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 measure presents the high school 4-Year graduation rate for African American Students in Iowa for the most current graduating class available.

In 2022, around 91.8 percent of women had graduated high school or had obtained a higher educational degree in the United States. This is an increase from 1960, when 42.5 percent of women in the U.S. had graduated from high school or above.

This map shows high school graduations within the US by graduation rate and number of students expected to graduate. This is shown by US counties from the 2018 County Health Rankings. The national average of students who graduate high school for the 2018-2019 academic year was 88%, according to U.S. News and World Report.The popup shows the graduation rate of each county in comparison to the national rate. For example, my home county of Logan, Colorado has a graduation rate of 75% as compared to the national average of 88%.The data comes from the County Health Rankings 2018 layer. The report is from a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute.

This statistic shows the higher education graduation rate in the United States from the 2000/01 academic year to 2016/17. The graduation rate includes all those who completed their higher education certificate or degree within 150% of normal completion time. The graduation rate has remained relatively constant over time and most recently in 2017/18 the graduation rate stood at 50 percent.

Latest available data and trends in graduation and dropout outcomes by school.

Metric scores are not reported for n-sizes under 10. Per OSSE's policy, secondary suppression is applied to all student groups when a complementary group has an n-size under 10 or is top/bottom suppressed to prevent the calculation of suppressed data.

Data Source: DC Office of the State Superintendent of Education

Why This Matters

Graduating from high school is a critical step in advancing along educational and professional paths. Many careers and almost all colleges require a high school diploma or GED.

Educational attainment is strongly linked with socioeconomic and health outcomes. Americans who graduate high school tend to have higher incomes than those who do not. High school graduates also tend to live longer, healthier, and happier lives.

Black, Hispanic, and Native American students in the U.S. have lower graduation rates, on average, than white students. Segregation and historical disinvestment in communities of color play a significant role in these disparities. Poverty and limited educational resources act as barriers to graduation.

The District Response

The Office of the State Superintendent of Education (OSSE)’s Reimagining High School Graduation Requirements initiative aims to identify and implement new high school graduation requirements that incorporate outcome measures and support innovative approaches to preparing young people for life after graduation.

The District of Columbia Public Schools offers a number of supports to both proactively aid students in graduating and assist those at risk of not graduating.

Since 2014, those who pass the GED receive a State High School Diploma instead of a GED credential. This more accurately represents the dedication, hard work, and demonstration of skill it takes for residents to successfully complete this alternative path to a high school diploma.

Excel version of report to City Council required per LL 147

In the 2019-20 school year, West Virginia had the highest graduation rate for Hispanic students in the United States, at 93 percent. Florida closely followed, with a graduation rate of 89.7 percent for Hispanic students.

This dataset shows the percentage of students who graduated from Massachusetts public schools with a regular high school diploma within 4 or 5 years. It is a long file that contains multiple rows for each school and district, with rows for different years and different student groups.

Note: Data is currently available at the school level only, as well as the state overall. For district-level graduation rates, please see the High School Graduation Rates dataset, or the High School Graduation Rates report on our DESE Profiles site.

Economically Disadvantaged was used 2015-2021. Low Income was used prior to 2015, and a different version of Low Income has been used since 2022. Please see the DESE Researcher's Guide for more information. 

For more data about student experiences and outcomes in high school and beyond, please see the main DART: Success After High School dataset and dashboard.

The New York State calculation method was first adopted for the Cohort of 2001 (Class 2005). The cohort consists of al students who first entered 9th grade in a given school year (e.g., the cohort of 2006 entered 9th grade in 2006-2007 school year). Graduates are defined as those students earning either a local or regents diploma and exclude those earning either a special education (IEP) diploma for GED. In order to comply with FERPA regulations on public reporting of education outcomes, rows with a cohort of 20 or fewer students are suppressed. Due to small number of students identified as Native American or Multi-Racial these ethnicities are not reported on the Ethnicity tab, however these students are included in the counts on all other tabs.

Institute Graduation Rate Prediction Dataset is prepared from IPEDS[1] dataset by following proposed framework[2] by** Ms. Mala H. Mehta, Dr. N.C.Chauhan and Dr.Anu Gokhle** (Research Paper presented in ET2ECN-2021 International Conference). The paper will soon be published in Springer-Scopus Indexed publication.

The dataset consists of total 143 features and 11319 records of 8 student batches (from 2004 to 2011). How many students have successfully graduated within stipulated time period? Can we do the prediction of that? If low graduation rates are known in advance, institute can take prior steps to avoid low graduation rates.

