Search Results: (1-15 of 56 records)
|NFES 2022132||Using Education Indicators: A Forum Guide for State and Local Education Agencies
This guide was developed to provide timely and useful information on education indicators, how their collection and use have changed over time, and how agencies use them strategically. Since the publication of the 2005 document Forum Guide to Education Indicators (https://nces.ed.gov/forum/pub_2005802.asp), many advancements in education have impacted indicators, including changes to data systems (such as improved longitudinal data systems), federal data collections and accountability systems, legislation, mandatory public reporting, privacy protections, and data security. This new guide highlights best practices for using indicators, adjustments over time to the collection and use of indicators, shifts in types of relevant indicators, and what possibilities local and state education agencies see for the effective use of indicators in the future.
|NCES 2022049||U.S. Technical Report and User Guide for the 2019 Trends in International Mathematics and Science Study (TIMSS)
The U.S. TIMSS 2019 Technical Report and User’s Guide provides an overview of the design and implementation of TIMSS 2019 in the United States and includes guidance for researchers using the U.S. datasets.
This information is meant to supplement the IEA’s TIMSS 2019 Technical Report and TIMSS 2019 User Guide by describing those aspects of TIMSS 2019 that are unique to the United States including information on merging the U.S. public- and restricted-use student, teacher, and school data files with the U.S. data files in the international database.
|NCEE 2022004||Sharing Study Data: A Guide for Education Researchers
Open science envisions that researchers will make their study data available to other investigators to facilitate research transparency and accelerate the development of knowledge. This guide describes key issues that education researchers should consider when deciding which study data to share, how to organize the data, what documentation to include, and where to share their final dataset. The guide also provides strategies for addressing related challenges and includes links to other resources, a checklist aligned to each section, and appendices that contain templates and samples.
|NCES 2021030REV||National Household Education Surveys Program of 2019 Data File User's Manual
The 2019 National Household Education Surveys Program (NHES:2019) Data File User’s Manual provides documentation and guidance for users of the NHES:2019 data files, which include data from the Early Childhood Program Participation survey and the Parent and Family Involvement in Education survey. The survey program collected information about early childhood care, parental involvement in education, school choice, homeschooling, online learning, and home learning activities. Data files are being released for each survey, with ASCII, SAS, SPSS, Stata, csv, and R formats available.
|NFES 2021110||Forum Guide to Metadata
The Forum Guide to Metadata presents and examines the ways in which metadata can be used by education agencies to improve data quality and promote a better understanding of education data. Supported by metadata-related case studies from state and local education agencies, the guide highlights the uses of metadata from a technical point of view, as well as the perspectives of data management, data reporting and use, and data privacy and security. The guide further discusses how to plan and successfully implement a metadata system in an education setting and provides examples of standard metadata items and definitions to assist agencies with standardization.
|REL 2021104||Using High School and College Data to Predict Teacher Candidates' Performance on the Praxis at Unibetsedåt Guåhan (University of Guam)
Policymakers and educators on Guåhan (Guam) are concerned about the persistent shortage of qualified K-12 teachers. Staff at the Unibetsedåt Guåhan (University of Guam, UOG) School of Education, the only local university that offers a teacher training and certification program, believe that more students are interested in becoming teachers but that the program's admissions requirements--in particular, the Praxis® Core test, which consists of reading, writing, and math subtests--might be a barrier. Little is known about the predictors for passing the Praxis Core test. This makes it difficult to develop and implement targeted interventions to help students pass the test and prepare for the program.
This study examined which student demographic and academic preparation characteristics predict passing the Praxis Core test and each of its subtests. The study examined two groups of students who attempted at least one subtest within three years of enrolling at UOG: students who graduated from a Guåhan public high school (group 1) and all students, regardless of the high school from which they graduated (group 2). Just over half the students in each group passed the Praxis Core test (passed all three subtests) within three years of enrolling at UOG. The pass rate was lower on the math subtest than on the reading and writing subtests. For group 1, students who earned credit for at least one semester of Advanced Placement or honors math courses in high school had a higher pass rate on the Praxis Core test than students who did not earn any credit for those courses, students who earned a grade of 92 percent or higher in grade 10 English had a higher pass rate on the reading subtest than students who earned a lower grade, and students who earned a grade higher than 103 percent in grade 10 English had a higher pass rate on the writing subtest than students who earned a lower grade. For group 2, students who did not receive a Pell Grant (a proxy for socioeconomic status) had a higher Praxis Core test pass rate than students who did receive a Pell Grant, students who earned a grade of B or higher in first-year college English had a higher Praxis Core test pass rate than students who earned a lower grade, and male students had a higher pass rate on the reading and math subtests than female students.
