This dataset provides comprehensive information about various Data Science and Analytics master's programs offered in the United States. It includes details such as the program name, university name, annual tuition fees, program duration, location of the university, and additional information about the programs.

Column Descriptions:

• Subject Name: The name or field of study of the master's program, such as Data Science, Data Analytics, or Applied Biostatistics.

• University Name: The name of the university offering the master's program.

• Per Year Fees: The tuition fees for the program, usually given in euros per year. For some programs, the fees may be listed as "full" or "full-time," indicating a lump sum for the entire program or for full-time enrollment, respectively.

• About Program: A brief description or overview of the master's program, providing insights into its curriculum, focus areas, and any unique features.

• Program Duration: The duration of the master's program, typically expressed in years or months.

• University Location: The location of the university where the program is offered, including the city and state.

• Program Name: The official name of the master's program, often indicating its degree type (e.g., M.Sc. for Master of Science) and format (e.g., full-time, part-time, online).

In 2023, ** percent of prospective graduate business students in the United States were interested in hybrid programs, an increase from ** percent in 2019. However, the overall preference in 2023 was for in-person business school programs, at ** percent.

According to a 2023 survey, ** percent of undergraduate students who were studying online in the United States were White, while ** percent were Black or African-American. In comparison, ** percent of graduate students studying online in the United States in that year were White, while ** percent were Black or African American.

Dataset with information on the number of new students in each Official Master's degree.

ABSTRACT The health care model based on the Family Health Strategy, created in the early 1990s, encouraged changes in health education, highlighting the need to create lato and stricto sensu postgraduate courses aimed at empowering professionals that foster comprehensive health care. Periodic evaluations are carried out and encouraged by Capes/MEC in order to maintain the quality of postgraduate courses, but evaluations of recently-introduced professional master’s degree courses in family health remain scarce. Objectives To describe the academic profile, contribution, motivations and expectations of graduates of a Professional Master’s in Family Health. Method Cross-sectional and quantitative study to analyze the results of 102 questionnaires answered by graduates of the Professional Master’s Degree in Family Health of the Estácio de Sá University (RJ), who had concluded the course between 2007 and 2012. The instrument consisted of open-ended and closed-ended questions, sent by e-mail and made available online through the electronic platform Survey Monkey. The study evaluated age, gender, regional origin, academic background, as well as the contributions, expectations and motivations related to the course. Results The survey sample was formed predominantly by female graduates, aged over 30, from 13 Brazilian states and, mainly from Medicine and Nursing courses. The contribution of the master’s degree to the graduate’s professional life was evaluated as excellent by 77% of the interviewees. The expectations regarding the course were positively evaluated and the main reasons for seeking the qualification were scientific-technical improvement and personal satisfaction, rather than better salaries or job stability. Conclusion The course was evaluated positively by the graduates, having exceeded their expectations and satisfied the interests that led them to it, thus producing changes to their personal and professional life. A longitudinal analysis of the impact of the professional master’s degree in the career of graduates will require a sequence of similar studies, as has been stimulated by Capes/MEC in recent years.

The COVID-19 data sets and associated Jupyter Hub notebooks are support for a manuscript describing how data science was shown to be effective in developing a transdisciplinary team and the production of novel outputs in part due to the common learning process of all team members being part of an online professional data science and analytics master’s degree program. This online curriculum helped the team members to find a common process that allowed them learn in common (Kläy, Zimmermann, & Schneider, 2015), transdisciplinary learning a key component of transdisciplinary teamwork (Yeung, 2015). Our team's Jupyter Hub files with complete coding and data set explanations are uploaded to document this teamwork and the outputs of the team.

The data relates to the paper that analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The data used have been gathered through an online survey created on the Qualtrics software package. The research questions were developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that played a role (see anonymous link at https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY. An SMS was sent to all students of the 2021 module group to make them aware of the survey. They were under no obligation to complete it and all information was regarded as anonymous. We received 39 responses. The raw data from the survey was processed through the SPSS statistical, software package. The data file contains the demographics, frequencies, descriptives, and open questions processed.     The study...