Cite this dataset as - Ms. Mala Mehta Bhatt, Dr. N.C.Chauhan, & Dr. Anu Gokhale. (2021). Institute Graduation Rate Prediction Dataset [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/2914166

1 Objective 1.1 Context Education data mining (EDM) is a field related to generate useful,novel and actionable knowledge by applying miniing/ML algorithms on academic data. Knowledge generated could give unexpected benefit to education domain stakeholders.

EDM also known sometimes as Learning Analytics has various branches to work. Two Major branches are: 1. Student Performance related study 2. Institute Performance related study. Much research is done on the first aspect, however, the second aspect is not touched much.

This dataset is designed with aim of effectively predicting Institute Graduation Rates for Higher education institutions.

2 IPEDS [1] Dataset The National Centre for Education Statistics (NCES) is the primary federal entity for collecting, analyzing, and reporting data related to education in the United States and other nations.

The Integrated Postsecondary Education Data System (IPEDS) surveys approximately 7,500 postsecondary institutions, including universities and colleges, as well as institutions offering technical and vocational education beyond the high school level. IPEDS, which began in 1986, replaced the Higher Education General Information Survey (HEGIS).

IPEDS consists of nine integrated components that obtain information on who provides postsecondary education (institutions), who participates in it and completes it (students), what programs are offered and what programs are completed, and both the human and financial resources involved in the provision of institutionally-based postsecondary education.

3 Approach 3.1 Feature Selection IPEDS dataset is a big dataset consisting of many tables and many years' databases. A framework[2] was designed to extract IGR related features and data. By following this framework, final file was created. 143 Features were selected out of which one is response variable. 3.1.1 Response Variable GBA4RTT - Graduation rate - bachelor's degree within 4 years 3.1.2 Predictor Variables 142 Predictor/Independent features are identified. (meta data is uploaded.)

3.2 Handling Missing Values Missing values are handled by applying statistical measure mean on each feature and the replacing missing values by them. 3.3 Splitting into Train-Validation-Test sets Data is split into training and testing set with 80-20% ratio. 3.4 Modeling AS Response variable considered in the study is a continuous variable. Regression Models are used to find the minimum error in prediction. 4 models are considered: Multiple linear regression, Support vector regression, Decision tree regression, XGBoost regression 4 Execution Execution process consists of below mentioned step by step procedure: 1. Preprocessing of data, 2. Splitting the data in training and testing sets, 3. Applying the models, 4. Measuring MSE,RMSE,R2, Adjusted R2 and program's running time. 5 Conclusion Mean Squared Error measured is considered here for comparison among 4 models. Minimum MSE is received in XGBoost regression algorithm followed by support vector regression, decision tree regression and multiple linear regression algorithms. Future Work Researchers could use the dataset for further analysis with different models, different dimensionality reduction techniques and education domain analysis. References [1] NCES, “National Center for Education Statistics”, Available at: https://nces.ed.gov/ipeds/use-the-data, Accessed at 2021. [2] "A Dataset preparation framework for education data mining" presented in 4th international conference on Emerging technology trends in electronics, communication and networking (ET2ECN-2021), SVNIT, Surat. Acknowledgements Thanks to NCES [1], for providing such huge open repository related to education available freely. I acknowledge all efforts put by Dr. N.C.Chauhan and Dr. Anu Gokhale in this work. Special Thanks to Vinay Bhatt, who found IPEDS repository for me, because of that only I was able to prepare this dataset.

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."

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Graph and download economic data for High School Graduate or Higher for Ohio (GCT1501OH) from 2006 to 2024 about secondary schooling, secondary, educational attainment, 25 years +, OH, education, and USA.

This dataset tracks annual graduation rate from 2013 to 2023 for American High School vs. California and Fremont Unified School District

USA College Dataset

Here is the 777 Observations with 18 variables

Content

A complete csv file with columns like private , graduation rates , Student Faculty ratio,etc of more than 500 colleges/universities.

• Private A factor with levels No and Yes indicating private or public university
• Apps Number of applications received
• Accept Number of applications accepted
• Enroll Number of new students enrolled
• Top10perc Pct. new students from top 10% of H.S. class
• Top25perc Pct. new students from top 25% of H.S. class
• F.Undergrad Number of fulltime undergraduates
• P.Undergrad Number of parttime undergraduates
• Outstate Out-of-state tuition
• Room.Board Room and board costs
• Books Estimated book costs
• Personal Estimated personal spending
• PhD Pct. of faculty with Ph.D.’s
• Terminal Pct. of faculty with terminal degree
• S.F.Ratio Student/faculty ratio
• perc.alumni Pct. alumni who donate
• Expend Instructional expenditure per student
• Grad.Rate Graduation rate

