In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

College Completion Dataset

Graduation Rates, Race, Efficiency Measures and More

By Jonathan Ortiz [source]

About this dataset

This College Completion dataset provides an invaluable insight into the success and progress of college students in the United States. It contains graduation rates, race and other data to offer a comprehensive view of college completion in America. The data is sourced from two primary sources – the National Center for Education Statistics (NCES)’ Integrated Postsecondary Education System (IPEDS) and Voluntary System of Accountability’s Student Success and Progress rate.

At four-year institutions, the graduation figures come from IPEDS for first-time, full-time degree seeking students at the undergraduate level, who entered college six years earlier at four-year institutions or three years earlier at two-year institutions. Furthermore, colleges report how many students completed their program within 100 percent and 150 percent of normal time which corresponds with graduation within four years or six year respectively. Students reported as being of two or more races are included in totals but not shown separately

When analyzing race and ethnicity data NCES have classified student demographics since 2009 into seven categories; White non-Hispanic; Black non Hispanic; American Indian/ Alaskan native ; Asian/ Pacific Islander ; Unknown race or ethnicity ; Non resident with two new categorize Native Hawaiian or Other Pacific Islander combined with Asian plus students belonging to several races. Also worth noting is that different classifications for graduate data stemming from 2008 could be due to variations in time frame examined & groupings used by particular colleges – those who can’t be identified from National Student Clearinghouse records won’t be subjected to penalty by these locations .

When it comes down to efficiency measures parameters like “Awards per 100 Full Time Undergraduate Students which includes all undergraduate completions reported by a particular institution including associate degrees & certificates less than 4 year programme will assist us here while we also take into consideration measures like expenditure categories , Pell grant percentage , endowment values , average student aid amounts & full time faculty members contributing outstandingly towards instructional research / public service initiatives .

When trying to quantify outcomes back up Median Estimated SAT score metric helps us when it is derived either on 25th percentile basis / 75th percentile basis with all these factors further qualified by identifying required criteria meeting 90% threshold when incoming students are considered for relevance . Last but not least , Average Student Aid equalizes amount granted by institution dividing same over total sum received against what was allotted that particular year .

All this analysis gives an opportunity get a holistic overview about performance , potential deficits &

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How to use the dataset

This dataset contains data on student success, graduation rates, race and gender demographics, an efficiency measure to compare colleges across states and more. It is a great source of information to help you better understand college completion and student success in the United States.

In this guide we’ll explain how to use the data so that you can find out the best colleges for students with certain characteristics or focus on your target completion rate. We’ll also provide some useful tips for getting the most out of this dataset when seeking guidance on which institutions offer the highest graduation rates or have a good reputation for success in terms of completing programs within normal timeframes.

Before getting into specifics about interpreting this dataset, it is important that you understand that each row represents information about a particular institution – such as its state affiliation, level (two-year vs four-year), control (public vs private), name and website. Each column contains various demographic information such as rate of awarding degrees compared to other institutions in its sector; race/ethnicity Makeup; full-time faculty percentage; median SAT score among first-time students; awards/grants comparison versus national average/state average - all applicable depending on institution location — and more!

When using this dataset, our suggestion is that you begin by forming a hypothesis or research question concerning student completion at a given school based upon observable characteristics like financ...

This dataset shows broad performance metrics for education for Maryland as a whole, from School Years 2005/2006 to 2013/2014. Data are provided by the Maryland State Department of Education (MSDE) and were originally submitted to the Governor's Office.

Students’ retention rates (RR), students’ progression rates (PR), and students’ graduation rates (GR) are statistical figures commonly used in higher education to monitor the performance of higher education institutions (HEI), academic programs (courses), or their students. Due to the variability in defining these quantitative quality metrics, their values should be interpreted carefully with a clear understanding of how they were computed to avoid misleading judgments and unfair comparisons. In the current study, we develop clearly-defined benchmarking retention, progression, and graduation rates by curating and processing (with the aid of descriptive statistics, nonlinear extrapolation, numerical relaxation, and regression analysis) well-documented public longitudinal raw data about undergraduate higher institutions over four recent consecutive cohorts. We particularly account for the variability in the desired time window over which some rates are reported. We also count for the presence of a pre-college bridging year of study (a foundational or preparatory postsecondary year) offered before the formal college program starts. Based on our outcomes, the overall bachelor’s degree benchmarking retention rate after one year of entry is 75.93%, the overall benchmarking progression rate after one year of entry is 75.22%, and the overall benchmarking graduation rate within 150% of the normal degree duration is 64.2%.

