About NTPSThe National Teacher and Principal Survey (NTPS) is a system of related questionnaires that provide descriptive data on the context of elementary and secondary education while also giving policymakers a variety of statistics on the condition of education in the United States.The NTPS is a redesign of the Schools and Staffing Survey (SASS), which the National Center for Education Statistics (NCES) conducted from 1987 to 2011. The design of the NTPS is a product of three key goals coming out of the SASS program: flexibility, timeliness, and integration with other Department of Education collections. The NTPS collects data on core topics including teacher and principal preparation, classes taught, school characteristics, and demographics of the teacher and principal labor force every two to three years. In addition, each administration of NTPS contains rotating modules on important education topics such as: professional development, working conditions, and evaluation. This approach allows policy makers and researchers to assess trends on both stable and dynamic topics.Data OrganizationEach table has an associated excel and excel SE file, which are grouped together in a folder in the dataset (one folder per table). The folders are named based on the excel file names, as they were when downloaded from the National Center for Education Statistics (NCES) website.In the NTPS folder, there is a catalog csv that provides a crosswalk between the folder names and the table titles.The documentation folder contains (1) codebooks for NTPS generated in NCES datalabs, (2) questionnaires for NTPS downloaded from the study website and (3) reports related to NTPS found in the NCES resource library

This Private Schools feature dataset is composed of private elementary and secondary education facilities in the United States as defined by the Private School Survey (PSS, https://nces.ed.gov/surveys/pss/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2017-2018 school year. This includes all prekindergarten through 12th grade schools as tracked by the PSS. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 2675 new records, modifications to the spatial location and/or attribution of 19836 records, the removal of 254 records no longer applicable. Additionally, 10,870 records were removed that previously had a STATUS value of 2 (Unknown; not represented in the most recent PSS data) and duplicate records identified by ORNL.

A nationally representative sample of eighth-graders were first surveyed in the spring of 1988. A sample of these respondents were then resurveyed through four follow-ups in 1990, 1992, 1994, and 2000. On the questionnaire, students reported on a range of topics including: school, work, and home experiences; educational resources and support; the role in education of their parents and peers; neighborhood characteristics; educational and occupational aspirations; and other student perceptions. Additional topics included self-reports on smoking, alcohol and drug use and extracurricular activities. For the three in-school waves of data collection (when most were eighth-graders, sophomores, or seniors), achievement tests in reading, social studies, mathematics and science were administered in addition to the student questionnaire. To further enrich the data, students' teachers, parents, and school administrators were also surveyed. Coursework and grades from students' high school and postsecondary transcripts are also available in the restricted use dataset - although some composite variables have been made available in the public use file. The third follow-up took place in 1994, when most sample members had completed high school. The primary goals of the 1994 round were: 1) to provide data for trend comparisons with NLS-72 and HS&B; 2) to address issues of employment and postsecondary access and choice; and 3) to ascertain how many dropouts have returned to school and by what route. (NCES 2/13/2015)

About SASSThe Schools and Staffing Survey (SASS) was conducted by NCES seven times between 1987 through 2011. SASS was an integrated study public and private school districts, schools, principals, and teachers designed to provide descriptive data on the context of elementary and secondary education. SASS covered a wide range of topics from teacher demand, teacher and principal characteristics, general conditions in schools, principals' and teachers' perceptions of school climate and problems in their schools, teacher compensation, district hiring and retention practices, to basic characteristics of the student population. After 2010–11, NCES redesigned SASS and named it the National Teacher and Principal Survey (NTPS) to reflect the redesigned study's focus on the teacher and principal labor market and on the state of K-12 school staff. NCES first conducted NTPS in 2015–16.Data OrganizationEach table has an associated excel and excel SE file, which are grouped together in a folder in the dataset (one folder per table). The folders are named based on the excel file names, as they were when downloaded from the National Center for Education Statistics (NCES) website.In the SASS folder, there is a catalog csv that provides a crosswalk between the folder names and the table titles.The documentation folder contains (1) codebooks for SASS generated in NCES datalabs, (2) questionnaires for SASS downloaded from the study website and (3) documentation and user manuals related to SASS found in the NCES resource library.

About TFSThis is a study of public and private school teachers in elementary and secondary schools and is part of the NTPS study, which collects information from U.S. elementary and secondary schools and their staff. Use this study to learn about teacher retention and attrition rates, characteristics of teachers who stayed in the teaching profession and those who changed professions or retired, activity and occupational information for those who left the position of a K-12 teacher, reasons for moving to a new school or leaving the K-12 teaching profession, and job satisfaction.Data OrganizationEach table has an associated excel and excel SE file, which are grouped together in a folder in the dataset (one folder per table). The folders are named based on the excel file names, as they were when downloaded from the National Center for Education Statistics (NCES) website.In the TFS folder, there is a catalog csv that provides a crosswalk between the folder names and the table titles.The documentation folder contains (1) codebooks for TFS generated in NCES datalabs, (2) questionnaires for TFS downloaded from the study website and (3) reports related to TFS found in the NCES resource library.