The study findings have several implications for intervention plans at both the secondary and postsecondary levels. Although students must pass all three Praxis subtests to be admitted to the teacher preparation program at the School of Education, examining student performance on each subtest can help stakeholders understand the content areas in which students might need more support. In the long term preparing more prospective teachers for the Praxis Core test might increase program enrollment, which in turn might increase the on-island hiring pool.
|NCES 2021047||Program for the International Student Assessment (PISA) 2018 Restricted-Use Files (RUF)
The PISA 2018 Restricted Use File (RUF) consists of restricted-use data from PISA 2018 for the United States. The data file and documentation includes the data file, a codebook, instructions on how to merge with the U.S. PISA 2018 public-use dataset (NCES 2021-047), and a cross-walk to assist in merging with other public datasets, such as the Common Core of Data (CCD) and Private School Survey (PSS). As these data files can be used to identify respondent schools, a restricted-use license must be obtained before access to the data is granted. Click on the restricted-use license link below for more details https://nces.ed.gov/surveys/pisa/datafiles.asp.
For more details on the data, please refer to chapter 9 of the PISA 2018 Technical Report and User Guide (NCES 2021-011).
|NCES 2021019||Program for the International Student Assessment (PISA) 2018 Public Use File (PUF)
The PISA 2018 Public Use File (PUF) consists of data from the PISA 2018 sample. Statistical confidentiality treatments were applied due to confidentiality concerns. The PUF can be accessed from the National Center for Education Statistics website at http://nces.ed.gov/surveys/pisa/datafiles.asp.
For more details on the data, please refer to chapter 9 of the PISA 2018 Technical Report and User Guide (NCES 2021-011).
|NCES 2021020||Technical Report and User Guide for the 2016 Program for International Student Assessment (PISA) Young Adult Follow-up Study
This technical report and user guide is designed to provide researchers with an overview of the design and implementation of PISA YAFS 2016, as well as with information on how to access the PISA YAFS 2016 data.
|NCES 2021022||Program for the International Student Assessment Young Adult Follow-up Study (PISA YAFS) 2016 Public Use File (PUF)
The PISA YAFS 2016 Public Use File (PUF) consists of data from the PISA YAFS 2016 sample. PISA YAFS was conducted in the United States in 2016 with a sample of young adults (at age 19) who participated in PISA 2012 when they were in high school (at age 15). In PISA YAFS, students took the Education and Skills Online (ESO) literacy and numeracy assessments, which are based on the Program for the International Assessment of Adult Competencies (PIAAC). It contains data for individuals including responses to the background questionnaire and the cognitive assessment. Statistical confidentiality treatments were applied due to confidentiality concerns.
For more details on the data, please refer to chapter 8 of the PISA YAFS 2016 Technical Report and User Guide (NCES 2021-020).
|NCES 2021524||2012 Beginning Postsecondary Students Longitudinal Study (BPS:12) Student Records Collection Data File Documentation: Research Data File Documentation
This publication describes the methodology used in the 2012 Beginning Postsecondary Students Longitudinal Study (BPS:12) Student Records Collection research datafile, a release of exploratory administrative data that are made available only for research on institution response and imputation methodologies. As a result of low institutional response rates, population estimates are NOT advised. Specifically, these data should NOT be used to generate population estimates or analyze the postsecondary records of this BPS cohort. This release includes student-level data for a nationally representative sample of over 35,000 first-time beginning postsecondary students who began postsecondary education during the 2011-12 academic year. Efforts, albeit unsuccessful, were made to collect student level data on enrollment, student budget, and financial aid from postsecondary education institutions attended between the 2011–12 and 2016–17 academic years.
