The Graduate Students and Postdoctorates in Science and Engineering survey is an annual census of all U.S. academic institutions granting research-based master's degrees or doctorates in science, engineering, and selected health fields as of fall of the survey year. The survey, sponsored by the National Center for Science and Engineering Statistics within the National Science Foundation and by the National Institutes of Health, collects the total number of master's and doctoral students, postdoctoral appointees, and doctorate-level nonfaculty researchers by demographic and other characteristics such as source of financial support. Results are used to assess shifts in graduate enrollment and postdoc appointments and trends in financial support. This dataset includes GSS assets for 2022.

In the academic year of 2020/21, about 202,334 Master's degrees were earned in business across the United States, making it the most common master's degree earned. In that same year, another 47,257 Master's degrees were earned in engineering.

With the enactment of the Higher Education Opportunity Act (HEOA) of 2008, five Predominantly Black Institutions are eligible to receive funding to improve graduate education opportunities at the master’s level in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health or other scientific disciplines where African American students are underrepresented. Types of Projects Institutions may use federal funds for activities that include: Purchase, rental or lease of scientific or laboratory equipment for educational purposes, including instructional and research purposes; Construction, maintenance, renovation and improvement in classroom, library, laboratory and other instructional facilities, including purchase or rental of telecommunications technology equipment or services; Purchase of library books, periodicals, technical and other scientific journals, microfilm, microfiche, and other educational materials, including telecommunications program materials; Scholarships, fellowships, and other financial assistance for needy graduate students to permit the enrollment of students in, and completion of a master’s degree in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health, or other scientific disciplines in which African Americans are underrepresented; Establishing or improving a development office to strengthen and increase contributions from alumni and the private sector; Assisting in the establishment or maintenance of an institutional endowment to facilitate financial independence pursuant to Section 331; Funds and administrative management, and the acquisition of equipment, including software, for use in strengthening funds management and management information systems; Acquisition of real property that is adjacent to the campus in connection with the construction, renovation, or improvement of, or an addition to, campus facilities; Education or financial information designed to improve the financial literacy and economic literacy of students or the students’ families, especially with regards to student indebtedness and student assistance programs under title IV; Tutoring, counseling, and student service programs designed to improve academic success; Faculty professional development, faculty exchanges, and faculty participation in professional conferences and meetings; and Other activities proposed in the application that are approved by the Secretary as part of the review and acceptance of such application.

This page provides information about award recipients, project abstracts, and summaries of competitions under the Master's Degree Programs at Historically Black Colleges and Universities Program.

In the academic year of 2022, it is expected that 551,460 female and 331,530 male students will earn a Master’s degree in the United States. These figures are a significant increase from the academic year of 1950, when 16,980 female students and 41,220 male students earned a Master’s degree.

What is a Master’s degree?

A Master’s degree is an academic degree granted by universities after finishing a Bachelor’s degree. Master’s degrees focus in on a specific field and are more specialized than a Bachelor’s. A typical Master’s program is about two years long, with the final semester focusing on the thesis. Master’s degree programs are usually harder to get into than Bachelor’s degree programs, due to the rigor of the program. Because these programs are so competitive, those with a Master’s degree are typically paid more than those with a Bachelor’s degree.

Master’s degrees in the United States

The number of master’s degrees granted in the United States has steadily increased since the 1970s and is expected to continue to increase. In 2021, the Master’s degree program with the worst job prospects in the United States by mid-career median pay was counseling, while the program with the best job prospects was a physician's assistant.

Graduation of master's degree students, within the field of study grouping (Variant of the Classification of Instructional Programs (CIP) Canada 2021 Version 1.0 for Science, technology, engineering and mathematics (STEM) and Business, humanities, health, arts, social science and education (BHASE) groupings) and province or territory of first enrolment, by demographic characteristics. The STEM grouping includes fields of study in science, technology, engineering, and mathematics and computer sciences. The BHASE grouping includes fields of study in business, humanities, health, arts, social science, education, legal studies, trades, services, natural resources and conservation.

Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs. However, a gap remains between the computational skills taught in statistics service courses and those required for the use of statistics in scientific research. Ten years after the publication of "Computing in the Statistics Curriculum,'' the nature of statistics continues to change, and computing skills are more necessary than ever for modern scientific researchers. In this paper, we describe research on the design and implementation of a suite of data science workshops for environmental science graduate students, providing students with the skills necessary to retrieve, view, wrangle, visualize, and analyze their data using reproducible tools. These workshops help to bridge the gap between the computing skills necessary for scientific research and the computing skills with which students leave their statistics service courses. Moreover, though targeted to environmental science graduate students, these workshops are open to the larger academic community. As such, they promote the continued learning of the computational tools necessary for working with data, and provide resources for incorporating data science into the classroom.

Methods Surveys from Carpentries style workshops the results of which are presented in the accompanying manuscript.

Pre- and post-workshop surveys for each workshop (Introduction to R, Intermediate R, Data Wrangling in R, Data Visualization in R) were collected via Google Form.

