Search

The research featured in this paper is part of the CORE-PACE Research Partnership, which is focused on producing research that informs continuous improvement in the CORE districts as well as policy and practice in California and beyond. In this report, the authors used data from multiple interim assessments to examine how the rate of student learning from fall 2019 through winter 2020-21 differs from that of student learning before COVID-19. Specifically, the authors assessed the degree to which approximately 100,000 students across 19 local education agencies (LEAs) in California experienced slower academic growth compared to previous school years (i.e., a learning lag) by the time they completed winter 2021 interim assessments (NWEA MAP Growth, Renaissance Learning Star, and Curriculum Associates i-Ready) in Grades 4-8. To understand equity gaps in the degree to which students have experienced lost instructional opportunities, the authors disaggregated these results for students who were economically disadvantaged, students who were English learners, students with disabilities, students of different racial/ethnic backgrounds, students with low prior achievement, and students who were experiencing homelessness. The results show that by the time students completed winter interim assessments in the 2020-21 school year, they had experienced a learning lag of approximately 2.6 months in English language arts (ELA) and 2.5 months in math. It was further found that students who were economically disadvantaged, English learners, and Latinx experienced greater learning lag than students who were not in these groups. The authors position these findings in the context of other recent studies that have estimated COVID-19 impacts on student learning, discuss caveats of using interim assessments (including those administered remotely), and highlight the importance of examining differences in the effects for students in different groups. These findings can be useful for guiding decision-making and resource allocation at the state and local levels.

The research featured in this paper is part of the CORE-PACE Research Partnership, which is focused on producing research that informs continuous improvement in the CORE districts as well as policy and practice in California and beyond. Since spring 2020, the COVID-19 pandemic has been abruptly interrupting regular instruction in almost all schools in the U.S. One year later, policymakers, district administrators, and educators are still balancing the benefits and risks of returning K-12 students to fully in-person school. Many are concerned about the pandemic's disruption to students' academic progress. In California, educators have been focused equally on students' mental and emotional health, social relationships, and learning environment, given that many students have been learning remotely since the onset of the pandemic. Anticipating the need for schools and districts to understand their students' social-emotional well-being, the CORE Districts in California developed survey instruments to collect such information in the 2020-21 school year. The surveys were administered remotely, as all participating districts offered distance-only instruction. This report draws on data from the "Student well-being and learning conditions diagnostic survey" taken by 32,000 students in Grades 4-12 from three districts at the beginning of the 2020-21 school year. The results from 15,000 students who also responded to the "Comprehensive interim survey" a few months later are also highlighted. This report brings data to bear on the areas of student well-being that are most relevant at each developmental stage, so that all education stakeholders are able to focus their efforts on meeting the most pressing needs of each group of students.

Spin-lattice dynamics is used to study the magnetic properties of Fe foams. The temperature dependence of the magnetization in foams is determined as a function of the fraction of surface atoms in foams, nsurf. The Curie temperature of foams decreases approximately linearly with nsurf, while the critical exponent of the magnetization increases considerably more strongly. If the data are plotted as a function of the fraction of surface atoms, reasonable agreement with recent data on vacancy-filled Fe crystals and novel data on void-filled crystals is observed for the critical . Critical temperature and critical exponent also depend on the coordination of surface atoms. Although the decrease we find is relatively small, it hints to the possibility of improved usage of topology to taylor magnetic properties., Comment: 8 pages, 6 figures, submitted to Computational Materials Science

We propose a moving-boundary scenario to model the penetration of diffusants into dense and foamed rubbers. The presented modelling approach recovers experimental findings related to the diffusion of cyclohexane and the resulting swelling in a piece of material made of ethylene propylene diene monomer rubber (EPDM). The main challenge is to find out relatively simple model components which can mimic the mechanical behavior of the rubber. Such special structure is identified here so that the computed penetration depths of the diffusant concentration are within the range of experimental measurements. We investigate two cases: a dense rubber and a rubber foam, both made of the same matrix material. After a brief discussion of scaling arguments, we present a finite element approximation of the moving boundary problem. To overcome numerical difficulties due to the \textit{a priori} unknown motion of the diffusants penetration front, we transform the governing model equations from the physical domain with moving unknown boundary to a fixed fictitious domain. We then solve the transformed equations by the finite element method and explore the robustness of our approximations with respect to relevant model parameters. Finally, we discuss numerical estimations of the expected large-time behavior of the material., Comment: 19 pages, 16 figures, 7 tables

This brief applies value-added models to student surveys in the CORE Districts to explore whether social-emotional learning (SEL) surveys can be used to measure effective classroom-level supports for SEL. The authors find that classrooms differ in their effect on students' growth in self-reported SEL--even after accounting for school-level effects. Results suggest that classroom-level effects within schools may be larger than school-level effects. However, the low explanatory power of the SEL models means it is unclear that these are causal effects that have appropriately controlled for student-level characteristics. Finally, there are generally low correlations between classroom-level growth in SEL and classroom-level growth in English language arts (ELA) or math, suggesting the SEL measures may capture growth not measured by academic test scores. Although results are preliminary, they indicate there might be measurable student growth in SEL impacted by the environment of classrooms within schools. [For the full working paper, see "Can We Measure Classroom Supports for Social-Emotional Learning? Applying Value-Added Models to Student Surveys in the CORE Districts. Working Paper" (ED600451).]

