In January 2021, the Google Classroom application was downloaded more ******* times in the United Kingdom, which was a peak for downloads of this app during the provided time period. The closure of UK schools due to the Coronavirus pandemic at this time resulted in teachers and students having to learn remotely, and explains the sharp upticks in downloads seen in January 2021 and March 2020.

Enrollment is a head count of all students receiving their primary PK-12 educational services through Wisconsin public schools. This map is in a series of maps that show enrollments by district for a particular student group (demographic) for the 2023-2024 school year. Additional enrollment data are available for the public to view on the WISEdash Public Portal. Enrollment data is sourced from the WISEdata system. Enrollment Count is the number of students enrolled on specific dates as determined by school enrollment/exit dates that cover those dates. Percent Enrollment by Student Group is a percent of the enrollment count for all student groups combined. DPI collects data to meet all required school, district, state, and federal reporting mandates, e.g., Every Student Succeeds Act (ESSA), Individuals with Disabilities Education Act (IDEA), and Title II Higher Education Act. These data inform education research and data analysis. Multiple teams from IT and content areas work together at DPI to build tools for data collection, to support districts in data collection, and to report on and facilitate the use of data based on federal and state reporting mandates. Through the DPI dashboard and reporting tools, DPI staff, teachers, administrators, parents, and researchers are better able to understand and improve educational outcomes for Wisconsin students.A person's race or ethnicity is the racial and/or ethnic group to which the person belongs or with which he or she most identifies. Ethnicity is self-reported as either Hispanic/Not Hispanic. Race is self-reported as any of the following 5 categories: Asian, American Indian or Alaskan Native, Black or African American, Native Hawaiian or other Pacific Islander, or White. The data displayed reflects the race/ethnicity that is reported by school districts to DPI.An economically disadvantaged student is one who is identified by Direct Certification (only if participating in the National School Lunch Program) OR a member of a household that meets the income eligibility guidelines for free or reduced-price meals (less than or equal to 185 percent of Federal Poverty Guidelines) under the National School Lunch Program (NSLP) OR identified by an alternate mechanism, such as the alternate household income form.English Learner status is any student whose first language, or whose parents' or guardians' first language, is not English and whose level of English proficiency requires specially designed instruction, either in English or in the first language or both, in order for the student to fully benefit from classroom instruction and to be successful in attaining the state's high academic standards expected of all students at their grade level.

Context

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Content

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Acknowledgements

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Inspiration

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This statistic shows the percentage of the U.S. adult population that belong to the middle class from 1971 to 2015, by education. In 2015, about 50 percent of U.S. adult residents were part of the middle class.

This study defined middle class income households as those with an income between 67 and 200 percent of the U.S. median household income, after adjustment for household size. Middle class income ranges from about 42,000 U.S. dollars to about 126,000 U.S. dollars per year for a three-person household.

This dataset presents statistics on the number and total sales, value of shipments, or revenue of establishments; distribution of sales, shipments, or revenue by class of customer; and sales, shipments, or revenue of establishments responding to class of customer inquiry as a percent of total revenue for selected industries for selected geographies. Includes only establishments of firms with paid employees.

This statistic shows the distribution of target populations of online education programs in the United States in 2019. In 2019, ** percent of respondents stated that their online education programs were aimed at adult students returning to school after an absence.

This is a longitudinal file that provides information about the students and the classroom in all grades, from first to sixth. It is an essential file that researchers will necessarily have to merge with the other files containing the variables of interest. The file provides information to identify and locate each student in each grade (e.g., identification number, cohort and sample to which he/she belongs, classroom in which he/she is enrolled in each grade, year of entry or exit from the sample,...), and demographic information (sex, date of birth, age in each grade,...), inclusion information (ethnicity, time in Spain, Spanish language proficiency, degree of absenteeism,...), his/her sociometric status at each moment and whether he/she meets criteria to receive intervention. Finally, it also includes data on the classroom in which the participant is enrolled each year and the tutor teacher (e.g., classroom ratio, whether the composition of the classroom is changing on a scheduled basis, sex of the teacher and whether the tutor has changed with respect to the previous year). Most of the information was provided by the teacher and is part of the STUDENT-INFORM and CLASSROOM-INFORM files, but it also includes information provided by researchers in the SUJ-2 files and information provided by peers in the SOCIOMET-P files. The data were collected in public schools in Castellón (Spain) mostly in the fall of each school year, but many variables were also measured in the spring, from first to sixth grade of primary education, from school year 2010-11 to school year 2015-16. To learn more about our research and access to other datasets of this or other measures, follow the link GREI Longitudinal Project

