteristics, including instructional practices and popular stereotypes, may shape action for students in specific higher educational contexts. While previous studies have highlighted the significance of broader computer science cultural values, self-efficacy beliefs, and experience with computers to women's attrition, our findings provide a new theoretical lens to conceptualize the complex ways these and other factors connect in students' daily lives--through preening male students or "brogrammers," authentic or collaborative learning experiences, and uncomfortable social interactions due in part to women's underrepresentation. Our findings also point to differences in local interactions and social positions that can begin to mediate these factors, including opportunities in class to ask questions, collaborate, and work on real-world example problems; fuller access to instructors; and departmental and campus infrastructural supports that contribute to a more meaningful sense of belonging in computer science.

This work asks one simple question: "how reliable is the method used by the National Centre for Vocational Education Research (NCVER) to estimate projected rates of VET program completion?" In other words, how well do early projections align with actual completion rates some years later? Completion rates are simple to calculate with a cohort of students who start together in a very short program with a defined end date. The context in vocational education and training (VET) is, however, far more complex. Program lengths vary and may span several years, students commence at different times and many study part-time. Waiting for all students to complete or "drop out" of their training before calculating an actual completion rate gives a reliable answer, but is somewhat impractical. This paper summarises the key findings from a technical review of the validity of the method long used by NCVER in estimating projected completion rates for government-funded VET programs. This analysis required the interrogation of large longitudinal data sets with tens of millions of enrolments over multiple years. The outcomes are revealing because of ever-high interest in completion rates as measures of the efficiency and effectiveness of the VET sector. Key findings include the following: (1) The method long used by NCVER for estimating VET program completion rates using data from the National VET Provider Collection is shown to be reliable and aligns well with actual rates of completion for historical estimates; (2) Given that it takes a number of years for actual rates of completion to stabilise, the method is well suited for inclusion as part of any method of assessing completion rates, where the projected completion rate method is used to estimate rates for the most recent years and actual rates used for prior years; (3) The technical review has also shown that the current predictive method can be improved by defining a program's commencing year as the year it first appears in the National VET Provider Collection rather than using the commencing flag variable; and (4) It is anticipated that the incorporation of unique student identifiers into any preferred methodology, and its extension to total VET activity, can be phased in from the collection of 2017 training activity. "The Current Method for Projecting Rates of Completion: A Working Example" is appended.

Initiatives to increase leadership accountability coupled with efforts to promote data-driven leadership have led to widespread adoption of instruments to assess school leaders. In this paper we present a decision matrix that practitioners and researchers can use to facilitate instrument selection. Our decision matrix focuses on the psychometric properties of the instrument; the model of leadership used to construct the instrument; the feasibility of implementation; and the extent to which feedback lends itself to changes in behavior (actionability). We apply this decision matrix to two of the most prominent leadership feedback instruments, CALL and VAL-ED. We find substantial similarities between the instruments, yet each has unique strengths and drawbacks. We discuss the implications of the comparative strengths and drawbacks of the two instruments and how they might be most effectively deployed to improve leadership practices.

This paper investigates the impact of immigration on the college enrollment of U.S. natives. Many studies have focused on the effect of increased demand for schooling by immigrants on the enrollment of natives. However, changes in immigrant labor supply may also affect native enrollment by changing local market prices. Using U.S. Census data from 1970 to 2000, I find that state-level increases in the number of immigrant college students do not significantly lower the enrollment rates of U.S. natives. On the contrary, state-level increases in the ratio of unskilled immigrant workers to skilled immigrant workers significantly raise native enrollment rates. These findings suggest that the demand for college is sensitive to wage rates and that college slots are flexibly supplied over a decadal time horizon. An appendix presents "Theory: A Model of Immigration and Native College Enrollment."

This study explores the effect of in-person schooling on youth suicide. We document three key findings. First, using data from the National Vital Statistics System from 1990-2019, we document the historical association between teen suicides and the school calendar. We show that suicides among 12-to-18-year-olds are highest during months of the school year and lowest during summer months (June through August) and also establish that areas with schools starting in early August experience increases in teen suicides in August, while areas with schools starting in September don't see youth suicides rise until September. Second, we show that this seasonal pattern dramatically changed in 2020. Teen suicides plummeted in March 2020, when the COVID-19 pandemic began in the U.S. and remained low throughout the summer before rising in Fall 2020 when many K-12 schools returned to in-person instruction. Third, using county-level variation in school reopenings in Fall 2020 and Spring 2021--proxied by anonymized SafeGraph smartphone data on elementary and secondary school foot traffic--we find that returning from online to in-person schooling was associated with a 12-to-18 percent increase teen suicides. This result is robust to controls for seasonal effects and general lockdown effects (proxied by restaurant and bar foot traffic), and survives falsification tests using suicides among young adults ages 19-to-25. Auxiliary analyses using Google Trends queries and the Youth Risk Behavior Survey suggests that bullying victimization may be an important mechanism. [Additional support for this research was provided by the Center for Health Economics & Policy Studies (CHEPS) and the Troesh Family Foundation.]

Student loans are a crucial aspect of financing a college education for millions of Americans, yet we have surprisingly little empirical evidence concerning individuals' unwillingness to borrow money for educational purposes. This study provides the first large-scale quantitative evidence of levels of loan aversion in the United States. Using survey data collected on more than 6,000 individuals, we examine the frequency of loan aversion in three distinct populations. Depending on the measure, between 20 to 40 percent of high school seniors exhibit loan aversion with lower rates among community college students and adults not in college. Women are less likely to express loan averse attitudes than men, and Hispanic respondents are more likely to be loan averse than white respondents.

Significant numbers of people have very low levels of literacy in many OECD countries and, because of this, face significant labour market penalties. Despite this, it remains unclear what teaching strategies are most useful for actually rectifying literacy deficiencies. The subject remains hugely controversial amongst educationalists and has seldom been studied by economists. Research evidence from part of Scotland prompted a national change in the policy guidance given to schools in England in the mid-2000s about how children are taught to read. We conceptualise this as a shock to the education production function that affects the technology of teaching. In particular, there was phasing in of intensive support to some schools across Local Authorities: teachers were trained to use a new phonics approach. We use this staggered introduction of intensive support to estimate the effect of the new "teaching technology" on children's educational attainment. We find there to be effects of the teaching technology ("synthetic phonics") at age 5 and 7. However, by the age of 11, other children have caught up and there are no average effects. There are long-term effects only for those children with a higher initial propensity to struggle with reading. An appendix contains the following tables: (1) Communication, Language and Literacy at Age 5; (2) Local Authorities in Treatment and Control Groups; (3) Heterogeneity in Estimated Treatment Effects by Non-Native Speaker Status and Free School Meals Eligibility--Different Cohorts for the EDRp v Control; (4) Age 11 Results With and Without Imputation; (5) Heterogeneity in Estimated Treatment Effects by Language Type (i.e. Latin Script v Non-Latin Script) and Free School Meals Eligibility; (6) Heterogeneous Effects for Boys and Girls; (7) Heterogeneity by Subject; and (8) Heterogeneity by Subject: Threshold Effects. [Support was provided by the British Academy and the Royal Society in the framework of the Newton International Fellowship.]