In which post secondary sectors (private/public, 2 Year / CTC / 4 Year, in-state/out of state) do high school graduates enroll in the first year after graduation?

See notice below about this dataset

This dataset provides the number of graduates who enrolled in each type of postsecondary education per district.

Wage records are obtained from the Massachusetts Department of Unemployment Assistance (DUA) using a secure, anonymized matching process with limitations. For details on the process and suppression rules, please visit the Employment and Earnings of High School Graduates dashboard.

This dataset is one of three containing the same data that is also published in the Employment and Earnings of High School Graduates dashboard: Average Earnings by Student Group Average Earnings by Industry College and Career Outcomes

List of Outcomes

• Total Postsecondary Enrollment
• In-State Public 2-Year
• In-State Public 4-Year
• In-State Private
• Out-of-State
• Total Employed
• Total Missing

The data link between high school graduates and future earnings makes it possible to follow students beyond high school and college into the workforce, enabling long-term evaluation of educational programs using workforce outcomes.

While DESE has published these data in the past, as of June 2025 we are temporarily pausing updates due to an issue conducting the link that was brought to our attention in 2023 by a team of researchers. The issue impacts the earnings information for students who never attended a postsecondary institution or who only attended private or out-of-state colleges or universities, beginning with the 2017 high school graduation cohort, with growing impact in each successive high school graduation cohort.

The issue does not impact the earnings information for students who attended a Massachusetts public institution of higher education, and earnings data for those students will continue to be updated.

Once a solution is found, the past cohorts of data with low match rates will be updated. DESE and partner agencies are exploring linking strategies to maximize the utility of the information.

More detailed information can be found in the attached memo provided by the research team from the Annenberg Institute. We thank them for calling this issue to our attention.

We publish a wide range of tables and charts about graduates from higher education.

Data is available for 2017/18

What percent of high school graduates enrolled in post secondary institutions in the first year after graduation?

Last update: April 2013 Was added to StatsWales: April 2013 Source: Higher Education Statistics Agency (HESA) Contact: post16ed.stats@wales.gsi.gov.uk The information in this table is taken from Performance Indicators in Higher Education in the UK available on the HESA web-site at www.hesa.ac.uk/pi. A Guide to Performance Indicators in Higher Education is also available at this web-site. The indicators are designed to provide reliable information on the nature and performance of the higher education sector in the UK. The performance indicators broadly cover access to higher education, non-continuation rates and outcomes. Indicators relate to higher education institutions in the individual countries of the UK. The Performance Indicators Steering Group (PISG) has led the development of these indicators. Members are drawn from the four higher education funding bodies for England, Scotland, Wales and Northern Ireland (HEFCE, SHEFC, HEFCW, DEL); the Department for Education and Skills and other government departments, the Higher Education Statistics Agency, and universities and colleges through their representative bodies (Universities UK and SCOP) Since 2002/03 HESA has published the Performance Indicators on behalf of the Higher Education Funding Council for England (HEFCE) who published them previously. A number of changes were introduced for the 2002/03 publication; further details can be found at www.hesa.ac.uk/pi . The access indicators relate to students starting in 2004/05; the indicators of non-continuation (students who do not continue after their first year) and of non-completion (students who drop out and do not resume later or transfer elsewhere) relate to the cohort starting in 2003/04. The disability indicator covers all students, not just entrants, on undergraduate programmes in 2004/05. WIDENING ACCESS: PERCENTAGE OF YOUNG FIRST DEGREE ENTRANTS FROM STATE SCHOOLS OR COLLEGES. School type is taken from previous institution attended. All schools or colleges that are not denoted ‘independent’ are assumed to be state schools. This means that students from sixth-form or further education colleges, for example, are included as being from state schools.

Higher Education Services Market Outlook

In 2023, the global higher education services market size was valued at approximately $16 billion, with a projected growth to $30 billion by 2032, reflecting a compound annual growth rate (CAGR) of 7%. This substantial growth can be attributed to the increasing demand for advanced educational technologies, growing student enrollment in higher educational institutions worldwide, and the rising need for institutions to offer diversified and flexible learning platforms. The integration of technology in education, particularly with the rise of digital learning and online education models, is driving this market's expansion. As more institutions recognize the importance of adapting to new educational technologies and methodologies, the higher education services market is poised for continued growth in the coming years.

The growth factors for the higher education services market are multifaceted. First, the continuous evolution and integration of technology in education play a prominent role. Institutions are increasingly adopting advanced technologies such as artificial intelligence, machine learning, and data analytics to improve educational outcomes and operational efficiency. These technologies are providing educators with insights into student performance, enabling personalized learning experiences, and streamlining administrative processes. Additionally, the proliferation of online learning platforms has made education more accessible to a broader population, allowing students from diverse backgrounds to pursue higher education at their convenience. The demand for flexible learning options is further driving institutions to invest in comprehensive higher education services.

