Introduction

Google Classroom Statistics: Google Classroom is a free blended learning platform developed by Google to streamline the process of creating, distributing, and grading assignments. Since its launch in 2014, it has become a widely adopted tool in educational institutions worldwide. By the first half of 2024, Google Classroom had approximately 10 million daily active users on Android. This growth is attributed to its integration with Chromebooks and its role in facilitating remote learning during the COVID-19 pandemic.

In the United States, the platform is prevalent in K–12 schools, with an estimated 60,000 schools utilizing it as of 2022. Globally, Google Classroom is used in over 230 countries and territories, supporting millions of teachers and students in managing coursework and communication. The article explores market share, customers, and major developments concerning Google Classroom statistics in the year 2024.

In January 2021, the Google Classroom application was downloaded more 465,460 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.

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

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

This statistic shows the percentage of the U.S. adult population that belonged to the middle class from 1971 to 2015, by race and ethnicity. In 2015, about 50 percent of U.S. adult residents were part of the middle class. In that year 56 percent of those who some hadcollege belonged to the middle class, compared to only 37 percent of those who did not graduate from high school.

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.

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).

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 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.

Use of the laptop or tablet that was replaced or that the owner stopped using, by demographic characteristics. National.

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).

Survey on Equipment and Use of Information and Communication Technologies in Households: Use of the Internet by demographic characteristics and last time of use. National.

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 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 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent 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 to 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.

Between November 2020 and November 2021, about 40 percent of users on the online education platform Tencent Classroom in China were female. The share of female students using the platform increased during the outbreak of the coronavirus COVID-19 pandemic. Before the pandemic, only 35 percent of the users were female.

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.

Historical Dataset of Cecil County School Of Technology is provided by PublicSchoolReview and contain statistics on metrics:Total Classroom Teachers Trends Over Years (2003-2023)

Laos General Education: Number of Classroom: Primary data was reported at 34,305.000 Unit in 2017. This records an increase from the previous number of 34,229.000 Unit for 2016. Laos General Education: Number of Classroom: Primary data is updated yearly, averaging 28,389.000 Unit from Dec 1985 (Median) to 2017, with 21 observations. The data reached an all-time high of 34,305.000 Unit in 2017 and a record low of 18,720.000 Unit in 1985. Laos General Education: Number of Classroom: Primary data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.G017: Education Statistics.

Use of the Internet by demographic characteristics and last time of use. National.

This article introduces how to teach an interactive one-semester-long statistics and programming class. The setting can also be applied to shorter and longer classes as well as for beginner and advanced courses. I propose a project-based seminar that also inherits elements of an inverted classroom. Thanks to this character, the seminar supports the students' learning progress and can also create engaging virtual classes. To showcase how to apply a project-based seminar setting to teaching statistics and programming classes, I use an introductory class to data wrangling and management with the statistical software R. Students are guided through a typical data science workflow that requires data management, data wrangling, and ends with visualizing and presenting first research results during a mini-conference.

No of Classroom: Middle School data was reported at 85,759.000 Unit in 2017. This records an increase from the previous number of 85,692.000 Unit for 2016. No of Classroom: Middle School data is updated yearly, averaging 48,282.000 Unit from Dec 1968 (Median) to 2017, with 50 observations. The data reached an all-time high of 86,222.000 Unit in 2015 and a record low of 14,695.000 Unit in 1968. No of Classroom: Middle 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).

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.