Se trata de un fichero longitudinal que aporta información sobre los estudiantes y el aula en todos los cursos, de primero a sexto. Se trata de un fichero esencial que necesariamente los investigadores tendrán que fusionar con los otros ficheros que contengan las variables de su interés. El fichero proporciona información para identificar y localizar a cada estudiante en cada curso (p.e, número de identificación, cohorte y muestra a la que pertenece, aula en la que está escolarizado en cada curso, curso de incorporación o de salida de la muestra,…), e información demográfica (sexo, fecha de nacimiento, edad en cada curso,..), de inclusión (etnia, tiempo en España, dominio d la lengua española, grado de absentismo,…), su estatus sociométrico en cada momento y si reúne criterios para recibir intervención. Por último, también incluye datos sobre el aula en la que el participante está escolarizado cada curso y del profesor tutor (p.e., ratio del aula, si la composición del aula cambia de forma programada en determinados cursos, el sexo del profesor y si la clase ha cambiado de tutor respecto del curso anterior). La mayor parte de la información ha sido proporcionada por el profesor y forma parte de los ficheros STUDENT-INFORM y CLASSROOM-INFORM, pero también incluye información aportada por los investigadores en los ficheros SUJ-2 e información aportada por los iguales en los ficheros SOCIOMET-P. Los datos fueron recogidos en centros públicos de Castellón (España) mayoritariamente en otoño de cada curso, pero muchas variables también fueron medidas en primavera, desde primero a sexto curso de educación primaria, desde el (curso escolar 2010-11 al curso escolar 2015-16. Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace Proyecto Longitudinal GREI

Korea Number of Classroom: High School data was reported at 97,571.000 Unit in 2017. This records a decrease from the previous number of 97,632.000 Unit for 2016. Korea Number of Classroom: High School data is updated yearly, averaging 42,309.500 Unit from Dec 1968 (Median) to 2017, with 50 observations. The data reached an all-time high of 97,632.000 Unit in 2016 and a record low of 9,316.000 Unit in 1969. Korea Number of Classroom: High School data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s South Korea – Table KR.G068: Education Statistics: Number of Schools, Teachers, Classroom and Students (Annual).

Abstract

In Brazil, policy makers in the state of Ceara are looking at how providing information to schools about best teaching practices, as well as offering peer learning opportunities, can help boost the performance of less effective teachers. The state government wants to stimulate more interaction among teachers at the school level that will lead to faster and cheaper diffusion of good practices within schools. The Secretariat requested World Bank assistance with the design and implementation of the random assignment experiment during the 2015 school year to measure cost-effectiveness of this approach.

The endline data collection was carried out in October - November 2015. Researchers used "Stallings Classroom Snapshot" instrument to gather information about teachers' use of time, materials and interactive pedagogical practices. The observations were made in 3,121 classrooms of 10th, 11th and 12th grade in randomly selected 300 schools.

The schools were randomly assigned to a treatment group (156 schools) or a control group (136 schools). The treatment was launched in March 2015. The treatment group received detailed feedback on the school's results from the classroom observations, information on teacher performance, self-help materials that included a book, videos and exercises about effective teaching strategies, and a log book and classroom observation templates to record teachers' observations of one other. The control schools received neither feedback nor information. After the treatment, researchers assessed the results of student test scores to determine whether the campaign helped improve classroom learning.

The baseline survey was conducted in November 2014.

Geographic coverage

The state of Ceará

Analysis unit

Classrooms; Schools

Kind of data

Observation data/ratings [obs]

Sampling procedure

Ceará has 573 secondary schools that offer the complete three-year cycle. Of these, a sample of 400 schools was stratified by size, geographic area and quartile of learning results. Researchers randomly assigned the 400 schools into 4 groups, with the first 175 assigned to the treatment group, a second group of 25 assigned to a no-observation group, the next 175 schools assigned to the control group, and the last 25 schools also assigned to the no-observation group.

A late start to the baseline round of classroom observations and a limited budget led to a reduction in the sample to 350 schools (175 treatments and 175 controls), which were selected through simple randomization to keep the sample balance. The team did not observe any classroom in the group of 50 schools that were randomly assigned to a no-observation group of the study, but was able to analyze the students' assessments results afterwards.

Sampling deviation

Out of the 350 schools of the randomization, with 175 each planned for treatment and controls, 292 schools were observed in November 2014 and in November 2015. The full initial sample could not be observed due to disruptions in the school calendar in November 2014 (standardized tests and holidays) and a shortage of observers in the Fortaleza district. The 292-school final sample included 156 schools in the treatment group and 136 in the control group. This difference in the attrition of treatment and control schools was due to the data collection firm focusing their efforts on making up for the schools of the treatment group that would benefit from the classroom observation and the intervention. As a result, because the loss of schools from the treatment and control groups was uneven, the research team conducted a series of balance checks to test the randomization.

