During the academic year of 2021, around 18,614 constant 2022-23 U.S. dollars were spent on each pupil in public elementary and secondary schools in the United States. This is an increase from 1990, when 12,206 constant 2022-23 U.S. dollars were spent per pupil.

Out of the OECD countries, Luxembourg was the country that spent the most on educational institutions per full-time student in 2020. On average, 23,000 U.S dollars were spent on primary education, nearly 27,000 U.S dollars on secondary education, and around 53,000 U.S dollars on tertiary education. The United States followed behind, with Norway in third. Meanwhile, the lowest spending was in Mexico.

I downloaded this data from the ElSi (Elementary/Secondary Information System) tableGenerator hosted by the Institute of Educational Sciences' National Center for Education Statistics. ELSI tableGenerator

The cleaned, analysis-ready files are "finances_2001_2017.csv" and "pupils_fte_teachers_2001_2019.csv".

I am going to add graduation rate data. This is for an undergrad project on marijuana legalization and high school graduation rates.

Variable Definitions: "Total Expenditures (TE11+E4D+E7A1) per Pupil (MEMBR) [State Finance] This is the Total Expenditures (Digest) divided by the fall membership as reported in the state finance file. The Total Expenditures (Digest) is the subtotal of Direct State Support Expenditures for Private Schools (e4d), Debt Services Expenditures - Interest (e7a1) and Total Expenditures for Education (te11). These data are from the CCD National Public Education Financial Survey."

"Total revenues per student are the total revenues from all sources (tr) divided by the fall membership as reported in the state finance file. These data are from the CCD National Public Education Financial Survey."

"Full-Time Equivalent (FTE) Teachers [State] This is the total number of full-time equivalent teachers in a state as defined by the CCD State Nonfiscal Survey."

"Grades 9-12 Students [State] This is the number of students in a state who are enrolled in ninth grade through twelfth grade. These data are taken from the CCD State Nonfiscal survey."

#### Wallpaper by NeONBRAND on Unsplash

This dataset contains special education program characteristics and student demographics since 2019. It is a long file that contains multiple rows for each district, with rows for different years and indicators. For definitions of each indicator, please visit the RADAR Special Education Dashboard.

Resource Allocation and District Action Reports (RADAR) enable district leaders to compare their staffing, class size, special education services, school performance, and per-pupil spending data with similar districts. They are intended to support districts in making effective strategic decisions as they develop district plans and budgets.

This dataset is one of five containing the same data that is also published in the RADAR Special Education Dashboard: Special Education Program Characteristics and Student Demographics Special Education Placement Trajectory Students Moving In and Out of Special Education Services Special Education Indicators Special Education Student Progression from High School through Postsecondary Education

List of Indicators

• Enrollment
• Gradespan
• Race/Ethnicity
• Gender
• EL and Low Income/Economically Disadvantaged
• In District/Out of District
• Placement
• Disability Type
• Special Education FTEs per 100 SWDs

In 2023, general education was the major segment for the Russian government's spending, measured at around **** trillion Russian rubles, followed by higher and preschool education. What percent of the Russian GDP goes to education? Government spending on education accounted for less than **** percent of the Russian GDP in 2021, a figure that has slightly decreased in recent years. However, Russia’s education spending was lower than in OECD countries on average, which was measured at *** percent in 2018. For comparison, the United States spent *** percent of GDP on education in that year. How much does Russia spend on education? In total, the government expended nearly *** trillion Russian rubles on the educational sector in 2023. Looking at the average spending per student, the highest figure was recorded for higher education, at ******* Russian rubles. That was equal to approximately ***** U.S. dollars. To compare, on average in the OECD, the tertiary education expenditure per student neared ****** U.S. dollars in 2019.

Data on annual expenditure by educational institutions per student, in Canadian and American dollars, reference year 2020/2021. At the primary/secondary level, the amount spent on educational core services and ancillary services is also presented.

Historical Dataset of Shaw High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2016-2020),Total Classroom Teachers Trends Over Years (2016-2020),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2016-2020),Black Student Percentage Comparison Over Years (2016-2020),White Student Percentage Comparison Over Years (2019-2020),Diversity Score Comparison Over Years (2019-2020),Free Lunch Eligibility Comparison Over Years (2016-2020),Reading and Language Arts Proficiency Comparison Over Years (2015-2019),Math Proficiency Comparison Over Years (2015-2019),Overall School Rank Trends Over Years (2015-2019),Graduation Rate Comparison Over Years (2015-2020)