|REL 2021073||Using High School Data to Predict College Readiness and Early College Success on Guåhan (Guam)
On Guåhan (Guam), the large percentages of students enrolling in non-credit-bearing courses at Kulehon Kumunidåt Guåhan (Guam Community College) and Unibetsedåt Guåhan (University of Guam) have raised concerns about college readiness and early college success. Without adequate research on predictors of college readiness and early success among students on Guåhan, educators and other stakeholders find it difficult to identify and support students at risk of being underprepared for college. This study examined which student characteristics predicted college readiness and early college success among students who graduated from Guåhan high schools and enrolled at Kulehon Kumunidåt Guåhan or Unibetsedåt Guåhan between 2012 and 2015. Students' college readiness and early college success were assessed using three indicators: enrolling in only credit-bearing math and English courses during the first year of college, earning all credits attempted during the first semester of college, and persisting to a second year of college. About 23 percent of students met all three indicators and were thus classified as demonstrating college readiness and early college success. The percentages of students who met each individual indicator varied: 30 percent enrolled in only credit-bearing math and English courses, 43 percent earned all the credits they attempted, and 74 percent persisted to a second year. Various student characteristics predicted meeting all three indicators and each individual indicator. Graduates of John F. Kennedy High School and male students were the most likely to meet all three indicators and were the most likely to enroll in only credit-bearing math and English courses. Completing a high-level math course during high school positively predicted meeting the composite indicator of college readiness and early college success and of enrolling in only credit-bearing math and English courses and earning all credits attempted. A higher cumulative high school grade point average also positively predicted meeting all three indicators and each individual indicator. Kulehon Kumunidåt Guåhan enrollees were more likely than Unibetsedåt Guåhan enrollees to earn all credits attempted during their first semester.
|NFES 2021013|| Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR)
The Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR) was created to provide timely and useful best practices for education agencies that are interested in designing and implementing a strategy for data collection and reporting, focusing on these as key elements of the larger data process. It builds upon the Standards for Education Data Collection and Reporting (published by the Forum in 1991) and reflects the vast increase over the past three decades in the number of compulsory and/or continual data collections conducted by education agencies. This new resource is designed to be relevant to the state and local education agencies (SEAs and LEAs) of today, in which data are regularly collected for multiple purposes, and data collection and recording may be conducted by many different individuals within an agency.
|REL 2021067||Early Childhood Data Use Assessment Tool
The Early Childhood Data Use Assessment Tool is designed to identify and improve data use skills among early childhood education (ECE) program staff so they can better use data to inform, plan, monitor, and make decisions for instruction and program improvement. Data use is critical in quality ECE programs but can be intimidating for some ECE program staff. This tool supports growth in their data use skills. The tool has three components: (1) a checklist to identify staff skills in using child assessment and administrative data, (2) a resource guide to identify professional development resources for improving data use skills, and (3) an action plan template to support planning for the development and achievement of data use goals. Results obtained from using the tool are meant by the developers to support instruction and program improvement through increased and structured use of data.
|REL 2021059||Using High School Data to Predict College Success in Palau
The purpose of this study was to examine the college success of students who graduated from Palau High School between spring 2013 and spring 2015 and who enrolled at Palau Community College the fall semester immediately following their high school graduation. It also examined the relationships between student characteristics and three college success outcomes. The study’s sample included 234 students. The college success outcomes used in the study were first-year college cumulative grade point average, persistence to a second year of college, and earning an associate degree or certificate. Using existing data, researchers calculated descriptive statistics to describe the percentage of students who met each college success outcome. Multiple logistic regression models determined which student demographic and academic preparation characteristics predicted meeting the college success outcomes. The study results show that 60 percent of all students had a first-year college cumulative grade point average of 2.0 or higher, 56 percent persisted to a second year, and 20 percent earned an associate degree or certificate within three years. Having higher high school grade point averages predicted having higher first-year college grade point averages and being more likely to complete a degree or certificate within three years. Additionally, having higher grade 12 Palau Achievement Test scores, a standardized test administered in the Republic of Palau, predicted being more likely to have a higher first-year college grade point average. High school English course grades also predicted some college success outcomes. Specifically, earning a grade C or higher in grade 9 English predicted completing a certificate or degree within three years, and earning a grade of C or higher in grade 12 English predicted persisting to a second year. Finally, students who enrolled in the Palau High School Construction Technology Career Academy were less likely than students in other career academies to persist to a second year or complete a degree or certificate within three years. These findings suggest that most students achieved the early college success outcomes of earning a first-year college grade point average of 2.0 or higher and persisting to a second year, but that this did not always translate to graduating with a college degree or certificate within three years. Providing additional supports for students in college based on their high school performance, examining supports available for English learners at Palau High school, and reviewing the alignment of the Palau High School Construction Technology Career Academy and the needs of students who plan to attend college could help inform efforts to support the college success of students in Palau. Palau Community College may also want to conduct future studies to examine additional factors at the college, such as the effects of course sequencing or academic counseling services, to improve college success.