Yearly data of Quality Review ratings from 2005 to 2017

2018 DC School Report Card. STAR Framework student group scores by school and school framework. The STAR Framework measures performance for 10 different student groups with a minimum n size of 10 or more students at the school. The student groups are All Students, Students with Disabilities, Student who are At Risk, English Learners, and students who identify as the following ESSA-defined racial/ethnic groups: American Indian or Alaskan Native, Asian, Black or African American, Hispanic/Latino of any race, Native Hawaiian or Other Pacific Islander, White, and Two or more races. The Alternative School Framework includes an eleventh student group, At-Risk Students with Disabilities.Some students are included in the school- and LEA-level aggregations that will display on the DC School Report Card but are not included in calculations for the STAR Framework. These students are included in the “All Report Card Students” student group to distinguish from the “All Students” group used for the STAR Framework.Supplemental:Metric scores are not reported for n-sizes less than 10; metrics that have an n-size less than 10 are not included in calculation of STAR scores and ratings.At the state level, teacher data is reported on the DC School Report Card for all schools, high-poverty schools, and low-poverty schools. The definition for high-poverty and low-poverty schools is included in DC's ESSA State Plan. At the school level, teacher data is reported for the entire school, and at the LEA-level, teacher data is reported for all schools only.On the STAR Framework, 203 schools received STAR scores and ratings based on data from the 2017-18 school year. Of those 203 schools, 2 schools closed after the completion of the 2017-18 school year (Excel Academy PCS and Washington Mathematics Science Technology PCHS). Because those two schools closed, they do not receive a School Report Card and report card metrics were not calculated for those schools.Schools with non-traditional grade configurations may be assigned multiple school frameworks as part of the STAR Framework. For example, a K-8 school would be assigned the Elementary School Framework and the Middle School Framework. Because a school may have multiple school frameworks, the total number of school framework scores across the city will be greater than the total number of schools that received a STAR score and rating.Detailed information about the metrics and calculations for the DC School Report Card and STAR Framework can be found in the 2018 DC School Report Card and STAR Framework Technical Guide (https://osse.dc.gov/publication/2018-dc-school-report-card-and-star-framework-technical-guide).

xls. file with of all variables analyzed in the study: gender, groups, socio-economic background, engagement scale, school climate scale, items of Big Five Inventory questionnaire and items Comprehensive Inventory of Thriving.

Progress Reports grade each school with an A, B, C, D, or F. These reports focus on a school's learning environment, student performance, and student progress. They were designed to help parents, teachers, principals, and others understand how well schools are doing—and compare them to other, similar schools.

This dataset contains quantitative student data acquired during the administration of two validated Computational Thinking (CT) assessments for upper primary school (grades 3 and 4): the Beginners' CT test (BCTt) [1] and the comptent CT test (cCTt) [2]

To compare the psychometric properties of both instruments a comparative analysis was conducted with data acquired in schools in Portugal from the same school districts. More specifically, we analyse the results of:

• the BCTt test administered in March 2020 to 374 students in grades 3-4,

• the cCTt test administered in April 2021 to 201 different students in grades 3-4.

These students had no prior experience in Computational Thinking, as this was not part of the national curriculum at the times of administration.

The detailed psychometric comparison is published in Frontiers in Psychology - Educational Psychology [3] and provides indications regarding the use of both instruments for grades 3-4.

A README is included and provides additional information regarding :

• the requirements for re-use.

• the specific content of the 2 csv files

The BCTt is available upon request to maria.zapata@urjc.es and the cCTt items are available in [2] with an editable version being available upon request to laila.elhamamsy@epfl.ch.

In case of other inquiries, please contact: laila.elhamamsy@epfl.ch, maria.zapata@urjc.es or pedro.marcelino@treetree2.org

References

[1] M. Zapata-Cáceres, E. Martín-Barroso and M. Román-González, "Computational Thinking Test for Beginners: Design and Content Validation," 2020 IEEE Global Engineering Education Conference (EDUCON), 2020, pp. 1905-1914, doi: 10.1109/EDUCON45650.2020.9125368.