The surveys administered for the fall 2018, spring 2019 academic year are included as pre_workshop_survey and post_workshop_assessment PDF files. 
The raw versions of these data are included in the Excel files ending in survey_raw or assessment_raw.

  The data files whose name includes survey contain raw data from pre-workshop surveys and the data files whose name includes assessment contain raw data from the post-workshop assessment survey.


The annotated RMarkdown files used to clean the pre-workshop surveys and post-workshop assessments are included as workshop_survey_cleaning and workshop_assessment_cleaning, respectively. 
The cleaned pre- and post-workshop survey data are included in the Excel files ending in clean. 
The summaries and visualizations presented in the manuscript are included in the analysis annotated RMarkdown file.

The best master's degree for getting a job was considered to be Physicians Assistant with a mid-career median salary of ****** U.S. dollars in 2021. Salaries for nurse practitioner and computer science master's were also high.

Historical Dataset of Ms School For Math And Science School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Expenditure Trends,Average Expenditure Per Student Trends,Graduation Rate Trends,American Indian Student Percentage Comparison Over Years (2006-2023),Asian Student Percentage Comparison Over Years (1996-2023),Hispanic Student Percentage Comparison Over Years (2000-2023),Black Student Percentage Comparison Over Years (1993-2023),White Student Percentage Comparison Over Years (1993-2023),Two or More Races Student Percentage Comparison Over Years (2016-2023),Comparison of Students By Grade Trends

China Number of Graduate: Postgraduate: Science data was reported at 66,248.000 Person in 2022. This records an increase from the previous number of 61,454.000 Person for 2021. China Number of Graduate: Postgraduate: Science data is updated yearly, averaging 41,822.000 Person from Dec 1997 (Median) to 2022, with 25 observations. The data reached an all-time high of 66,248.000 Person in 2022 and a record low of 7,473.000 Person in 1998. China Number of Graduate: Postgraduate: Science data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GD: No of Graduate.

Financial overview and grant giving statistics of Sigma Delta Epsilon Graduate Women In Science Inc

The Survey of Graduate Students and Postdoctorates in Science and Engineering (GSS) is an annual census conducted by the U.S. National Center for Science and Engineering Statistics (NCSES) under the National Science Foundation (NSF) and co-sponsored by the National Institutes of Health (NIH). It collects data from all U.S. academic institutions granting research-based master’s or doctoral degrees in science, engineering, and selected health fields as of fall each year. The dataset includes the total number of graduate students (master’s and doctoral), postdoctoral appointees, and doctorate-level nonfaculty researchers, categorized by demographics (e.g., gender, race/ethnicity), field of study, citizenship status, funding sources, and institutional characteristics. Its primary purpose is to track trends in STEM education and workforce development, supporting policy decisions, resource allocation, and research on workforce diversity and training. Key features include its comprehensive coverage of U.S. institutions, granular demographic breakdowns, and longitudinal data for analyzing changes over time. Unique aspects are its role as the sole federal survey capturing institutional-level data on graduate students and postdocs, making it critical for understanding STEM education pipelines and workforce dynamics. The dataset is widely used by policymakers, researchers, and institutions to assess workforce needs and equity in STEM fields.

Historical Dataset of Dove Science Academy South Ms Okc is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2019-2023),Total Classroom Teachers Trends Over Years (2019-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2019-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2023),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2019-2023)

Taiwan Number of Graduate: HE: Female: Education Science data was reported at 5,639.000 Person in 2017. This records a decrease from the previous number of 6,213.000 Person for 2016. Taiwan Number of Graduate: HE: Female: Education Science data is updated yearly, averaging 6,903.500 Person from Jul 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 7,946.000 Person in 1998 and a record low of 5,639.000 Person in 2017. Taiwan Number of Graduate: HE: Female: Education Science data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under Global Database’s Taiwan – Table TW.G056: Number of Graduate.

In 2024, it was projected that people in the United States with a Master’s degree in Computer Science would have the highest average starting salary, at 85,403 U.S. dollars. People who held a Master’s degree in Engineering were projected to have the second-highest starting salary, at 83,628 U.S. dollars. An abundance of Masters As higher education in the United States has become more common, and even expected, the number of Master’s degrees awarded has increased. During the 1949-50 academic year, about 58,180 Master’s degrees were awarded to students, with the vast majority being earned by male students. In the 2018-19 academic year, this figure increased to about 833,710 Master’s degrees awarded, with the majority being earned by female students. The right career While Engineering might have the highest starting pay for Master’s degree holders, those with a Master’s degree as a Physician Assistant had the highest mid-career median pay in 2021. Engineering continues to be one of the most popular fields for those seeking their Master’s degree, and STEM fields continue to dominate the field in number of Master’s degrees awarded.

This dataset was generated as part of Practical Exercise 1 of the Data Typology and Lifecycle course, within the UOC's Master's in Data Science.

The objective of the project is to demonstrate the operation of an automated scraper developed with Python and Selenium to extract historical statistics of Premier League players from the 2007/08 season to 2023/24.