We illustrate the application of mixture IRT [item response theory] models to evaluate the possibility of respondent confusion due to the negative wording of certain items on a social-emotional learning (SEL) assessment. Using actual student self-report ratings on four social-emotional learning scales collected from students in grades 3-12 from CORE districts in the state of California, we also evaluate the consequences of the potential confusion in biasing student- and school-level scores as well as correlational relationships between SEL and student-level variables. Models of both full and partial confusion are examined. Our results suggest that (1) rating scale confusion due to negatively-worded items does appear to be present; (2) the confusion is most prevalent at lower grade levels (3rd-5th); and (3) the occurrence of confusion is positively related to reading proficiency and ELL status, as anticipated, and bias estimates of SEL correlations with these student-level variables. For these reasons, we suggest future iterations of the SEL measures use only positively oriented items. To maintain measurement continuity, we suggest bias corrections based on the studied mixture model may be useful, although the precision of such corrections is sensitive to the nature of confusion (e.g., full versus partial).

The 13 appendices in this publication accompany the full report, "Teacher Preparation Experiences and Early Teaching Effectiveness. NCEE 2019-4007" (ED598664). They include: (1) Teacher Survey Response Rates by District/State; (2) Comparison of the Subsample Used for Relational Analyses and the Full Sample; (3) Development of the Teacher Survey; (4) Teacher Survey Questions on Preparation Experiences; (5) Measures of Preparation Experiences; (6) Teachers' Assessment of the Usefulness of Preparation Experiences; (7) Factor Analysis Methodology; (8) Assessing Measurement Error in Teacher Survey Responses; (9) Value-Added Modeling Methodology; (10) Teachers' Preparation Experiences by Preparation Provider and Degree Program; (11) Robustness of Results to Alternative Statistical Models; (12) Subgroup Analyses of Relational Findings; and (13) Relationships between Preparation Experiences and Effectiveness by Year of Teaching.

This executive summary describes the larger study, "Teacher Preparation Experiences and Early Teaching Effectiveness. NCEE 2019-4007" (ED598664). This study provides information about new teachers' preparation experiences and explores whether particular types of experiences are related to teachers' effectiveness in improving their students' test scores. Understanding whether certain ways of preparing teachers are more effective than others is important, but very little is currently known about what teacher preparation emphasizes at a fine-grained level and how those experiences are related to teaching effectiveness. Research identifying which preparation experiences are related to improved student performance can generate hypotheses for improving teacher preparation. Through an online survey administered in spring 2015, this study collected information from new teachers about their preparation experiences. It also examined the relationship between the frequency of these experiences and teachers' effectiveness in improving student test scores. The summary describes how the study was conducted, key findings, and concluding thoughts.

This report examines the frequency of particular teacher preparation experiences and explores their relationships to beginning teachers' effectiveness in improving student test scores once they get to the classroom. The report found both differences in how teachers prepare for their certification in the field and that certain experiences are related to improving test scores in the classroom. The findings provide a detailed look into current teacher preparation practices and identify potential avenues for improving them. [For the appendices, see ED598665. For the executive summary, see ED598666. For the study highlights, see ED598667.]

School value-added models are increasingly used to measure schools' contributions to student success. At the same time, policymakers and researchers agree that schools should support students' socialemotional learning (SEL) as well as academic development. Yet, the evidence regarding whether schools can influence SEL and whether statistical growth models can appropriately measure this influence is limited. Recent work shows meaningful differences across schools in changes in SEL scores by grade (Loeb, Christian, Hough, Meyer, Rice, & West, 2019), but whether these differences represent the effects of schools is still unclear. The current paper builds upon this earlier work by examining the stability of the estimated school-by-grade effects on SEL across two years, using a large-scale SEL survey administered in California's CORE districts. We find that correlations among school effects in the same grades across different years are positive, but they are lower than those for math and English Language Arts (ELA). Schools in the top or the bottom of the school effect distribution are more persistent in their impacts across years than those in the middle of the distribution. Overall, the results provide evidence that these school effects measure real contributions to SEL. However, the low stability of effects from one year to the next draw into question whether including these school value-added measures of self-reported SEL in school performance frameworks and systems would be beneficial.