Search

Statewide assessments in reading and math are required every year under the Every Student Succeeds Act (ESSA) of 2015, at an annual expense of billions of taxpayer dollars. Analyzing 10 years of school-level results from public schools in two states—Nebraska and Texas—we found that year-to-year correlations of schools’ test scores were exceptionally high, with reading and math correlations regularly above r = 0.9, indicating that little new information is derived from annual testing. Furthermore, while schools experiencing the largest demographic changes had significantly lower year-to-year correlations—highlighting the sensitivity of these scores to changes in underlying student demographics—even these lower correlations remained strong. We argue that the frequency of these tests may therefore be reduced, yielding substantial savings of time and money and no loss of useful information.

Background One way of evaluating immigrants’ labor market outcomes is to assess the extent to which immigrants are able to enter into jobs that are commensurate with their education and experience. An imperfect alignment between workers’ educational qualifications and these required for their current job, or education-job mismatch, has implications for both the broader economy and individual workers. In this study, we investigate the factors associated with education-job mismatches among US workers by immigrant generation. Methods We analyzed the data from the US sample of the Program for the International Assessment of Adult Competencies (PIAAC) 2012/2014. Our analytic sample included 4022 employed (full and part-time) individuals between the ages of 20–65 years. We documented the distribution of education-job mismatches across selected independent variables and estimated the relationship between the individual characteristics of workers such as race, gender, presence of children, location, time in the country and knowledge of English for first-generation immigrant workers, and education-job mismatch using multinomial logistic regressions for the full sample and for the sample of first- and second-generation workers. Results We found that on average, immigrant workers in the US labor market were more likely to hold jobs which required less education that they had (being overmatched for the job), with first-generation workers being overmatched more frequently than second-generation workers. The probability of being overmatched for immigrant workers declines with the length of stay, and workers who are proficient in English are less likely to be overmatched. Our results also suggest that there may be labor market disadvantages to immigrant status that persist beyond the first-generation. Conclusions Previous research demonstrated that over-education depresses wages and lowers workers’ standards of living and their abilities to accumulate wealth. Our findings confirm that this dynamic may be particularly acute for first- and second-generation workers who are finding it difficult to become fully integrated into US labor markets, even though the factors behind the mismatch differs between the two immigrant generations.

Background/Context The Race to the Top federal initiatives and requirements surrounding waivers of No Child Left Behind promoted expanded use of value-added models (VAMs) to evaluate teachers. Even after passage of the Every Student Succeeds Act (ESSA) relaxed these requirements, allowing more flexibility and local control, many states and districts continue to use VAMs in teacher evaluation systems, suggesting that they consider VAMs a valid measure of teacher effectiveness. Scholars in the fields of economics, education, and quantitative methods continue to debate several aspects of VAMs’ validity for this purpose, however. Purpose The purpose of this study was to directly ask the most experienced VAM scholars about validity of VAM use in teacher evaluation based on the aspects of validity described in the Standards for Educational and Psychological Testing and found in a review of high-quality peer-reviewed literature on VAMs. Participants We invited the 115 scholars listed as an author or coauthor of one or more of the 145 articles published on evaluating teachers with VAMs that have been published in prominent peer-reviewed journals between 2002 and implementation of ESSA in 2016. In this article, we analyze data from 36 respondents (12 economists, 13 educators, and 11 methodologists) who rated themselves as “experienced scholars,” “experts,” or “leading experts” on VAMs. Research Design This article reports both quantitative and qualitative analyses of a survey questionnaire completed by experienced VAM scholars. Findings Analyses of 44 Likert-scale items indicate that respondents were generally neutral or mixed toward the use of VAMs in teacher evaluation, though responses from educational researchers were more critical of VAM use than were responses from economists and quantitative methodologists. Qualitative analysis of free response comments suggests that participants oppose exclusive or high-stakes use of VAMs but are more supportive of their use as a component of evaluation systems that use multiple measures. Conclusions These findings suggest that scholars and stakeholders from different disciplines and backgrounds think about VAMs and VAM use differently. We argue that it is important to understand and address stakeholders’ multiple perspectives to find the common ground on which to build consensus.

In this study, we analyzed public school teacher employment data from 2009 to 2015 to understand why teacher attrition is 54% higher in charter schools compared to traditional public schools. We investigated the factors associated with the differences in exit rates of teachers from traditional public and charter schools in Arizona which has a large charter school sector. Our findings suggest that the major factors behind the gap in retention rates between school sectors in Arizona are teachers’ professional characteristics: less experienced teachers and teachers with alternative certification are more likely to exit schools and, in particular, charter schools which also employ a significantly larger share of these teachers. We argue that charter school and school district leadership might consider interventions, mentoring, and support for teachers in the early stages of their career targeted at novice teachers.

This study examines the consequences of two controversial Arizona immigration laws, the Legal Arizona Workers Act and SB 1070, on school enrollment and student achievement trends. In the period after implementation of both policies, Arizona public schools have demonstrated growth in student achievement on standardized tests arguably due to the state education policies. We propose an alternative explanation and show that the observed achievement gains in schools resulted both due to academic improvement and partially because of the attrition of the low achieving students from certain type of schools. Using data from Arizona public schools we find that after the immigration laws were enacted, schools with initially higher shares of Hispanic students lost about 42 more Hispanic students on average and at the same time experienced greater increase in average test scores compared to schools with initially low Hispanic enrollment. We argue that changes in average test scores partially reflected the changes in school demographic composition as a result of the implementation of restrictive immigration policies.