Time series data for the statistic Initial government funding per pre-primary student, constant PPP$ and country Mauritius. Indicator Definition:Total general (local, regional and central, current and capital) initial government funding of education per student, which includes transfers paid (such as scholarships to students), but excludes transfers received, in this case international transfers to government for education (when foreign donors provide education sector budget support or other support integrated in the government budget). Calculation Method: Total general (local, regional and central) government expenditure (current and capital) on a given level of education (primary, secondary, etc) minus international transfers to government for education, divided by the number of student enrolled at that level of education. This is then expressed at constant purchasing power parity (constant PPP$). Limitations: In some instances data on total government expenditure on education refers only to the Ministry of Education, excluding other ministries which may also spend a part of their budget on educational activities. There are also cases where it may not be possible to separate international transfers to government from general government expenditure on education, in which cases they have not been subtracted in the formula. For more information, consult the UNESCO Institute of Statistics website: http://www.uis.unesco.org/Education/The indicator "Initial government funding per pre-primary student, constant PPP$" stands at 664.27 usd as of 12/31/2019, the highest value at least since 12/31/1972, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.96 percent compared to the value the year prior.The 1 year change in percent is 6.96.The 3 year change in percent is 23.28.The 10 year change in percent is 168.59.

This graph presents the distribution of the monthly expenditure of a French high school student in 2019, by type. It displays that ** percent of the expenses made by a high school student in a month in France that year concerned shopping. Sports represented **** percent of the monthly expenditure of a French high school student.

Time series data for the statistic Initial government funding per pre-primary student, constant PPP$ and country Maldives. Indicator Definition:Total general (local, regional and central, current and capital) initial government funding of education per student, which includes transfers paid (such as scholarships to students), but excludes transfers received, in this case international transfers to government for education (when foreign donors provide education sector budget support or other support integrated in the government budget). Calculation Method: Total general (local, regional and central) government expenditure (current and capital) on a given level of education (primary, secondary, etc) minus international transfers to government for education, divided by the number of student enrolled at that level of education. This is then expressed at constant purchasing power parity (constant PPP$). Limitations: In some instances data on total government expenditure on education refers only to the Ministry of Education, excluding other ministries which may also spend a part of their budget on educational activities. There are also cases where it may not be possible to separate international transfers to government from general government expenditure on education, in which cases they have not been subtracted in the formula. For more information, consult the UNESCO Institute of Statistics website: http://www.uis.unesco.org/Education/The indicator "Initial government funding per pre-primary student, constant PPP$" stands at 2.23 Thousand usd as of 12/31/2019, the highest value since 12/31/2010. Regarding the Three-Year-Change of the series, the current value constitutes an increase of 33.38 percent compared to the value three years prior.The 3 year change in percent is 33.38.The 5 year change in percent is 61.68.The 10 year change in percent is -13.49.The Serie's long term average value is 1.73 Thousand usd. It's latest available value, on 12/31/2019, is 28.58 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2012, to it's latest available value, on 12/31/2019, is +63.71%.The Serie's change in percent from it's maximum value, on 12/31/2009, to it's latest available value, on 12/31/2019, is -13.49%.

Higher education is one of the ways to overcome social inequalities in rural areas in developing countries. This has led states to develop public policies aimed at access, retention and timely graduation of students in those sectors, yet the high drop-out rates among the rural student population, which were catalysed by COVID-19, prevent the intrinsic and extrinsic benefits of obtaining a higher education degree from materialising. Thus, the study of the phenomenon of dropout before and after the pandemic has not sufficiently addressed the economic issues raised by this phenomenon for the different actors at the educational level. The purpose of this paper is to model the economic effects of rural student dropout at the higher education level for students and families, Higher Education Institutions (HEIs) and the State, based on public policies for access to higher education, in the pandemic and post-pandemic scenario. In order to delimit the operationalisation of the proposed model, a set of undergraduate training programmes in Colombia was taken as a reference. System dynamics was used as the main modelling technique. The model was based on data from the 20 training programmes with the highest number of students enrolled in rural areas for the year 2019, by running three computational simulations. The results showed the description of the dynamic model and the financial effects of dropout for the actors of the educational level with the current policies of access to higher education, the scenario in which COVID-19 would not have occurred and the consolidation of the public policy of tuition fee exemption in public HEIs as a result of the pandemic. It was concluded that the model developed is very useful for the valuation of these economic effects and for decision-making on policies to be implemented, given that the costs of dropout are characterised by high costs for students and their families as well as for HEIs, and where it was determined that current policies are inefficient in preventing and mitigating dropout.

Abstract

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

Geographic coverage

National

Analysis unit

Schools, teachers, students, public officials

Kind of data

Sample survey data [ssd]

Sampling procedure

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location.

For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions.