[2] El-Hamamsy, L., Zapata-Cáceres, M., Barroso, E. M., Mondada, F., Zufferey, J. D., & Bruno, B. (2022). The Competent Computational Thinking Test: Development and Validation of an Unplugged Computational Thinking Test for Upper Primary School. Journal of Educational Computing Research, 60(7), 1818–1866. https://doi.org/10.1177/07356331221081753

[3] Laila El-Hamamsy* , María Zapata-Cáceres, Pedro Marcelino, Jessica Dehler Zufferey, Barbara Bruno, Estefanía Martín-Barroso and Marcos Román-González (2022). Comparing the psychometric properties of two primary school Computational Thinking (CT) assessments for grades 3 and 4: the Beginners' CT test (BCTt) and the competent CT test (cCTt). Front. Psychol. doi:10.3389/fpsyg.2022.1082659

This table gives an overview of expenditure on regular education within the Netherlands. The government finances schools, colleges and universities. It pays for research which is done by universities on its behalf. Furthermore it provides student grants and loans, allowances for school costs, provisions for students with a disability and child care allowances as well as subsidies to companies and non-profit organisations. The government reclaims unjustified payments for student grants and loans and allowances for school costs. It also receives interest and repayments on student loans as well as EU subsidies for education. Parents and/or students have to pay tuition fees for schools, colleges and universities, parent contributions and contributions for school activities. They also have to purchase books and materials, pay for transport from home to school and back for students who are not eligible for subsidised transport, pay for private tutoring, pay interest and repayments on student loans, and repay wrongfully received student grants, loans and allowances for school costs. Parents and/or students receive child care allowances, provisions for students with a disability and an allowance for school costs as well as student grants and loans and scholarships of companies. Companies and non-profit organisations incur costs for supervising trainees and apprentices who combine learning with work experience. They also contribute to the cost of work related education of their employees and spend money on research that is outsourced to colleges for higher professional education and universities. Furthermore they contribute to the childcare allowances given to households and provide scholarships to students. Companies receive subsidies and tax benefits for the creation of apprenticeship places and trainee placements and for providing transport for pupils. Organisations abroad contract universities in the Netherlands to undertake research for them. The European Union provides funds and subsidies for education to schools, colleges and universities as well as to the Dutch government. Foreign governments contribute to international schools in the Netherlands that operate under their nationality. The table also contains various indicators used nationally and internationally to compare expenditure on education and place it in a broader context. The indicators are compounded on the basis of definitions of Statistics Netherlands and/or the OECD (Organisation for Economic Cooperation and Development). All figures presented have been calculated according to the standardised definitions of the OECD. In this table tertiary education includes research and development, except for the indicator Expenditure on education institutions per student, excluding R&D. The statistic on Education spending is compiled on a cash basis. This means that the education expenditure and revenues are allocated to the year in which they are paid out or received. However, the activity or transaction associated with the payment or receipt can take place in a different year. Statistics Netherlands published the revised National Accounts in June 2024. Among other things, GDP and total government expenditures have been adjusted upwards as a result of the revision. Data available from: 1995 Status of the figures: The figures from 1995 to 2022 are final. The 2023 figures are provisional. Changes as of 31 December 2024: The final figures of 2021 and 2022 and the provisional figures of 2023 have been added. As a result of the revision of the National Accounts, among other things, GDP and total government expenditures have been adjusted upwards. The indicators in this table that are expressed as a percentage of GDP and total government expenditure have been updated for the entire time series from 1995 on the basis of the revised figures. When will new figures be published? The final figures for 2023 and the provisional figures for 2024 will be published in December 2025. More information on the revision policy of National Accounts can be found under 'relevant articles' under paragraph 3.

Analysis of ‘2009 - 2010 School Progress Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/5fa27cbe-81d9-42c4-b6ea-4c162f289ef7 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Progress Reports grade each school with an A, B, C, D, or F. These reports focus on a school's learning environment, student performance, and student progress. They were designed to help parents, teachers, principals, and others understand how well schools are doing—and compare them to other, similar schools.

--- Original source retains full ownership of the source dataset ---

This dataset is about books and is filtered where the book subjects is High school students-Rating of-United States, featuring 9 columns including author, BNB id, book, book publisher, and book subjects. The preview is ordered by publication date (descending).

The dataset includes the technical information and assessments from the school buildings (n = 67).

