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.

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.

OVERVIEW

1. Title of Dataset: Arthralgia in female Master weightlifters

2. Author Information

Name: Marianne Huebner Institution: Michigan State University Address: East Lansing, MI 48824

1. Period of data collection: 27 April – 20 May 2022

2. Geographic region of data collection: Online survey in USA with participants from 30 countries in IWF regions Africa, Asia, Europe, Oceania, PanAmerican

LIST OF FILES

Dataset: wlmeno_oa.csv Data dictionary: wlmeno_oa_meta.xlsx

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: The survey was distributed by the Master Committee of the International Weightlifting Federation (IWF) to the National Master Chairs. They then used email or social media to communicate the study to the women weightlifters. The Survey was available in four languages (English, German, French, Spanish), translated and tested by native speakers. In addition, the survey was advertised in weightlifting interest groups via Facebook and Instagram. The survey was administered online via Qualtrics (Provo, UT, USA).

2. Methods for processing the data: Data were downloaded from Qualtrics (Provo, UT, USA) to Excel and then pre-processed in the statistical software R v. 4.3.0. (https://www.r-project.org)

   Variable formats (numeric, character) were checked and transformed, as appropriate.

3. Quality-assurance procedures performed on the data: Exclusion criteria were younger than 30 years (n=1), currently pregnant (n=3). To account for the possibility of male participants missing responses to age of menstruation or prior pregnancies (n=22), were also excluded. Since the focus was on active weightlifters, missing best snatch or clean and jerk in the last 6 months (n=18) were also exclusion criteria. This resulted in an analysis data set of 868 females. Univariate distributions were evaluated numerically and graphically.

DATA-SPECIFIC INFORMATION

1.Number of variables: 51

2.Number of cases/rows: 868

3.Variable List: wlmeno_oa.xlsx

4.Missing data codes: empty cells

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 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 dataset provides Census 2021 estimates for National Statistics Socio-economic Classification (NS-SeC) by sex in Northern Ireland. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

The quality assurance report can be found here

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 dataset provides Census 2021 estimates that classify usual residents aged 3 and over in Northern Ireland by main language.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

This table reports the categories for which there are 10 or more usual residents. Where there are fewer than 10 usual residents for any category, these have been reported in a residual group which may or may not contain 10 or more usual residents in total.

Main language is reported as provided by respondents; those who stated 'Chinese' are recorded as 'Chinese (not otherwise specified)'. If a specific Chinese language has been stated, it is recorded separately.

Quality assurance report can be found here

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

Flipped classroom models encourage student autonomy and reverse the order of traditional classroom content such as lectures and assignments. Virtual learning environments are ideal for executing flipped classroom models to improve critical thinking skills. This paper provides health professions faculty with guidance on developing a virtual flipped classroom in online graduate nutrition courses between September 2021 and January 2022 at the School of Health Professions, Rutgers The State University of New Jersey. Examples of pre-class, live virtual face-to-face, and post-class activities are provided. Active learning, immediate feedback, and enhanced student engagement in a flipped classroom may result in a more thorough synthesis of information, resulting in increased critical thinking skills. This article describes how a flipped classroom model design in graduate online courses that incorporate virtual face-to-face class sessions in a virtual learning environment can be utilized to promote critical thinking skills. Health professions faculty who teach online can apply the examples discussed to their online courses.

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.

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.

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in Northern Ireland by their highest level of qualification, and by broad age bands. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

'Age' is age at last birthday.

Qualification

• No qualifications: No academic or professional qualifications.
• Level 1: 1-4 GCSEs, O Levels, CSEs (any grades); NVQ level 1; or equivalent qualifications.
• Level 2: 5+ GCSEs (Grades A*-C, 9-4), O Levels (Passes), CSEs (Grade 1); 1 A Level, 2-3 AS Levels; NVQ level 2, BTEC General, City and Guilds Craft; or equivalent qualifications. Apprenticeship.
• Level 3: 2+ A Levels, 4+ AS Levels; NVQ Level 3, BTEC National, OND or ONC, City and Guilds Advanced Craft; or equivalent qualifications.
• Level 4+: Degree (for example BA, BSc), foundation degree, HND, HNC, NVQ Level 4-5, professional qualifications (for example teaching, nursing), or equivalent qualifications.
• Other: Any other qualifications, equivalent unknown.

Quality assurance report can be found here

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 < 001) and a decrease in unemployment (21.9% vs 2.1%, p < 001) were observed. The highest levels of impact were observed regarding the achievement of the professional goals as nearly 90% of the population agreed with this statement.ConclusionsThis study highlighted the creation and employment of an assessment tool that can be utilized to monitor the perceptions of student outcomes. Among the findings, a decrease in unemployment and a high degree of career impact and satisfaction were observed in the population of this study. Moving forward, it is essential that monitoring educational outcomes remains a priority worldwide.

This chart offers an insightful look at the store count by category in Montserrat. Leading the way is Apparel, with 1 stores, which is 33.33% of the total stores in the region. Next is Gifts & Special Events, contributing 1 stores, or 33.33% of the region's total. Sports also has a notable presence, with 1 stores, making up 33.33% of the store count in Montserrat. This breakdown provides a clear picture of the diverse retail landscape in Montserrat, showcasing the variety and scale of stores across different categories.

This dataset provides Census 2021 estimates that classify usual residents in Northern Ireland by ethnic group.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

This table reports the categories for which there are 10 or more usual residents. Where there are fewer than 10 usual residents for any category, these have been reported in a residual group which may or may not contain 10 or more usual residents in total.

All ethnic groups are classified within one of the five groups: White, Asian, Black, Mixed, and Other. 'Irish Traveller' is included in 'Other'; this is changed from Census 2011 when 'Irish Traveller' was included in 'White'.

Quality assurance report can be found here

This dataset provides Census 2021 estimates that classify usual residents in Northern Ireland by single year of age, and by sex. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.