The International STEM Graduate Student Survey assesses why international students are coming to the United States for their graduate studies, the challenges they have faced while studying in the US, their future career plans, and whether they wish to stay or leave the US upon graduation. According to the Survey of Earned Doctorates by the National Science Foundation and the National Center for Science and Engineering Statistics, international students accounted for over 40% of all US doctoral graduates in STEM in 2013. The factors that influence international students' decisions to study in the US and whether they will stay or leave are important to US economic competitiveness. We contacted graduate students (both domestic and international) in STEM disciplines from the top 10 universities ranked by the total number of enrolled international students. We estimate that we contacted approximately 15,990 students. Individuals were asked to taken an online survey regarding their background, reasons for studying in the US, and whether they plan to stay or leave the US upon graduation. We received a total of 2,322 completed surveys, giving us a response rate of 14.5%. 1,535 of the completed were from domestic students and 787 of which were from international students. Raw survey data are presented here.Survey participants were contacted via Qualtrics to participate in this survey. The Universe of this survey data set pertains to all graduate students (Master's and PhD) in STEM disciplines from the following universities: Columbia University, University of Illinois-Urbana Champaign, Michigan State University, Northeastern University, Purdue University, University of Southern California, Arizona State University, University of California at Los Angeles, New York University, University of Washington at Seattle. Data are broken into 2 subsets: one for international STEM graduate students and one for domestic STEM graduate students, please see respective files.

Raw data for the manuscript entitled: European Agrifood and Forestry Education for a Sustainable Future - Gap Analysis from an Informatics Approach Abstract Purpose: To evaluate how well European agrifood and forestry Masters program websites use vocabulary associated with the NextFood Project ‘categories of skills’. Methodology: Web-scraping Python scripts were used to collect texts from European Masters programs websites, which were then analysed using statistical tools including Partial Least Squares Regression and contextual relation analysis. A total of fourteen countries, twenty-seven universities, 1303 European Masters programs, 3305 web-pages and almost two million words were studied using this approach. Findings: While agrifood and forestry Masters programs used vocabulary from the NextFood Project ‘categories of skills’ in most cases equal to or more often than non-agrifood and forestry Masters programs, we found evidence for the relative underuse of words associated with networking skills, with least use among agriculture-related Masters programs. Practical Implications: The informatic approach provides evidence that European agrifood and forestry Masters programs are for the most part following the educational paths for meeting future challenges as outlined by the NextFood Project, with the possible exception of networking skills. Theoretical Implications: This text-based, informatic approach complements the more targeted approaches taken by the NextFood Project in studying the skilling-pathways, which involved focus-group interviews, surveys of stakeholders, interviews of individuals with expert-knowledge and literature reviews. Originality: A text-based, web-scraping informatic approach has thus far been limited in the study of agrifood and forestry higher education, especially relative to recent advances made in the social sciences.

IntroductionThe assessment of student outcomes is essential for monitoring the quality of graduate programs in healthcare sciences. As such, this study focused on developing a self-employed questionnaire that allowed for the evaluation of elements focused on career impact and levels of satisfaction regarding graduate program education. Following, this instrument was utilized in a cross-sectional study design with alumni that had obtained their degree (MSc or PhD) over a 25-year span (1995–2020) from a graduate program in dentistry located in Brazil.MethodsThe employed instrument comprised a total of 43 questions presenting a mix of both close and open-ended questions coupled with 5-point Likert scales. The questionnaire was hosted online and a total of 528 alumni were invited to participate through e-mail and social media outreach.Results376 alumni answered the questionnaire (71.2% response rate). The majority were female (69.9%), and with a MSc (58.5%). Levels of satisfaction towards the program as well the impact in career and life were higher in alumni that had obtained a PhD degree compared to MSc. After obtaining the degree, an increase in involvement in teaching/research positions (3.4% vs 21.5%, p 

According to an online survey conducted in February 2025 in the United States, ********* of LinkedIn users held a bachelor degree or equivalent. Additionally, ** percent of LinkedIn users in the U.S. held a masters degree or equivalent.

This file set is the basis of a project in which Stephanie Pywell from The Open University Law School created and evaluated some online teaching materials – Fundamentals of Law (FoLs) – to fill a gap in the knowledge of graduate entrants to the Bachelor of Laws (LLB) programme. These students are granted exemption from the Level 1 law modules, from which they would normally acquire the basic knowledge of legal principles and methods that is essential to success in higher-level study. The materials consisted of 12 sessions of learning, each covering one key topic from a Level 1 law module.The dataset includes a Word document that consists of the text of a five-question, multiple-choice Moodle poll, together with the coding for each response option.The rest of the dataset consists of spreadsheets and outputs from SPSS and Excel showing the analyses that were conducted on the cleaned and anonymised data to ascertain students' use of, and views on, the teaching materials, and to explore any statistical association between students' studying of the materials and their academic success on Level 2 law modules, W202 and W203.Students were asked to complete the Moodle poll at the end of every session of study, of which there were 1,013. Only one answer from each of the 240 respondents was retained for Questions 3, 4 and 5, to avoid skewing the data. Some data are presented as percentages of the number of sessions studied; some are presented as percentages of the number of respondents, and some are presented as percentage of the number of respondents who meet specific criteria.Student identifiers, which have been removed to ensure anonymity, are as follows: Open University Computer User code (OUCU) and Personal Identifier (PI). These were used to collate the output from the Moodle poll with students' Level 2 module results.