The values are as follows; • Pupils per building: < 200 = less than 200 pupils per building, 200–500 = from 22 to 500 pupils per building, > 500 = more than 500 pupils per building • Constructed: the year of construction • Renovated: the year of renovation • Experts A and B: The school building assessments of the technical experts combined in three categories: No deficiencies—Deficiencies—Renovated • Additional information: Additional information from the school buildings provided by the experts • The inspection report: The indoor air quality assessments from the inspection reports of the Environment Center of the city: No comments—Renovation work recommended—Health impacts • The targeted benchmarking data: The indoor air quality assessments in the targeted benchmarking data on the schools from the National Institute for Health and Welfare: No deficiencies—Deficiencies—Renovated • Technical assessment: IA (Indoor Air) non-problems—IA problems—IA problems renovated • Reasons for the decision: Agreement of the experts—Disagreement of the experts; the final decision made by following the order of precedence; (1) the assessments of the technical experts, (2) the additional information provided by the technical experts, (3) the assessments in the inspection report of the Environment Center of the city, (4) the assessments in the targeted benchmarking data on the schools from the National Institute for Health and Welfare.

This study consists of both qualitative and quantitative investigation of the influences on the school to prison pipeline. The quantitative study, the one included in this release, brings together four large datasets maintained by the Virginia Department of Education (DOE; Discipline Crime and Violence [DCV]), Department of Criminal Justice Services (DCJS; School Safety Audits and School Climate Data), and Department of Juvenile Justice (DJJ; Juvenile Referrals and Intakes). These datasets were used to compare what characteristics (individual or building level) either increase or decrease the odds that a student will become involved with the criminal justice system, as a result of school behaviors. The qualitative study involved in-depth individual interviews with 34 educational stakeholders across Virginia, who are involved in the discipline process in the schools (e.g. administrators, counselors, School Resource Officers). The analysis of these interviews found that the themes in how school discipline is differentiated from law enforcement in the schools, and the efforts that schools communities are making to keep children in the classroom and out of the courtroom. Individuals are the unit of analysis. The sample includes the following vulnerable populations: children, minorities, institutionalized persons, and persons with disabilities.

Data from a school-level randomized controlled trial (RCT) of the Double Check professional development model, focused on improving teachers' cultural responsivity and student engagement. Data were developed to evaluate the multi-component whole-school Double Check model, testing the combined impacts of school-wide data-based decision-making, along with staff professional development on culturally responsive practices, and classroom coaching using the Double Check version of the Classroom Check-up. Detailed descriptions of this model and intervention activities can be found in Bradshaw et al (2018; a description of the model from a prior trial) and Pas et al (2022; analysis of intervention activities from the present trial). A total of 41 middle school from two states in the mid-Atlantic region of the United States participated. Schools were recruited to participate in four cohorts. The first school-years of participation for these cohorts were 2015-2016, 2016-2017, 2017-2018, and 2018-2019, respectively. Teacher recruitment sessions were generally held in the weeks leading up to beginning of the school year (during faculty professional development days). A total of 352 teachers consented to participate in the RCT. Following Fall baseline data collection for each of the four cohorts, schools were randomly assigned to receive the Double Check model (n = 19) or to the comparison group (n = 22; i.e., business as usual). Recruited schools were assigned into paired matches within their cohort based on their school-level demographic characteristics and baseline data; one school in each pair was randomly assigned to each group to ensure balance across conditions. Intervention activities took place during the first year of each school's participation in the trial. During year 2, intervention schools also received two professional development “booster” sessions. These sessions reviewed the Double Check model and components of culturally responsive teaching, and facilitated action planning for the second academic year for teachers’ implementation of culturally responsive strategies. Data collection occurred at baseline (pre-test; Fall of year 1), post-test (Spring of year 1), and follow-up (Spring of year 2). Data from all cohorts and time points are included in this submission. Follow-up data are missing for the fourth cohort of schools, as their follow-up time point coincided with Spring of 2020, when the COVID-19 pandemic interfered with data collection within schools. At the completion of the two years of participation (one intervention year, one follow up year for data collection), comparison schools received all Double Check PD materials and individual staff members received training in the coaching model.