For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools werer sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

Sampling deviation

MELQO data was merged with the Peru school frame in order to optimally stratify. We stratified on the basis of urban/rual and department. There are 25 departments in Peru. In 2017, Peru conducted an examination of around 4,500 children between 5 and 8 years old, with a median age of 6. The MELQO exam is quite similar to our ECD examination module. We are able to use data from this 2017 survey to choose the number of schools in each province optimally by calculating means and standard deviations by province and feeding this information into the optimal stratification algorithm. See https://cran.r-project.org/web/packages/SamplingStrata/vignettes/SamplingStrata.html. Provinces with low standard deviations among students in terms of their MELQO development scores are allocated fewer schools compared to an allocation that is simply based on population, and provinces with high standard deviations are allocated more schools.

203 schools were chosen for our survey after optimally stratifying.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

More information pertaining to each of the three instruments can be found below:

• School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

• Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey questions.

• Survey of Public Officials: The Survey of Public Officials collects information about the capacity and orientation of the bureaucracy, as well as political factors affecting education outcomes. This survey is a streamlined and education-focused version of the civil-servant surveys that the Bureaucracy Lab (a joint initiative of the Governance Global Practice and the Development Impact Evaluation unit of the World Bank) has implemented in several countries. The survey includes questions about technical and leadership skills, work environment, stakeholder engagement, impartial decision-making, and attitudes and behaviors. The survey takes 30-45 minutes per public official and is used to interview Ministry of Education officials working at the central, regional, and district levels in each country.

Sampling error estimates

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level.

Context

College tuition data is somewhat difficult to find - with many sites limiting it to online tools.

Content

The data this week comes from many different sources but originally came from the US Department of Education. The most comprehensive and easily accessible data cames from TuitionTracker.org who allows for a .csv download! Unfortunately it's in a very wide format that is not ready for analysis, but tidyr can make quick work of that with pivot_longer(). It has a massive amount of data, I have filtered it down to a few tables as seen in the attached .csv files. Tuition and diversity data can be quickly joined by dplyr::left_join(tuition_cost, diversity_school, by = c("name", "state")). Some of the other tables can also be joined but there may be some fuzzy matching needed.

Historical averages from the National Center for Education Statistics (NCES) - spanning the years 1985 - 2016.

• Tuition and fees by college/university for 2018-2019, along with school type, degree length, state, in-state vs out-of-state from the Chronicle of Higher Education.
• Diversity by college/university for 2014, along with school type, degree length, state, in-state vs out-of-state from the Chronicle of Higher Education.
• Example diversity graphics from Priceonomics.
• Average net cost by income bracket from TuitionTracker.org.
• Example price trend and graduation rates from TuitionTracker.org
• Salary potential data comes from payscale.com.

Acknowledgements

The data was downloaded and cleaned by Thomas Mock for #TidyTuesday during the week of March 10th, 2020. You can see the code used to clean the data in the TidyTuesday GitHub repository.

Inspiration

Use this dataset to explore the costs of college tuition in the US on their own, by geographic area, degree type, and/or salary. Whatever you choose to explore, consider sharing your notebook on Twitter using the #TidyTuesday hashtag!

License

The data provided in the TidyTuesday repository is licensed under the MIT License.

Snapshot img

US Community College Market Size 2025-2029

The US community college market size is forecast to increase by USD -7825.8 million, at a CAGR of -2.7% between 2024 and 2029.

The Community College market in the US is experiencing significant shifts driven by the growing emphasis on non-traditional learning and the evolving education marketing process. This trend is fueled by the increasing number of adults returning to education and the need for flexible learning options. However, community colleges face challenges in securing adequate funding, which may hinder their ability to meet the demands of an expanding student population. The education landscape is transforming, with community colleges playing a pivotal role in catering to the needs of non-traditional learners. The marketing process has become increasingly important as institutions compete for students in a crowded market.
Yet, reduced funding poses a significant challenge. Community colleges must navigate this financial obstacle by exploring innovative funding models and cost-effective solutions to maintain their competitiveness and continue providing accessible, affordable education. Adapting to these market dynamics and addressing funding constraints will be crucial for community colleges seeking to capitalize on opportunities and thrive in the evolving educational landscape.

What will be the size of the US Community College Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The community college market in the US is characterized by a shift towards hybrid learning and competency-based education, as resource management and curriculum mapping gain prominence. Student recruitment strategies are increasingly data-driven, with mobile learning and learning analytics playing crucial roles. Institutional advancement efforts include compliance regulations, capital campaigns, and board of trustees engagement. Budget allocation and information technology investments are key areas of focus for administrators, with technology infrastructure and program review shaping the future of education. Faculty governance, endowment management, and professional development are essential components of institutional success.
Skills gap analysis and blended learning are critical in addressing workforce needs, while accreditation standards ensure academic rigor. Personalized learning and alumni relations strengthen student engagement, and faculty recruitment and shared governance foster a collaborative learning environment.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Revenue Stream

  Government funds
  Tuition and fees
  Grants and contracts
  Others


Courses

  Associate degree
  TVET certification
  Continuing education
  Bachelors degree


Student Type

  Traditional
  Non-Traditional
  Online
  Recent High School Graduates
  Adult Learners
  Career Changers


Delivery Mode

  On-Campus
  Online
  Hybrid


Subject Area

  STEM
  Healthcare
  Business
  Liberal Arts


Geography

  North America

    US

By Revenue Stream Insights

The government funds segment is estimated to witness significant growth during the forecast period.