This web map provides and in-depth look at school districts within the United States. Clicking on a school district in the map will reveal different statistics about each district in the pop-up. The statistics presented in this map are approximations based on summarizing American Community Survey(ACS) data using tract centroids. They may differ from published statistics by school districts found on data.census.gov. A few things you will learn from this map:How many public and private schools fall within a district?Socioeconomic factors about the Census Tracts which fall within the district:School enrollment for grades Kindergarten through 12thDisconnected children in the districtChildren living below the poverty level Children with no internet at home Children without a working parentRace/ethnicity breakdown of population under the age of 19 in the districtFor more information about the data sources:This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases estimates, so values in the map always reflect the newest data available.Current School Districts Layer:The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, and unified school district boundaries clipped to the U.S. shoreline. School districts are single-purpose administrative units designed by state and local officials to organize and provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to support educational research and program administration, and the boundaries are essential for constructing district-level estimates of the number of children in poverty.The Census Bureau’s School District Boundary Review program (SDRP) (https://www.census.gov/programs-surveys/sdrp.html) obtains the boundaries, names, and grade ranges from state officials, and integrates these updates into Census TIGER. Census TIGER boundaries include legal maritime buffers for coastal areas by default, but the NCES composite file removes these buffers to facilitate broader use and cleaner cartographic representation. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop the composite school district files. The inputs for this data layer were developed from Census TIGER/Line and represent the most current boundaries available. For more information about NCES school district boundary data, see https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries.Public Schools Layer:This Public Schools feature dataset is composed of all Public elementary and secondary education facilities in the United States as defined by the Common Core of Data (CCD, https://nces.ed.gov/ccd/ ), National Center for Education Statistics (NCES, https://nces.ed.gov ), US Department of Education for the 2017-2018 school year. This includes all Kindergarten through 12th grade schools as tracked by the Common Core of Data. Included in this dataset are military schools in US territories and referenced in the city field with an APO or FPO address. DOD schools represented in the NCES data that are outside of the United States or US territories have been omitted. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 3065 new records, modifications to the spatial location and/or attribution of 99,287 records, and removal of 2996 records not present in the NCES CCD data.Private Schools Layer:This Private Schools feature dataset is composed of private elementary and secondary education facilities in the United States as defined by the Private School Survey (PSS, https://nces.ed.gov/surveys/pss/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2017-2018 school year. This includes all prekindergarten through 12th grade schools as tracked by the PSS. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 2675 new records, modifications to the spatial location and/or attribution of 19836 records, the removal of 254 records no longer applicable. Additionally, 10,870 records were removed that previously had a STATUS value of 2 (Unknown; not represented in the most recent PSS data) and duplicate records identified by ORNL.Web Map originally owned by Summers Cleary

Higher Education Institutions in the United States of America Dataset

This repository contains a dataset of higher education institutions in the United States of America. This dataset was compiled in response to a cybersecurity research of American higher education institutions' websites [1]. The data is being made publicly available to promote open science principles [2].

Data

The data includes the following fields for each institution:

• Id: A unique identifier assigned to each institution.
• Region: The federal state in which the institution is located.
• Name: The full name of the institution.
• Category: Indicates whether the institution is public or private.
• Url: The website of the institution.

Methodology

The dataset was obtained from the Higher Education Integrated Data System (IPEDS) website [3], which is administered by the National Center for Education Statistics (NCES). NCES serves as the primary federal entity for collecting and analyzing education-related data in the United States. The data was collected on February 2, 2023.

The initial list of institutions was derived from the IPEDS database using the following criteria: (1) US institutions only, (2) degree-granting institutions, primarily bachelor's or higher, and (3) industry classification, which includes: public 4 - year or above, private not-for-profit 4 years or more, private for-profit 4 years or more, public 2 years, private not-for-profit 2 years, private for-profit 2 years, public less than 2 years, private not-for-profit for-profit less than 2 years and private for-profit less than 2 years.

The following variables have been added to the list of institutions: Control of the institution, state abbreviation, degree-granting status, Status of the institution, and Institution's internet website address. This resulted in a report with 1,979 institutions.

The institution's status was labeled with the following values: A (Active), N (New), R (Restored), M (Closed in the current year), C (Combined with another institution), D (Deleted out of business), I (Inactive due to hurricane-related issues), O (Outside IPEDS scope), P (Potential new/add institution), Q (Potential institution reestablishment), W (Potential addition outside IPEDS scope), X ( Potential restoration outside the scope of IPEDS) and G (Perfect Children's Campus).