Abstract copyright UK Data Service and data collection copyright owner.Background:The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will requireto provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)to collect information on previously neglected topics, such as fathers' involvement in children's care and developmentto focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may beto emphasise intergenerational links including those back to the parents' own childhoodto investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when availableAdditional objectives subsequently included for MCS were:to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of EnglandFurther information about the MCS can be found on the Centre for Longitudinal Studies web pages.The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.End User Licence versions of MCS studies:The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.Sub-sample studies:Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).Release of Sweeps 1 to 4 to Long Format (Summer 2020)To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Secure Access datasets:Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).Secure Access versions of the MCS include:detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)linked education administrative datasets for Key Stages 1, 2 and 4 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;Banded Distances to English Grammar Schools for MCS5 held under SN 8394linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030linked Hospital of Birth data held under SN 5724.The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page). The Millennium Cohort Study, Sweeps 3-6, 2006-2015: Banded Distances between Home and School study provides banded straight-line distances between the address at interview and the school attended by each cohort member for MCS3-MCS6 inclusive. Distances were calculated in a SIR database environment using the co-ordinates (eastings/northings of the British National Grid) of the unit postcode centroid of the address at interview and the unit postcode of the school attended, using the Pythagorean Theorem.

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old. End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Health Administrative Datasets (SAIL) for Wales held under SN 9310
  
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

The MCS Linked Education Administrative Dataset (KS1), Scotland: Secure Access (SN 7414) includes a data file containing selected information from the Pupil Census, 2008, the School Meals Survey and attendance and absence records for the year 2008-2009, for those cohort members attending a school in Scotland at the time of MCS4 interview. Also included are anonymised Local Education Authorities (LEA) and anonymised School Numbers, to allow comparison of results across LEA and school. The data were obtained only for children whose parents/carers gave consent to data linkage, and who were successfully matched.

This study only includes data for MCS cohort members attending schools in Scotland. Data for England and Wales are available under SNs 8481 and 7415 respectively.

In this study, we took advantage of the randomized allocation of the US EPA's funding for school bus replacements and retrofits to causally assess the impacts of upgrading buses on students' educational performance through the EPA’s national School Bus Rebate Program. Specifically, we used classical intent-to-treat analyses for randomized controlled trials to compare the change in school district level reading and language arts and math standardized test scores after vs before the 2012 through 2016 lotteries by funding selection status . We used overall district average standardized test scores since rates were not available for only school-bus riders.

State comparisons data for food stamps, National School Lunch Program, TANF, supplemental security income, Medicare, Medicaid, child care, child abuse, child neglect, and Social Security. Data include a national ranking.

Progress Reports grade each school with an A, B, C, D, or F. These reports focus on a school's learning environment, student performance, and student progress. They were designed to help parents, teachers, principals, and others understand how well schools are doing—and compare them to other, similar schools.

Discourse on students' moral dilemmas in a comparison of three Hungarian school models

This study provides an evidence-based understanding on etiological issues related to school shootings and rampage shootings. It created a national, open-source database that includes all publicly known shootings that resulted in at least one injury that occurred on K-12 school grounds between 1990 and 2016. The investigators sought to better understand the nature of the problem and clarify the types of shooting incidents occurring in schools, provide information on the characteristics of school shooters, and compare fatal shooting incidents to events where only injuries resulted to identify intervention points that could be exploited to reduce the harm caused by shootings. To accomplish these objectives, the investigators used quantitative multivariate and qualitative case studies research methods to document where and when school violence occurs, and highlight key incident and perpetrator level characteristics to help law enforcement and school administrators differentiate between the kinds of school shootings that exist, to further policy responses that are appropriate for individuals and communities.

This survey is a follow-up to the 2009 survey with additions and specializations in key parameters/variables of education for the country as well as individual administrative units. The data were obtained from the Hellenic Statistical Authority. The purpose of this survey is to analyse indicators related to education and compare them over time in order to draw conclusions on the development of education. The analysis concerns the comparative evolution over time of specific variables such as the number of teachers and students per level of education and regional unit, the number of school units, the number of higher education institutions, staff and students.

Key Stage 2 (KS2) data for year 6 primary school pupils who met or exceeded the Expected Standard (EXS+) by School Ward for the period 2016 onwards. The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER) but the figures come from the Department of Education (DfE).

A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance.

Please note some DFE numbers might have changed please see previous DFE code on Schools list.