Community colleges in the US receive the majority of their revenue from government funds, primarily from state, local, and central sources. These funds support various aspects of college operations, including instructor salaries, staff compensation, and infrastructure improvements. Thirty-two out of the fifty states in the US employ funding formulas to distribute resources to their respective colleges. Some states, such as Washington and Ohio, have adopted performance-based funding models to incentivize enrollment growth and expedite graduation rates. Educational technology plays a significant role in community colleges, with online learning platforms and classroom technology enhancing the learning experience. Dual enrollment programs enable high school students to earn college credits, while GED preparation courses help adults attain their diplomas.

Faculty development and program assessment ensure academic rigor and continuous improvement. International students contribute to campus diversity, with career services and student affairs providing support. Campus safety and accessibility compliance are essential considerations, as are technical skills training, workforce development, certificate programs, and continuing education. Transfer agreements facilitate seamless transitions to four-year institutions, while ESL programs cater to non-native English speakers. Associate degrees and bachelor's degrees

Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.

How Are We Protecting Privacy?

Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.

This information is also available on the Ministry of Education's School Information Finder website by individual school.

Descriptions for some of the data types can be found in our glossary.

School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.

Snapshot img { margin: 10px !important; } Market outlook of global classroom collaboration management systems

According to the classroom collaboration management systems market research, Technavio’s market research analysts predict the global classroom collaboration management systems market to grow at a CAGR of close to 19% during the forecast period.

Classroom collaboration management systems market growth

Increased adoption of synchronous e-learning in educational institutions has significantly influenced the classroom management systems market growth. The software is likely to penetrate the education sector as many educational institutions are deploying it to improve the quality and effectiveness of e-learning. Apart from this, rising need for controlled lecture sessions through the software is expected to make significant changes in the methods of conducting classroom sessions. However, the many costs involving setup and installation of the software in classrooms act as an impediment to the market growth. Market vendors will look to work around costs incurred by education intuitions related to training teachers and IT staff which is a necessity for schools and colleges to implement.

How are collaboration management systems useful?

The classroom collaboration management system is an effective tool for managing classes using online modes of teaching. Online classroom structures typically require students to access digital content with the help of computers and tablets, thereby enhancing interactivity and real-time knowledge sharing.

As learning abilities and levels of monitoring differ for every student, it is essential for educators to implement classroom collaboration management software to facilitate collaborative learning within the required timeframe and curriculum. With the help of collaborative systems, teachers can easily identify challenges faced by students in understanding subjects and complex topics. It helps develop mechanisms to tackle the same. Hence, the software empowers teachers to create classes as per the need of students and tweak it as and when required.

Classroom collaboration management systems market by end-user

Higher Education
Primary Education

Based on the classroom management systems industry report, the higher education segment is witnessing healthy growth because of many new universities opening up in the market. These universities are recruiting course designers, app designers, and other IT staff to increase the volume and variety of online courses by incorporating new learning models. Therefore, universities and colleges are expected to invest in collaborative software and solutions over the next four years.

classroom collaboration management systems forecast as per geographies

North America
Europe
APAC
ROW

North America emerged as the largest region for classroom collaboration management systems with over 50% of the overall market shares in 2014. There is greater emphasis on e-learning in the region along with the development of various new forms of education such as blended learning in schools and colleges that accelerate the adoption of classroom management systems. North America was followed by Europe and APAC respectively. APAC constitutes many emerging markets with high growth potential in the education sector.

Classroom collaboration management systems market value for vendors

Dell    
HP     
Stoneware

Market vendors are keen to leverage the opportunity presented by the rise in virtual schools during the forecast period. It is predicted to re-define the classroom learning experience with the aid of different types of content such as video, audio, and simulation while facilitating real-time interactive sessions with fellow learners and trainers from different regions under one platform.

Key questions answered in the report

What are the key factors driving the classroom collaboration management systems market?
What are the key market trends impacting the growth of the connected classroom collaboration management systems market?
What are the various opportunities and threats faced by the vendors in the classroom collaboration management systems market?
Trending factors influencing the market shares for the classroom collaboration management systems market?
Market shares for North America, Europe, APAC, and ROW?
Key outcome of the five forces analysis on the classroom collaboration management systems market?
Growth forecast of the classroom collaboration management systems market?

Technavio also offers customization on reports based on specific client requirement.

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