Graduation Outcomes - Cohorts of 2001 through 2006 (Classes of 2005 through 2010) ¶¶•The New York State calculation method was first adopted for the Cohort of 2001 (Class of 2005). The cohort consists of all students who first entered 9th grade in a given school year (e.g., the Cohort of 2006 entered 9th grade in the 2006-2007 school year). Graduates are defined as those students earning either a Local or Regents diploma and exclude those earning either a special education (IEP) diploma or GED. For the most recent cohort, graduation rates as of both June and August (including summer graduates) are reported. ¶¶•Records with cohorts of 20 students or less are suppressed. August outcomes are only reported for the most recent cohort. ¶¶•August outcomes include all June and August graduates. In school-level reporting, students who were in a school for less than 5 months are not included in the school’s cohort, but are included in citywide totals. ¶¶•School level results are not presented for District 79 schools, but their outcomes are included in citywide totals. ¶¶•Schools are listed by their current DBN's.

College Completion and Efficiency Measures for US Institutions

Rates, Awards, Expenditures, and Outcomes

By Jonathan Ortiz [source]

About this dataset

This dataset provides valuable insights into college completion rates and efficiency measures for institutions across the United States. Using data from the National Center for Education Statistics’ Integrated Postsecondary Education System (IPEDS) and the Voluntary System of Accountability’s Student Success and Progress rate, this dataset allows for a detailed look at graduation rates among groups of first-time, full-time degree-seeking students at the undergraduate level.

Gain meaningful insights into individual graduation rates by examining data points like race, gender, control (public versus private) and length of study. Determine how well your favorite institution stands up to its peers in terms of awards per 100 full-time undergraduate students as well as expenditure categories that are educational in nature or indirectly associated with educational efforts. Evaluate median estimated SAT scores & average student aid to gain an understanding if admissions standards have an effect on graduating numbers along with financial situations that can be improved through aid sources available to students. Finally, seek out trends in endowment figures whilst assessing the professor faculty size relative to student enrollment size – a great insight into whether institutions are motivated towards maximizing their students' chance of success through providing adequate resources!

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How to use the dataset

Welcome to the College Completion and Efficiency Measures dataset! This dataset contains graduation rates, efficiency measures, race & ethnicity information, SAT/ACT scores, average student aid awarded, endowment values and faculty headcounts for college institutions in the United States.

In this guide we will explain how to use this dataset and how to analyze its data.

• Understand the Columns: Read through the above description of each column carefully. Take note of what type of data is stored in each column (string or number) and understand which columns are important for your desired analysis. Use the list above as a reference if needed.
• Filter Your Results: Narrow down your results by selecting filters relevant to your desired analysis. For example you can filter by state name, gender or race by typing their name in them respective box provided at Kaggle’s Data tab (example given below). You can also filter multiple parameters with OR or AND conditions for more detailed results (example given below).
  OR Filters: State Name= ‘California’ OR ‘Oregon’ OR Filters: Level= 'Four Year' AND Gender='Male'.
  3 Analyze Your Results: Once you have narrowed down on a specific set of records using filters, you can explore various metrics to measure performance such as Graduation Rate within 150%, Awards per 100 full-time undergraduate students Program Expenses per Student etc., Look up scatter plots between metrics like Endowment Value Vs SAT Scores per incoming Freshman Class or Spending budget vs Graduation rate within 150%. Based on these observations identify areas where infrastructural investments may yield improvement in instutional performance over time

Research Ideas

• Finding correlations between graduation rates and factors such as control, gender, race and level of institution to identify potential causes of inequity or areas that require further investigation.
• Analyzing differences in completion rates among public and private institutions to measure the effectiveness of government funding in improving completion rates.
• Using efficiency measures such as awards per 100 full-time undergraduates and expenditure categories to evaluate how financial resources are used within higher education institutions to maximize student success

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: cc_state_sector_grads.csv | Column name | Description | |:------------------...

Graduation Outcomes - Cohorts of 2001 through 2006 (Classes of 2005 through 2010) ¶¶•The New York State calculation method was first adopted for the Cohort of 2001 (Class of 2005). The cohort consists of all students who first entered 9th grade in a given school year (e.g., the Cohort of 2006 entered 9th grade in the 2006-2007 school year). Graduates are defined as those students earning either a Local or Regents diploma and exclude those earning either a special education (IEP) diploma or GED. For the most recent cohort, graduation rates as of both June and August (including summer graduates) are reported. ¶¶•Records with cohorts of 20 students or less are suppressed. August outcomes are only reported for the most recent cohort. ¶¶•August outcomes include all June and August graduates. In school-level reporting, students who were in a school for less than 5 months are not included in the school’s cohort, but are included in citywide totals. ¶¶•School level results are not presented for District 79 schools, but their outcomes are included in citywide totals. ¶¶•Schools are listed by their current DBN's.