In the academic year of 2021/22, about 880,250 students were awarded a Master's degree in the United States. This figure is projected to increase by the academic year of 2031/32, when it is forecasted that 1,000,460 students will be awarded a Master's degree.

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.

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 reported in this paper employed the mixed methods approach comprising a quantitative and qualitative analysis. The quantitative and econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explain it. The results show significance in terms of the assignments and existing knowledge marks in terms of their bachelor's average mark. We extended the analysis to a qualitative and quantitative survey, which indicated that the mean statistical feedback was above average and therefore strongly agreed/agreed except for library use by the student. Students, therefore, need more guidance in terms of library use and the open questions showed a need for a research methods course in the future. Furthermore, supervision tends to be a significant determinant in all cases. It is also here where supervisors can use social media instruments such as WhatsApp and Facebook to inform students further. This study contributes as the first to investigate the preparation and research skills of students for master's and doctoral studies during the COVID-19 pandemic in an online environment.

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 

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.

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.

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.

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.

Between 2015 and 2024, the number of bachelor's students who graduated from online universities in Italy steadily increased. In 2015, less than ***** people obtained their bachelor's from an online university. After nine years, the number of students more than doubled, reaching ****** graduates. In Italy, bachelor's students represented the largest group of e-learning university students, ******* people.

Abstract

High quality postgraduate training in science, technology, engineering and mathematics (STEM) related disciplines in sub-Saharan Africa (SSA) is important to strengthen research evidence to advance development and ensure countries achieve the Sustainable Development Goals (SDGs). Equally, participation of women in STEM careers is vital, to ensure that countries develop economies that work for all their citizens. However, women and girls remain underrepresented in STEM due to gender stereotyping, lack of visible role models, and unsupportive policies and work environments. Therefore, there is a need to consolidate information on participation and experiences of women in STEM related postgraduate training and careers in SSA to enhance their contribution to realizing the SDGs. The primary objective of this study is to examine the participation and experiences of women in postgraduate training, and their subsequent recruitment, retention and progression in STEM careers in East Africa. A secondary objective is to establish the gender gaps in training and career engagement in selected STEM related academic disciplines in East Africa. The descriptive study will employ a mixed methods approach, including a scoping review, qualitative interviews, and quantitative analysis of secondary data. We will synthesize results to inform the development of an effective gendered approach and framework to improve participation and experiences of women in STEM training and career engagements in SSA. We will conduct the study over a period of five years.

Geographic coverage

Regional coverage (East Africa Region)

Analysis unit

Individual Women in STEM

Universe

Qualitative data: Women in Science Technology Engineering and Mathematics (STEM) in postgraduate training and career Quantitative data: Postgraduate students, faculty, reseachers and supervisors (both men and women) in STEM in Inter-University Council for East Africa (IUCEA) member Universitiies

Sampling procedure

The study utilized a purposive sampling technique and targeted all universities that offered doctoral programs in applied sciences, technology, engineering, and mathematics. At the time, only 23 of the 74 universities in Kenya—equivalent to 30%—offered doctoral degrees in STEM. It was assumed that a similar or lower percentage would be found in the other five countries, namely Uganda, Tanzania, Rwanda, Burundi, and South Sudan.

Purposive sampling was used to recruit participants from purposively selected universities and national higher education commissions and agencies for the study. In universities, all students enrolled in doctoral programs in STEM were considered. Additionally, female and male students' lecturers, supervisors, mentors, and other faculty members and researchers in the identified institutions were also considered for participation in the study.

Purposive sampling of doctoral students, faculty, and early career researchers (post-doctoral fellows within the first six years since receiving their PhD) was conducted using the following inclusion criteria:

Inclusion criteria i. Worked in a STEM field/discipline ii. Enrolled in a doctoral program within a STEM field iii. Early career researchers in a STEM field in research organizations iv. Faculty in a STEM field at a university

Additionally, registrars, postgraduate training coordinators, heads of departments, and officials from national agencies and ministries related to postgraduate training and research were purposively selected from all the identified universities to provide input on existing policies, guidelines, and enrollment data. For each of the mentioned groups, 7-12 interviews were conducted, totaling 60 interviews.

Sampling deviation

Qualitative For the Key informant interviews one participant was interviewed from the engineers board despite the scope being Inter-University Council for East Africa (IUCEA) member Universities.