This file contains simulated data.
To avoid potential conflicts with intellectual property or privacy rights, the original personal and sports data has been replaced with automatically generated fictitious values. Although masked, private use is preferred. The structure, format, and statistical consistency have been maintained for educational and demonstration purposes.

The original scraper dynamically accessed the official Premier League website (https://www.premierleague.com/stats) to extract information such as:

• Player name
• Position
• Nationality
• Date of birth
• Height
• Season
• Club

Seasonal statistics (goals, assists, appearances, minutes, cards, etc.)

This simulated dataset retains that structure but does not contain any real data.
It can be used as a basis for testing, data analysis training, or documentation of the scraping process.

Introduction This STEM advising outreach program was developed for undergraduate students who are contemplating future applications to PhD programs in the life sciences. The audience of ~20 students ranged in academic stage, and was composed mostly of life sciences undergraduates enrolled at Bowdoin College.

We have previously described two similar outreach events (ref. 1,2); this 90-minute combination of seminar and discussion built on that pilot program. This session at Bowdoin College was intended to complement the advising that students receive from their primary research mentors on campus. Although undergraduates at many excellent institutions have access to extensive pre-professional advising for careers in medicine, law and some other directions, the structure of advising for scientific research and the many career options that rely on PhD training is less consistent. Independent study or thesis research mentors are often a student’s primary source of advice. Career advisors have confirmed that reiteration and reinforcement of advising principles by professionals external to the school environment is helpful. Therefore, this outreach program’s content was developed with a goal of demystifying PhD programs and the benefits that they provide. The topics covered included (a) determining the key differences between programs, (b) understanding how PhD admissions works, (c) preparing an effective application, (d) proactive planning to strengthen one’s professional portfolio (internships, independent research, cultivating mentors), (e) key transferable skills that most students learn in graduate school, (f) what career streams are open to life science PhDs, and, (g) some national and institutional data on student career aspirations and outcomes (ref. 3). Methods The approach of bringing a faculty member and an administrative staff member who both have life science PhD training backgrounds was intentional. This allowed the program to portray different perspectives and experience to guide student career development, while offering credible witnesses to the types of experiences, skills and knowledge gained through PhD training. Central to the method of this outreach program is the willingness of graduate educators to meet the students on their own ground. The speakers guided students through a process of identifying national graduate programs that might best serve their individual interests and preferences. In addition to recruiting prospective applicants to Harvard Medical School (HMS) summer internships and PhD programs, the speakers made an explicit appeal to students to hone their professional portfolio proactively by discussing important skills that undergraduates need to be competitive in admissions and the career workplace including acquiring training in statistics and programming, soliciting diverse mentorship, acquiring authentic research experiences/internships, conducting thesis research, and obtaining fellowships). By reinforcing much of the anecdotal and formal advising content that is made available by faculty mentors and career counselors, our host saw the value of external experts to validate guidance.

This event built off our most recent event (ref. 2); we delivered a presentation covering the relevant topics and transitioned into an open discussion featuring a third visitor in our team. In contrast to the aforementioned previous event, the time constraint at lunch time prevented us from doing a formal panel. Our third speaker was a HMS Curriculum Fellow (ref. 4) whose career goals included teaching at a comparable institution (primarily undergraduate institution, PUI).

Students were encouraged to have lunch during the session, as the program was held at midday to avoid conflicts with other academic or extracurricular events. ResultsAs the principal goal of the session was to encourage and engage students, not to evaluate them, and the students ranged widely in stage and long-term career objectives, there were no assessment surveys of learning gains. Informally, student engagement was excellent as judged by the frequency and thoughtful nature of questions asked during the discussion phase of the session. Ad hoc student feedback directly following the event was extremely positive, as was our host’s follow up by email after the event. The success of the program was also evident by an invitation for a repeat of the program or other forms of collaboration in the future, including the possibility of reciprocal visits to HMS.DiscussionThis advising session was a continued refinement of our prototype, and thus served to prepare us for a series of similar events across a larger network of colleges. Our decision to incorporate a HMS Curriculum Fellow served three purposes: (1) to engage speaker who pursued doctoral training at three different institutions (UCLA, Tufts University, Harvard University), (2) to broaden the range of career trajectories presented as outcomes from doctoral programs, and (3) to provide networking and career development opportunities for the Curriculum Fellow.

Weighted average tuition fees by field of study for full-time Canadian graduate students. Data are collected from all publicly funded Canadian degree-granting institutions.

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.

This data set contains the research data for the master's thesis: Integrating Explainability into Federated Learning: A Non-functional Requirement Perspective. The master's thesis was written by Nicolas Sebastian Schuler at the Computer Science Department at Karlsruhe Institute for Technology (KIT) in Germany. The data set contains: - Associate Jupyter notebooks for reproducing the figures in the master's thesis. - Generated experiment data by the federated learning simulations. - Results of the user survey conducted for the master's thesis. - Used Python Libraries. It also includes the submitted final thesis. Notice: The research data is split into multiple chunks and can be combined via the following command after downloading: $ cat thesis-results-part-* > thesis-results.tar.zst and extracted via: $ tar --zstd -xvf thesis-results.tar.zst