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|NCES 2023015||Middle Grades Longitudinal Study of 2017–18 (MGLS:2017) Assessment Item Level File (ILF), Read Me
This ReadMe provides guidance and documentation for users of the Middle Grades Longitudinal Study of 2017-18 (MGLS:2017) Assessment Item Level File (ILF)(NCES 2023-014) made available to researchers under a restricted use only license. Other supporting documentation includes MGLS_Math_and_Reading_Items_User_Guide.xlsx, MGLS_MS1_Math_Item_Images.pdf, MGLS_MS2_Math_Item_Images.pdf, MGLS_MS1_MS2_Reading_Sample_Item_Type_Images.pdf, MGLS_MS1_MS2_EF_HeartsFlowers_Instructions.pptx, and MGLS_MS2_EF_Spatial_2-back_Instructions.pptx
|NCES 2023014||MGLS 2017 Assessment Item Level Files (ILF)
The Middle Grades Longitudinal Study of 2017-18 (MGLS:2017) measured student achievement in mathematics and reading along with executive function. The MGLS:2017 ILF contains the item level data from these direct measures that can be used in psychometric research for replicating or enhancing the scoring found in the MGLS:2017 RUF or in creating new scores. The Middle Grades Longitudinal Study of 2017–18 (MGLS:2017) Assessment Item Level File (ILF) contains two .csv files representing the two rounds of data collection: the MGLS:2017 Main Study (MS) Base Year (MS1) and the Main Study Follow-up (MS2) files.
|NCES 2023131||MGLS:2017 Restricted Access Use Data Files (RUF)
MGLS data offers information on the characteristics and cognitive outcomes of students who were enrolled in the 6th grade in public schools in the 2017-2018 school year and two years later in spring of 2020 when most students were in the 8th grade. The MGLS data are organized into student and school folders, each containing .txt data, data input files for SAS, SPSS, Stata and R survey software packages. A .csv version of the data is also provided.
|NCES 2023055||Overview of the Middle Grades Longitudinal Study of 2017–18 (MGLS:2017): Technical Report
This technical report provides general information about the study and the data files and technical documentation that are available. Information was collected from students, their parents or guardians, their teachers, and their school administrators. The data collection included direct and indirect assessments of middle grades students’ mathematics, reading, and executive function, as well as indirect assessments of socioemotional development in 2018 and again in 2020. MGLS:2017 field staff provided additional information about the school environment through an observational checklist.
|NCES 2021029||2012–2016 Program for International Student Assessment Young Adult Follow-up Study (PISA YAFS): How reading and mathematics performance at age 15 relate to literacy and numeracy skills and education, workforce, and life outcomes at age 19
This Research and Development report provides data on the literacy and numeracy performance of U.S. young adults at age 19, as well as examines the relationship between that performance and their earlier reading and mathematics proficiency in PISA 2012 at age 15. It also explores how other aspects of their lives at age 19—such as their engagement in postsecondary education, participation in the workforce, attitudes, and vocational interests—are related to their proficiency at age 15.
|NFES 2020132||Forum Guide to Exit Codes
The Forum Guide to Exit Codes provides best practice information for tracking data about when students transferred, completed high school, dropped out, or otherwise exited an education agency. This resource defines exit codes and reviews their use in an education agency; provides an updated, voluntary, common taxonomy for exit codes; discusses best practices and methods for addressing specific challenges in exit codes data collection; features case studies that highlight different education agencies’ approaches to and experiences with exit coding.
|REL 2020026||Relationships between Schoolwide Instructional Observation Scores and Student Academic Achievement and Growth in Low‑Performing Schools in Massachusetts
The Massachusetts Department of Elementary and Secondary Education (DESE), like other state education agencies and districts, recognizes that a key lever to turning around low-performing schools is the quality of instruction (Hill & Harvey, 2004; Hopkins, Harris, Watling, & Beresford, 1999). As part of the annual monitoring of state-designated low-performing schools, DESE’s external low-performing school monitors use Teachstone’s Classroom Assessment Scoring System (CLASS) tool to conduct observations. DESE’ external monitors rated low-performing schools on three domains of instruction—Emotional Support, Classroom Organization, and Instructional Support. This paper examines the relationships between these observation scores and academic growth and achievement within a school, after adjusting for the percentage of students with low incomes and the grade levels in these low-performing schools. Results show statistically significant positive relationships between schoolwide average observation scores for each instructional domain and school-level academic growth in both English language arts (ELA) and mathematics. On a 7-point scale, a 1-point increase in a school’s overall observation rating was associated with an increase in student growth of 4.4 percentile points of growth in ELA and 5.1 percentile points of growth in mathematics. For schoolwide achievement, which is measured by the percentage of students who met or exceeded expectations on the state assessment, results show a significant positive relationship between the classroom organization domain and ELA schoolwide achievement. There was no significant relationship between observation scores and schoolwide achievement in ELA for any other domain or for mathematics schoolwide achievement. The relationship between observation scores and current achievement levels may be weak because achievement levels may be influenced by many other factors including students’ prior achievement and the economic and social challenges their families face.
|NCES 2019084||Technology and K-12 Education: The NCES Ed Tech Equity Initiative
This interactive brochure provides an overview of the Initiative—including its purpose, goal, and target outcomes.