Quantitative The online survey was completed by some researchers not working/teaching in IUCEA member universities

Mode of data collection

Other [oth]

Research instrument

Quantitative data collection A. Online Survey This was carried out through an online survey questionnaire that was circulated via email and other digital platforms such as WhatsApp. The questionnaire had various parts: Part A - Participants characteristics This section mainly collected demographic details such as age, gender, nationality, residence, marital status, income, highest level of education completed, year of study, supervision and mentoship relationship, field of study in STEM (Science, Technology, Enginnering and Mathematics), mode of funding of postgraduate degree,

Part B - Status of Gender equality This section collected information on students enrollment and graduation in masters and PhD in STEM looking at gender distribution,

Part C - Factors that contribute to participation of women in STEM This section collected information on the factors or situations encountered while pursuing career in STEM in your specific discipline

Part D - Strategies for Optimizing Women's Engagement in STEM This section collected information on the strategies can maximize engagement of women in STEM training PhD level and subsequent careers

Part E - Effect of the COVID-19 pandemic on women's progression In this section collected information on COVID-19 pandemic affect on research progress or deadline for submission of thesis, COVID-19 pandemic affect on current research funding, COVID-19 pandemic caused researchers to work from home, working from affected progress in studies, any direct responsibilities caring for children, number of children being taken care of, change of domestic work responsibilities since the COVID-19 outbreak, change of domestic work responsibilities since the COVID-19 outbreak on studies, COVID-19 pandemic affect on access to these research tools which inlude: Computer or laptop, Reliable Internet, Assistive Technology, Laboratory equipment, University Library, Archives/special collections and Access to patients/research participants. It als collected information on: any benefits to COVID-19 pandemic for your work, some ways one thinks their supervisor or line manager could support or help one manage the impacts of COVID-19 on studies

The questionnaire was developed in English and was latertranslated into French to accommodate the French speaking countries i.e Burundi and Rwanda. The French questionnaire was backtlanslated to English to ensure the questions still maintained their original meaning. This work was done by an external consultant and the French questionnaires were reviewed by the research assistant from Burundi and tested among postgraduate students in Light University.

All questionnares and modules are provided as external resources.

Cleaning operations

Qualitative The data was collected through qualitative interviews (In-depth interviews) and focus group discussions. They were audio recorded and the recordings were transcribed on Ms Ofiice.The transcript were subjected to data quality checks and the clean transcripts were anonyzed for data protection.

QUANTITATIVE Secondary data The data was collected from the five countries in an Ms Excel designed data abstraction sheet. The data abstraction sheet helped the universities administrators and rergistrars to directly enter the data only in the required field and for the defined or specific variables. For the dataset that was in hardcopy format the data entry was also done using the data abstraction sheets. The data sets were subjected to data quality checks for data quality. We used a standard template to ensure data editing took place during data entry.

Online survey Data entry was in form of responding to the survey. Data editing was done while cleaning the data.

Response rate

Quantitaive The online survey link was circulated using contacts within universities and research institutions in East Africa via email and social media platforms such as WhatApp hence it is impossible to track those who received the survey and hence it is not possible t calculate the survey response rate.

Sampling error estimates

NA

Data were collected through an online survey and processed to create 95% CI using the BCA bootstrap confidence interval algorithm in MS EXCEL. Construction of confidence interval in MS EXCEL using the BCA bootstrap confidence interval algorithm is earlier not presented in any studies. The macro capabilities of MS EXCEL was utilized for the purpose stated.

Morocco MA: Refugee Population: by Country or Territory of Origin data was reported at 3,064.000 Person in 2017. This records an increase from the previous number of 2,262.000 Person for 2016. Morocco MA: Refugee Population: by Country or Territory of Origin data is updated yearly, averaging 1,299.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 4,710.000 Person in 2006 and a record low of 15.000 Person in 1990. Morocco MA: Refugee Population: by Country or Territory of Origin data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;

Morocco MA: Refugee Population: by Country or Territory of Asylum data was reported at 4,678.000 Person in 2017. This records a decrease from the previous number of 4,771.000 Person for 2016. Morocco MA: Refugee Population: by Country or Territory of Asylum data is updated yearly, averaging 779.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 4,771.000 Person in 2016 and a record low of 51.000 Person in 1996. Morocco MA: Refugee Population: by Country or Territory of Asylum data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of asylum is the country where an asylum claim was filed and granted.; ; United Nations High Commissioner for Refugees (UNHCR), Statistics Database, Statistical Yearbook and data files, complemented by statistics on Palestinian refugees under the mandate of the UNRWA as published on its website. Data from UNHCR are available online at: www.unhcr.org/en-us/figures-at-a-glance.html.; Sum;

Information about fire and burn data and statistics in Massachusetts.

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.

Morocco MA: SPI: Pillar 2 Data Services Score: Scale 0-100 data was reported at 90.400 NA in 2023. This stayed constant from the previous number of 90.400 NA for 2022. Morocco MA: SPI: Pillar 2 Data Services Score: Scale 0-100 data is updated yearly, averaging 89.400 NA from Dec 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 90.600 NA in 2021 and a record low of 73.600 NA in 2016. Morocco MA: SPI: Pillar 2 Data Services Score: Scale 0-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank.WDI: Governance: Policy and Institutions. The data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including input to national data strategies, advice on data ethics and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.;Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators);Weighted average;