Another significant growth factor is the increasing global student population. As the world becomes more interconnected, the value of higher education as a pathway to better career opportunities and socio-economic mobility continues to rise. Emerging economies are investing heavily in expanding their higher education infrastructure to cater to the growing number of college-aged individuals. This surge in student numbers necessitates the development of robust educational services that can accommodate and support a larger student body. Furthermore, government initiatives and policies aimed at enhancing the quality of education and promoting lifelong learning are providing additional impetus for the expansion of the higher education services market.

Moreover, the shift towards competency-based learning and the emphasis on skill development are contributing to market growth. Employers are increasingly seeking graduates who possess not only theoretical knowledge but also practical skills that are applicable in the workforce. This has led to a greater focus on vocational training, internships, and partnerships between educational institutions and industries. Higher education services are evolving to facilitate this transition, offering tailored programs that align with industry needs. The integration of real-world experience into educational curricula is becoming a key differentiator for institutions, driving demand for specialized services that support these initiatives.

Cloud Computing in Education Sector is revolutionizing the way educational institutions operate, offering unprecedented flexibility and scalability. As schools and universities increasingly adopt cloud-based solutions, they are able to streamline administrative processes, enhance collaboration among students and faculty, and provide access to a wealth of educational resources from anywhere in the world. This shift not only reduces the need for costly on-premises infrastructure but also enables institutions to quickly adapt to changing educational needs and technologies. The integration of cloud computing in education is facilitating the development of personalized learning environments, where students can access tailored content and resources that suit their individual learning styles and paces. As the demand for remote and hybrid learning models grows, cloud computing is playing a critical role in supporting these innovative educational approaches, ensuring that students have the tools they need to succeed in a digital age.

Regionally, the higher education services market is witnessing varied dynamics. In North America, the presence of advanced infrastructure and a strong emphasis on educational quality are driving market growth. The Asia Pacific region is experiencing rapid expansion due to the increasing student population, government i

The University of Washington - Beyond High School (UW-BHS) project surveyed students in Washington State to examine factors impacting educational attainment and the transition to adulthood among high school seniors. The project began in 1999 in an effort to assess the impact of I-200 (the referendum that ended Affirmative Action) on minority enrollment in higher education in Washington. The research objectives of the project were: (1) to describe and explain differences in the transition from high school to college by race and ethnicity, socioeconomic origins, and other characteristics, (2) to evaluate the impact of the Washington State Achievers Program, and (3) to explore the implications of multiple race and ethnic identities. Following a successful pilot survey in the spring of 2000, the project eventually included baseline and one-year follow-up surveys (conducted in 2002, 2003, 2004, and 2005) of almost 10,000 high school seniors in five cohorts across several Washington school districts. The high school senior surveys included questions that explored students' educational aspirations and future career plans, as well as questions on family background, home life, perceptions of school and home environments, self-esteem, and participation in school related and non-school related activities. To supplement the 2000, 2002, and 2003 student surveys, parents of high school seniors were also queried to determine their expectations and aspirations for their child's education, as well as their own educational backgrounds and fields of employment. Parents were also asked to report any financial measures undertaken to prepare for their child's continued education, and whether the household received any form of financial assistance. In 2010, a ten-year follow-up with the 2000 senior cohort was conducted to assess educational, career, and familial outcomes. The ten year follow-up surveys collected information on educational attainment, early employment experiences, family and partnership, civic engagement, and health status. The baseline, parent, and follow-up surveys also collected detailed demographic information, including age, sex, ethnicity, language, religion, education level, employment, income, marital status, and parental status.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

IntroductionCommunity Engaged Learning (CEL) is recognized for its positive impact on student development in higher education. This meta-analysis examined the effects of CEL on academic, personal, social, and citizenship outcomes among college students.MethodsStudies were identified through PsycINFO, PsycArticles, and ERIC, and were included if they met the following criteria: peer-reviewed English-language publications from 2017 to 2024, alignment with widely accepted definitions of CEL, inclusion of a control group, and sufficient data to calculate effect sizes. Random-effects models were used to estimate Hedges's g, a standardized measure of effect size, for each outcome domain.ResultsOur results showed that CEL had a statistically significant, small to medium effect on academic outcomes (Hedges's g = 0.344, 95% CI [0.190, 0.497], p < 0.001) and social outcomes (Hedges's g = 0.371, 95% CI [0.167, 0.575], p < 0.001). The effect on citizenship outcomes was small but significant (Hedges's g = 0.220, 95% CI [0.096, 0.344], p = 0.001). For personal outcomes, the effect was moderate (Hedges's g = 0.694, 95% CI [−0.089, 1.477]) but not statistically significant (p = 0.082). The substantial variability observed across studies suggests that differences in CEL implementation, program focus, and student populations may influence outcomes.ConclusionOverall, our findings highlight CEL as an impactful pedagogy that contributes to academic success, personal growth, and civic engagement. Further research may explore the long-term impacts of CEL and identify specific program components that enhance its effectiveness.