A filter was applied to the report to retain only institutions with an A, N, or R status, resulting in 1,978 institutions. Finally, a data cleaning process was applied, which involved removing the whitespace at the beginning and end of cell content and duplicate whitespace. The final data were compiled into the dataset included in this repository.

Usage

This data is available under the Creative Commons Zero (CC0) license and can be used for any purpose, including academic research purposes. We encourage the sharing of knowledge and the advancement of research in this field by adhering to open science principles [2].

If you use this data in your research, please cite the source and include a link to this repository. To properly attribute this data, please use the following DOI: 10.5281/zenodo.7614862

Contribution

If you have any updates or corrections to the data, please feel free to open a pull request or contact us directly. Let's work together to keep this data accurate and up-to-date.

Acknowledgment

We would like to acknowledge the support of the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), within the project "Cybers SeC IP" (NORTE-01-0145-FEDER-000044). This study was also developed as part of the Master in Cybersecurity Program at the Instituto Politécnico de Viana do Castelo, Portugal.

References

1. Pending.
2. S. Bezjak, A. Clyburne-Sherin, P. Conzett, P. Fernandes, E. Görögh, K. Helbig, B. Kramer, I. Labastida, K. Niemeyer, F. Psomopoulos, T. Ross-Hellauer, R. Schneider, J. Tennant, E. Verbakel, H. Brinken, and L. Heller, Open Science Training Handbook. Zenodo, Apr. 2018. [Online]. Available: [https://doi.org/10.5281/zenodo.1212496]
3. Integrated Postsecondary Education Data System, "Compare Institutions", Fev 2023. [online]. Available: https://nces.ed.gov/ipeds/use-the-data

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.

Abstract (en): The primary purpose of the State Nonfiscal Survey is to provide basic information on public elementary and secondary school students and staff for each of the 50 states, the District of Columbia, and outlying territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). The database provides the following information on students and staff: general information (name, address, and telephone number of the state education agency), staffing information (number of FTEs on the instructional staff, guidance counselor staff, library staff, support staff, and administrative staff), and student information (membership counts by grade, counts of high school completers, counts of high school completers by racial/ethnic breakouts, and breakouts for dropouts by grade, sex, race). ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. All public elementary and secondary education agencies in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside of the United States. 2006-01-18 File DOC2450.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-01-18 File CB2450.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. (1) Part 2, Imputed Data, is a different version of the data in Part 1, Reported Data. The National Center for Education Statistics (NCES) imputed and adjusted some reported values in order to create a data file (Part 2) that more accurately reflects student and staff counts and improves comparability between states. Imputations are defined as cases where the missing value is not reported at all, indicating that subtotals for the category are under-reported. An imputation by NCES assigns a value to the missing item, and the subtotals containing this item increase by the amount of the imputation. Imputations and adjustments were performed on the 50 states and Washington, DC, only. Since all states and Washington, DC, reported data in this survey, these imputations and adjustments were implemented to correct for item nonresponse only. This process consisted of several stages and steps, and varied as to the nature of the missing data. No adjustments or imputations were made to high school graduates or other high school completer categories, nor were any adjustments or imputations performed on the race/ethnicity data. (2) The Instruction Manual that is included with this data collection also applies to COMMON CORE OF DATA: PUBLIC EDUCATION AGENCY UNIVERSE, 1995-1996 (ICPSR 2468) and COMMON CORE OF DATA: PUBLIC SCHOOL UNIVERSE, 1995-1996 (ICPSR 2470). (3) The codebook, data collection instrument, and instruction manual are provided as two Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using the Adobe Acrobat Reader (version 3.0 or later). Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

The Schools and Staffing Survey, 2007-08 (SASS 07-08), is a study that is part of the Schools and Staffing Survey (SASS) program. SASS 07-08 (https://nces.ed.gov/surveys/sass/) is a cross-sectional survey that collects data on public, private, and Bureau of Indian Education (BIE) elementary and secondary schools across the nation. The survey was primarily conducted through the use of mailed paper questionnaires. Nonresponse follow-up interviews were conducted using computer-assisted telephone interviews and face-to-face paper interviews. Teachers, librarians, principals, and districts were sampled. Key statistics produced from SASS 07-08 included how many teachers remained at the same school, moved to another school, or left the profession in the year following the SASS administration.

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACSAnnotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data. -9 An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small. -8 An '-8' means that the estimate is not applicable or not available. -6 A '-6' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. -5 A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. -3 A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate. -2 A '-2' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.