This resource contains the survey questions, compiled results, and code for Fisher's exact test, as associated with the following manuscript:

"Faculty Perspectives on a Collaborative, Multi-Institutional Online Hydrology Graduate Student Training Program" by Anne J. Jefferson, Steven P. Loheide, and Deanna H. McCay. Submitted to Frontiers in Water, in the research topic: “Innovations in Remote and Online Education by Hydrologic Scientists", May 2022

Abstract: The CUAHSI Virtual University is an interinstitutional graduate training framework that was developed to increase access to specialized hydrology courses for graduate students from participating institutions. The program was designed to capitalize on the benefits of collaborative teaching, allowing students to differentiate their learning and access subject matter experts at multiple institutions, while enrolled in a single course at their home institution, through a framework of reciprocity. Although the CUAHSI Virtual University was developed prior to the covid-19 pandemic, the resilience of its online education model to such disruptions to classroom teaching increases the urgency of understanding how effective such an approach is at achieving its goals and what challenges multi-institutional graduate training faces for sustainability and expansion within the water sciences or in other disciplines. To gain faculty perspectives on the program, we surveyed water science faculty who had served as instructors in the program, as well as water science faculty who had not participated and departmental chairs of participating instructors. Our data show widespread agreement across respondent types that the program is positive for students, diversifying their educational opportunities and increasing access to subject matter experts. Concerns and factors limiting faculty participation revolved around faculty workload and administrative barriers, including low enrollment at individual institutions. If these barriers can be surmounted, the CUAHSI Virtual University has the potential for wider participation within hydrology and adoption in other STEM disciplines.

The global massive open online course (MOOC) market size is calculated to advance at a CAGR of 32% through 2034, which is set to increase its market value from US$ 13.2 billion in 2024 to US$ 212.7 billion by the end of 2034.

Report Attribute	Detail
MOOC Market Size (2024E)	US$ 13.2 Billion
Projected Market Value (2034F)	US$ 212.7 Billion
Global Market Growth Rate (2024 to 2034)	32% CAGR
China Market Value (2034F)	US$ 23.3 Billion
Japan Market Growth Rate (2024 to 2034)	32.6% CAGR
North America Market Share (2024E)	23.9%
East Asia Market Value (2034F)	US$ 49.1 Billion
Key Companies Profiled	Alison; Coursera Inc; edX Inc; Federica.EU; FutureLearn; Instructure; Intellipaat; iverity; Jigsaw Academy; Kadenze.

Country Wise Insights

Attribute	United States
Market Value (2024E)	US$ 1.4 Billion
Growth Rate (2024 to 2034)	32.5% CAGR
Projected Value (2034F)	US$ 23.6 Billion

Attribute	China
Market Value (2024E)	US$ 1.5 Billion
Growth Rate (2024 to 2034)	32% CAGR
Projected Value (2034F)	US$ 23.3 Billion

Category-wise Insights

Attribute	xMOOC
Segment Value (2024E)	US$ 9.3 Billion
Growth Rate (2024 to 2034)	30.8% CAGR
Projected Value (2034F)	US$ 136.1 Billion

Attribute	Degree & Master Programs
Segment Value (2024E)	US$ 6.4 Billion
Growth Rate (2024 to 2034)	30.2% CAGR
Projected Value (2034F)	US$ 89.3 Billion

This deidentified Excel qualitative data set contains graduate outcomes and graduates' views on the skills they acquired while completing the Women's Health Minor (WHM) at the University of Western Australia (UWA) between 2018 and 2023. Data showed that this self-selected sample of graduates (N=38) had acquired new and diverse skills while completing the WHM.

This data collection contains information on degrees earned at a sample of postsecondary institutions in the United States. The survey collected data on the number of completions of academic, vocational, and continuing professional educational programs by award category. There are three files in the collection. Part 1, Response Status Information, contains response status information to the completions survey for active institutions in the sample. Part 2, Postsecondary Completions: Awards/Degrees Conferred, contains the number of degrees and other awards granted by the institution in each field of study (CIP code), by level of award/degree, and sex of recipient. Part 3, Postsecondary Completions by Major Discipline (Two-Digit CIP Codes), contains the number of degrees and other awards conferred by major discipline (two-digit CIP code), award level, race/ethnicity, and sex of recipient.