Teacher attrition is one of the driving contributors to the shortage of effective teachers internationally and in the United States. The common factors that spur teachers worldwide to leave the pro...

While states are no longer required to set up teacher evaluation systems based in significant part on student test scores, quite a few continue to use value-added (VAMs) or student growth percentil...

In this study, we explore the potential of data from large-scale assessments to provide insights into how students’ environmental knowledge could address the global challenge of environmental threats to humanity and the transition to sustainable development. We analyze data from the 2015 PISA survey to understand the extent to which 15-year old students in 54 countries are aware of these challenges. We find that students’ science activities, self-efficacy and environmental knowledge are positively associated with their awareness about environmental challenges. Students’ environmental awareness, in turn, is associated with environmental pessimism, or their outlook on the future of environmental issues. Students who are more engaged with environmental science are more aware about environmental issues and feel less optimistic that environmental issues will improve in the future. Such pessimistic attitudes about the future may be a precursor to pro-environmental behavior. Our results provide a cross-national picture of students’ engagement with environmental issues and insight into the potential of large-scale assessment data to inform environmental education policies promoted by individual countries and international organizations.

Preparing, recruiting, and retaining high-quality teachers into the profession has been a concern of policy makers and practitioners for some time. Teacher attrition is problematic and costly for schools and districts. However, relatively few studies have investigated the relationship between preservice teacher quality and teacher attrition. In this study, we analyze data from an apprenticeship-style teacher preparation program to understand the relationship between a measure of preservice teacher quality—student teachers’ observational scores—and their decisions to (a) enter into the profession, and (b) stay in the profession within the first 2 years after graduation. We find that more qualified student teachers are more likely to enter into the profession and stay in the profession, even after controlling for student teachers’ demographic characteristics and their academic achievement.

The 2016 Presidential election and the first months of the Trump administration have propelled immigration to the center of U.S. political debates. We use data from the Programme for International Student Assessment (PISA) 2012 to provide insights into the school experiences of high school–age immigrants and their U.S.-born peers. Our findings indicate that the immigrant–U.S.-born achievement gap is a race and wealth gap, and is also mediated by school factors. We also found that a substantial number of U.S.-born students attended schools that did not enroll immigrant students. We conclude by highlighting the research and policy implications of our findings.

This article presents data from 1,751 survey responses on how adults remember their share of very good teachers in K-12 education and their characteristics. Participants remembered most of their teachers as good or very good and typically just over 15 percent as bad or worse. Further, participants remembered their very good teacher as predominantly caring and supportive, with a strong knowledge of the subject content. A factor analysis describes that good teaching was consistently associated with what the learning sciences broadly define as "growth” models and not with the “teaching as delivery” model. These results show that participants’ positive perspectives about educators are consistent with several surveys of public opinion about local public schools, but not public schools nationally. The factor analysis also shows that when respondents reflected on their own learning, their assessment of “what worked” differed from key principles orienting most accountability-based education policies promoted since the 1980s.

Being an expert involves explaining how things are supposed to work, and, perhaps more important, why things might not work as supposed. In this study, researchers surveyed scholars with expertise in value-added models (VAMs) to solicit their opinions about the uses and potential of VAMs for teacher-level accountability purposes (for example, in the areas of teacher evaluation, promotion, tenure, merit pay, and termination). Researchers found that respondents were most concerned about VAMs and their methodological and pragmatic flaws and limitations; their uses, misuses, and sometimes abuses in practice; and their unintended consequences. Education practitioners will benefit from this shared knowledge, intelligence, wisdom, and expertise to develop a deeper understanding of the merits and pitfalls of value-added models.

In this critical review of literature, we summarize the major theoretical frameworks that have been used to study teacher mobility. In total we identified 40 teacher mobility studies that met our inclusion criteria. We conclude that relatively few theoretical frameworks have been used to study teacher mobility and those that have been used are lacking in several key areas. Specifically, none of the current teacher mobility theories are able to adequately account for the many teacher- and school-level factors that likely influence teachers’ professional decisions. Finally, we suggest a theoretical framework from the organizational psychology literature that can address the shortcomings of theories identified in this review.

Value-added models (VAMs) are being used in education to link the contribution of individual teachers and schools to students’ learning. The use of VAMs has been surrounded by controversy and high-...

The extensive coverage of household surveys in conflict regions in recent decades has fueled a growing literature on the microeconomic effects of war. In this paper, we use a unique panel dataset to quantify the impact of the Nepalese civil conflict on schooling attainment. Given longitudinal data, we are able to directly estimate unobserved individual heterogeneity and thus address selective wartime displacement. Despite the widely-held view that war is detrimental to human capital formation, we find no effect of war intensity on schooling attainment once unobserved individual heterogeneity is accounted for. We draw on supplementary data to explain our findings.

The extensive coverage of household surveys in conflict regions in recent decades has fueled a growing literature on the microeconomic effects of war. Most researchers identify these effects using econometric methods, with difference-indifferences – which exploits variation across birth cohorts and war intensity – being the most popular. This paper highlights problems of endogenous war intensity and selfselection due to non-random displacement when using common empirical methods on cross-sectional data, and explains how they can be overcome with panel data. We draw on a unique set of cross-sectional and panel data from Nepal to demonstrate our proposition. Both unobserved locality factors and individual heterogeneity lead to huge swings in the estimates of war intensity effects. Our results imply that researchers ought to think carefully about empirical methods and explain possible statistical biases, especially when their results are used to inform policy decisions. For researchers who use panel data, we propose augmentations to existing methods.