|NCES 2019086||Technology and K-12 Education: The NCES Ed Tech Equity Initiative: Framework
Check out our new factsheet to learn about the factors most critical to informing ed tech equity in the context of K-12 education!
|NCES 2019087||Technology and K-12 Education: The NCES Ed Tech Equity Initiative: Data Collection Priorities
This factsheet outlines the key subtopics NCES will prioritize in its ed tech equity data collections.
|NCES 2019031||Findings and Recommendations from the National Assessment of Educational Progress (NAEP) 2017 Pilot Study of the Middle School Transcript Study (MSTS): Methodological Report, NCES 2019-031
This report summarizes the methodological findings of a pilot study that was designed to test the feasibility of collecting eighth-grade student transcript and course catalog data via electronic submissions.
The transcript data of eighth-grade students from Trial Urban District Assessments (TUDA) schools that participated in the NAEP 2017 eighth-grade mathematics and reading assessments were collected.
|NCES 2018158||NAEP 2015 NIES Restricted-Use Data Files (Y46NIES)
This CD-ROM contains data and documentation files for the NAEP 2015 National Indian Education Study (NIES) for use in the analysis of NAEP data by secondary researchers. NIES, which was administered as part of NAEP, is a two-part study designed to describe the condition of education for American Indian and Alaska Native (AI/AN) students in the United States. The data files include NAEP mathematics and reading assessment data from the samples of American Indian/Alaska Native (AI/AN) students at grades 4 and 8 who participated in the National Assessment of Educational Progress (NAEP) 2015 mathematics or reading assessments, as well as NIES survey response data of sampled AI/AN students in grades 4 and 8, their teachers, and their school principals. A Data Companion is provided in electronic portable document format (PDF). This document contains information on the contents and use of the data files as well as the assessment design and its implications for analysis. NAEP datasets from 2002 onward require a Tool Kit with the updated NAEPEX. Your organization must apply for and be granted a restricted-use data license in order to obtain these data.
|NCES 2017249||Collaborative Problem Solving Skills of 15-Year-Olds: Results From PISA 2015
The focus of this Data Point is on the performance of students in the United States relative to their peers in 50 other education systems that participated in the PISA collaborative problem solving assessment in 2015. The PISA assessment of collaborative problem solving measured students’ ability to solve a problem by sharing the understanding and effort required to come to a solution, and pooling their knowledge, skills, and effort to reach that solution. Readers interested in more detailed data related to collaborative problem solving should also visit the NCES PISA website for data tables and figures. Please visit https://nces.ed.gov/surveys/pisa/pisa2015/index.asp to learn more.
|WWC SSR82160||The impact of computer usage on academic performance: Evidence from a randomized trial at the United States Military Academy
The 2016 study, "The Impact of Computer Usage on Academic Performance: Evidence from a Randomized Trial at the United States Military Academy," examined the impacts of computer usage on the academic performance of college students. The study found that students who were permitted to use Internet-enabled devices in class scored lower on final exams than those in classes that prohibited the use of such devices. The impact estimate for the combined multiple choice and short answer portion of the final exam meets WWC group design standards without reservations. The impact estimate for the essay question portion of the final exam does not meet WWC group design standards because essays were only graded once and therefore, the authors were unable to report a measure of reliability for these scores.
|REL 2017212||How are middle school climate and academic performance related across schools and over time?
The purpose of this study was to examine the relationship between school climate and academic performance in two different ways: (1) by comparing the academic performance of different schools with different levels of school climate and (2) by examining how changes in a school's climate were associated with changes in its students' academic achievement. To examine how school climate and academic performance are related, this study analyzed grade 7 student data from 2004/05 to 2010/11 from the California Healthy Kids Survey, the California Standardized Testing and Reporting program, and the California Basic Educational Data System for 978 middle schools in California. School climate was measured by a set of student survey questions that assessed students' perceptions about six domains of school climate. Schools with positive school climates were those in which students reported high levels of safety/connectedness, caring relationships with adults, and meaningful student participation, as well as low levels of substance use at school, bullying/discrimination, and student delinquency. Regression models were used to estimate the relationship between student-reported school climate and students' average academic performance across schools. Regression models were also used to estimate how, for a given school, academic performance changes as school climate changes. All models included controls for racial/ethnic composition, percentage of English learners, and percentage of students eligible for free/reduced-price meals. The study found that (1) middle schools with higher levels of positive student-reported school climate exhibited higher levels of academic performance; (2) increases in a school's level of positive student-reported school climate were associated with simultaneous increases in that school's academic achievement; and (3) within-school increases in academic achievement associated with school climate increases were substantially smaller than the academic performance differences across schools with different school climate levels. As positive school climate is continuing to gain more attention as a lever to improve student learning, there is increasing interest in how improvements in school climate are related to improvements in academic performance. Most studies examining the school climate-academic performance relationship compare the academic achievement across schools with different levels of school climate. Although the results of this study found that schools with high levels of positive school climate exhibited substantially higher levels of academic performance than their counterparts with low levels of positive school climate, such differences across schools were not an accurate guide for predicting the magnitude of school-specific gains in academic performance associated with increases in school climate.
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