Last update: April 2013 Was added to StatsWales: April 2013 Source: Higher Education Statistics Agency (HESA) Contact: post16ed.stats@wales.gsi.gov.uk The information in this table is taken from Performance Indicators in Higher Education in the UK available on the HESA web-site at www.hesa.ac.uk/pi. A Guide to Performance Indicators in Higher Education is also available at this web-site. The indicators are designed to provide reliable information on the nature and performance of the higher education sector in the UK. The performance indicators broadly cover access to higher education, non-continuation rates and outcomes. Indicators relate to higher education institutions in the individual countries of the UK. The Performance Indicators Steering Group (PISG) has led the development of these indicators. Members are drawn from the four higher education funding bodies for England, Scotland, Wales and Northern Ireland (HEFCE, SHEFC, HEFCW, DEL); the Department for Education and Skills and other government departments, the Higher Education Statistics Agency, and universities and colleges through their representative bodies (Universities UK and SCOP) Since 2002/03 HESA has published the Performance Indicators on behalf of the Higher Education Funding Council for England (HEFCE) who published them previously. A number of changes were introduced for the 2002/03 publication; further details can be found at www.hesa.ac.uk/pi . The access indicators relate to students starting in 2004/05; the indicators of non-continuation (students who do not continue after their first year) and of non-completion (students who drop out and do not resume later or transfer elsewhere) relate to the cohort starting in 2003/04. The disability indicator covers all students, not just entrants, on undergraduate programmes in 2004/05. WIDENING ACCESS: PERCENTAGE OF YOUNG FIRST DEGREE ENTRANTS FROM STATE SCHOOLS OR COLLEGES. School type is taken from previous institution attended. All schools or colleges that are not denoted ‘independent’ are assumed to be state schools. This means that students from sixth-form or further education colleges, for example, are included as being from state schools.

Last update: April 2013 Was added to StatsWales: April 2013 Source: Higher Education Statistics Agency (HESA) Contact: post16ed.stats@wales.gsi.gov.uk The information in this table is taken from Performance Indicators in Higher Education in the UK available on the HESA web-site at www.hesa.ac.uk/pi. A Guide to Performance Indicators in Higher Education is also available at this web-site. The indicators are designed to provide reliable information on the nature and performance of the higher education sector in the UK. The performance indicators broadly cover access to higher education, non-continuation rates and outcomes. Indicators relate to higher education institutions in the individual countries of the UK. The Performance Indicators Steering Group (PISG) has led the development of these indicators. Members are drawn from the four higher education funding bodies for England, Scotland, Wales and Northern Ireland (HEFCE, SHEFC, HEFCW, DEL); the Department for Education and Skills and other government departments, the Higher Education Statistics Agency, and universities and colleges through their representative bodies (Universities UK and SCOP) Since 2002/03 HESA has published the Performance Indicators on behalf of the Higher Education Funding Council for England (HEFCE) who published them previously. A number of changes were introduced for the 2002/03 publication; further details can be found at www.hesa.ac.uk/pi . The access indicators relate to students starting in 2004/05; the indicators of non-continuation (students who do not continue after their first year) and of non-completion (students who drop out and do not resume later or transfer elsewhere) relate to the cohort starting in 2003/04. The disability indicator covers all students, not just entrants, on undergraduate programmes in 2004/05. WIDENING ACCESS: PERCENTAGE OF YOUNG FIRST DEGREE ENTRANTS FROM STATE SCHOOLS OR COLLEGES. School type is taken from previous institution attended. All schools or colleges that are not denoted ‘independent’ are assumed to be state schools. This means that students from sixth-form or further education colleges, for example, are included as being from state schools.

In which post secondary institutions do graduates of WA public high schools enroll in the first year after HS graduation?

Analysis of ‘High School Graduate Outcomes - First Year Enrollment’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c25046bc-6719-4373-82e7-11698700fa04 on 28 January 2022.

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

What percent of high school graduates enrolled in post secondary institutions in the first year after graduation?

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