This repository contains a dataset of higher education institutions in France. This includes 349 higher education institutions in France, including universities, universities of applied sciences and Higher Institutes as Higher Institute of Engineering, Higher Institute of biotechnologies and few others. This dataset was compiled in response to a cybersecurity investigation of France higher education institutions' websites [1]. The data is being made publicly available to promote open science principles [2].

The data includes the following fields for each institution:

• ETER_Id: A unique identifier assigned to each institution.
• Name: The full name of the institution.
• Category: Indicates whether the institution is public or private.
• Institution_Category_Standardized: Indicates whether the institution is University, University of applied sciences or other.
• Member_of_European_University_alliance: Indicates if the institution is member of European University Alliance (A kind of collaborative higher education institutions network in Europe).
• Url: The website of the institution.
• NUTS2: Nomenclature of Territorial Units for Statistics (NUTS): A classification by the European Union to divide member states' territories into statistical units. The NUTS system has three hierarchical levels, with NUTS2 being the second level.
• NUTS2_Label_2016: Refers to the classification of regions at the NUTS2 level according to the 2016 criteria set by the European Union.
• NUTS2_Label_2021: Refers to the classification of regions at the NUTS2 level according to the 2021 criteria set by the European Union.
• NUTS3: Nomenclature of Territorial Units for Statistics (NUTS): A classification by the European Union to divide member states' territories into statistical units. The NUTS system has three hierarchical levels, with NUTS3 being the third level.
• NUTS3_Label_2016: Refers to the classification of regions at the NUTS3 level according to the 2016 criteria set by the European Union.
• NUTS3_Label_2021: Refers to the classification of regions at the NUTS3 level according to the 2021 criteria set by the European Union.

The methodology for creating the dataset involved obtaining data from two sources: The European Higher Education Sector Observatory (ETER)[3]. The data was collected on December 26, 2024, the Eurostat for NUTS - Nomenclature of territorial units for statistics 2013-16[4] and 2021[5].

This section outlines the methodology used to create the dataset for Higher Education Institutions (HEIs) in France. The dataset consolidates information from various sources, processes the data, and enriches it to provide accurate and reliable insights.

Data Sources

1. ETER Database: The primary dataset was sourced from the ETER database, containing detailed information about HEIs in Europe.
   • File: eter-export-2021-FR.xlsx
2. Eurostat NUTS Data: Two datasets from Eurostat were used for regional information:
   • NUTS 2013-2016 regions: NUTS2013-NUTS2016.xlsx
   • NUTS 2021 regions: NUTS2021.xlsx

Data Cleaning and Preprocessing Column Renaming Columns in the raw dataset were renamed for consistency and readability. Examples include:

• ETER ID → ETER_ID
• Institution Name → Name
• Legal status → Category

Value Replacement

1. HEI Categories: The Category column was cleaned, with government-dependent institutions classified as "public."
2. Standardized Institution Categories: Mapped numerical values to descriptive labels such as "University" and "University of applied sciences."
3. European University Alliance Membership: Replaced binary values with "Yes" or "No."

Handling Missing or Incorrect Data

1. Specific entries with missing or incorrect data were updated manually based on their ETER_ID. For instance:
   • Adjusted URLs for entries like FR0333 (updated to www.icam.fr)
   • Adjusted URLs for entries like FR0906 (updated to epss.fr)
   • Adjusted URLs for entries like FR0104 (updated to www.ensa-nancy.fr)
   • Adjusted URLs for entries like FR0466 (updated to www.clermont-auvergne-inp.fr)
   • Adjusted URLs for entries like FR0907 (updated to insp.gouv.fr) - This universety also changed your name for Institut national du service public
   • Removed entries such as FR0129 and FR0944 due to insufficient or invalid information.
   • Removed FR0513 Institut supérieur européen de gestion Lyon because it's the same url and school of Paris, so remains only the main campus in Paris
   • Remove FR0235 Institut supérieur de l'électronique et du numérique Toulon, because it's the same url of Institut supérieur de l'électronique et du numérique Lille, so remains only the main campus
   • Remove FR0106 and FR010 École spéciale militaire, because it's the url returns 403 forbiden
   • Remove FR0970 École nationale de la meteorologie beucase of invalid HTTPS

Regional Data Integration

1. Merged NUTS 2016 and NUTS 2021 data to enrich the dataset with regional labels.

Final Dataset The final dataset was saved as a CSV file: france-heis.csv, encoded in UTF-8 for compatibility. It includes detailed information about HEIs in France, their categories, regional affiliations, and membership in European alliances.