In the treatment sample, the 19 schools that were not observed could not receive the information treatment (benchmarked classroom observation feedback for the teachers in their school). But these schools were given access to the other three components of the program – self-help materials, face-to-face training and coaching, and were observed again at endline. The same schools were observed to obtain the endline data. Matched repeat observations were made in 2,399 classrooms, 75% of those observed at baseline. Variations in the school calendar and logistical issues resulted in 25% of the 2015 observations being conducted in grades and subjects in the school that had not been observed at baseline.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) The Stallings Classroom Snapshot Coding Sheet: The classroom snapshot records the participants, their activities, and the materials being used in the classroom, at ten separate instances throughout a class period.

2) School Principals Questionnaire: The questionnaire gathers information about teachers' engagement in the school, level of teacher training activities, and Principals' and supervisors' assessments of the value and impact of the treatment.

3) Classroom Demographic Sheet: The instrument is used for identification of the school and classroom, and the basic information related to the observed classroom, such as the number of student and the start time of the class.

Demographics of health workers who attended the classroom training (N = 48).

Survey on Equipment and Use of Information and Communication Technologies in Households: Number of times you have purchased through a Internet, for personal reasons, in the last 3 months by demographic characteristics and range. National.

School demographic.

By 2030, the middle-class population in Asia-Pacific is expected to increase from **** billion people in 2015 to **** billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from *** million in 2015 to *** million in 2030. Worldwide wealth While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around ** percent of the world’s population had assets valued at less than 10,000 U.S. dollars, while less than *** percent had assets of more than one million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percentage of non-investable assets. The middle-class The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth among the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle class.

The number of students starting in Ivy League schools for the Class of 2028 (those beginning in the Fall of 2024), varied from school to school. Cornell University had the largest Class of 2028 among the Ivy League schools, with ***** enrolled students.

This dataset tracks annual total classroom teachers amount from 1988 to 2023 for Thomas Dale High School

A dataset of Government schools average Secondary School English Class Size, showing average for Year 12 and overall secondary classes, from census year 2001 to 2025.\r
\r
The size of secondary English classes is collected from government schools as part of the February School Census conducted on the last school day of February each year.\r
The data is based on the number of English classes in secondary year levels. English class size is an indication of the size of classes in secondary schools, as almost all students study English. This includes each compulsory and elective English class for secondary students held during the week of the census. Secondary students not studying English are NOT counted in the class size return. Also included are classes (such as Remedial English or ESL / English as a Second Language) that a student attends instead of compulsory English. Excluded are classes such as English Literature, Remedial English or ESL that a student attends as well as “compulsory” English. Please note that extra teaching support is NOT included when calculating the average class size. Average class size is NOT the same as the student/teacher ratio.

Korea Number of Classroom: Kindergarten data was reported at 34,748.000 Unit in 2017. This records an increase from the previous number of 33,392.000 Unit for 2016. Korea Number of Classroom: Kindergarten data is updated yearly, averaging 15,635.500 Unit from Dec 1968 (Median) to 2017, with 50 observations. The data reached an all-time high of 34,748.000 Unit in 2017 and a record low of 857.000 Unit in 1969. Korea Number of Classroom: Kindergarten data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s South Korea – Table KR.G068: Education Statistics: Number of Schools, Teachers, Classroom and Students (Annual).

Sourcing accurate and up-to-date geodemographic data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent geodemographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

• Better understand your customers
• Identify optimal locations to expand your retail footprint
• Define sales territories for franchisees
• Run targeted marketing campaigns.

Premium geodemographics data for Asia and MENA includes the latest estimates (updated annually) on:

1. Population (how many people live in your local catchment)
2. Demographics (who lives within your local catchment)
3. Worker population (how many people work within your local catchment)
4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

Primary Use Cases for GapMaps Geodemographic Data:

1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
5. Target Marketing: Develop effective marketing strategies to acquire more customers.

6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

8. Tenant Recruitment

9. Target Marketing

10. Market Potential / Gap Analysis

11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

12. Customer Profiling

13. Target Marketing

14. Market Share Analysis

For more information about this layer please see the GIS Data Catalog.This layer was originally created to support the STAR Rating System objective EE-4: Equitable Services & Access Community Level Outcomes for King County. Three demographics are combined into one attribute to determine King County services access analysis by census tract. Each demographic: English proficiency, people of color, and household income, was applied to census tracts separately. This demographic information is based on the 2016 - 2020 American Community Survey from the Census Bureau. The demographic was sorted into five classes using the Natural Breaks classification. Then each class was given a score: 1 for the first class, 2 for the second class, 3 for the third class, etc. Next, each census tract received a score based on the class it was in: 1 if it was in the first class, 2 if it was in the second class, 3 if it was in the third class, etc. So each census tract will have a score for English proficiency (ESL_Score), a score for people of color (RE_Score), and a score for household income (Income_Score). These scores were added up (TotalScore) and an evenly weight average was determined (WeightedTotal333333). Thus each score for the census tracts represents a combination of demographics where lower scores mean a wealthier, less diverse community and higher scores mean more diverse, less wealthy community.

Financial overview and grant giving statistics of Classroom Teachers Council