Summary This methodology ensures that the dataset is accurate, consistent, and enriched with valuable regional and institutional details. The final dataset is intended to serve as a reliable resource for analyzing French HEIs.

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

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.

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.

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. The European Higher Education Sector Observatory, Dec 2024. Available: ETER
4. NUTS - Nomenclature of territorial units for statistics, Dec 2024. Available: NUTS-2013-2016
5. NUTS - Nomenclature of territorial units for statistics, Dec 2024. Available: NUTS-2021.

Abstract The aim of this paper is to understand students’ experience of research methodology teaching, through a survey with students enrolled in the Master’s Degree Program in Information Management, Libraries and Archives at the Complutense University of Madrid. The analyzed themes included the students’ perception of collaborative work, influence of emotions, implications of research competencies at the professional level, and the role of supervisors. Twenty-six master’s students, both online and on-site, were surveyed among those enrolled in the academic years 2014-2015 and 2013-2014. Results show the need to foster collaborative work with individual work in a balanced way. Furthermore, emotions, especially positive ones, appear to intertwine heavily with the learning experience. It is more difficult to appreciate the implications of research competencies for the professional sphere because of differences in the professional context of all students involved. The activities that students perceive as more creative include discussions of one’s own work (especially with the supervisor) as well as discussions of other students’ work (attendance at Master Thesis Defenses). Finally, supervisors stand out as important figure during the learning of research methodology, as their area of expertise is particularly relevant.

This longitudinal data collection supplies information on the educational, vocational, and personal development of young people who were high school seniors in 1972 and examines the kinds of factors -- personal, familial, social, institutional, and cultural -- that may affect that development. The collection provides a broad spectrum of information on each student and covers areas such as ability, socioeconomic status, home background, community environment, ethnicity, significant others, current activity at time of survey, educational attainment, school experiences, school performance, work status, work performance and satisfaction, goal orientations, marriage and the family, and military experience. Data collected in the base-year (1972) focus on factors relating to the student's personal/family background, education and work experiences, plans, aspirations, attitudes, and opinions. The first follow-up, which was conducted in 1973, offers information on the respondent's activity state (education, work, etc.), socioeconomic status, work and educational experience since leaving high school, future plans, and expectations. The second follow-up (1974) probes respondents on similar measures but is augmented by additional variables pertaining to work and education. The third follow-up (1976) contains additional items on graduate school application and entry, job supervision, sex roles, sex and race biases, and a subjective rating of high school experiences. The fourth follow-up (1979) offers data similar to the other follow-ups but includes some variables that were modified to elicit unique information. For the fifth follow-up, the sample members averaged 32 years of age and had been out of high school for 14 years. In addition to covering the same subject areas as the previous surveys, this follow-up includes additional questions on marital history, divorce, child support, and economic relationships in modern families. Part 1 of this collection contains base-year data as well as data collected during four subsequent follow-ups undertaken in 1973, 1974, 1976, and 1979, while Part 12 contains fifth follow-up data for 1986. Part 2, the School File, contains information obtained from the respondent's high school and also from high school counselors. Data are available on school organization and enrollment, course offerings, special services and programs, library and other resources, time scheduling, and grading systems. Counselor information is supplied on work loads, counseling practices and facilities, experience with student financial aid programs, age, ethnicity, training, and experience. A supplementary School District Census File, Part 3, contains 1970 Census data tabulated by school district boundaries. In addition, the collection includes an FICE Code File and a CEEB Institutional Data Base File that can be used in conjunction with the student file to supply contextual information about respondents' colleges. The Institutional Data Base File offers data for colleges and universities on items such as enrollment, income and revenues, expenses, tuition and fees, and median student scores on standardized tests. Parts 6, 7, 9, and 10 contain transcript data from each postsecondary institution reported by sample members in the first through fourth follow-up surveys. Data are available for several types of postsecondary institutions, ranging from short-term vocational or occupational programs through major universities with graduate programs and professional schools. Data in these four rectangular files -- Student, Transcript, Term, and Course Files -- are organized to be used in combination hierarchically. Information is available on terms of attendance, fields of study, specific courses taken, and grades and credits earned. The Fifth Follow-Up Teaching Supplement (Parts 15-17) surveyed those members of the original 1972 sample who had obtained teaching certificates and/or who had teaching experience. Respondents were asked questions about their qualifications, experience, and attitudes toward teaching.