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.

The Survey of Doctorate Recipients (SDR) provides demographic, education, and career history information from individuals with a U.S. research doctoral degree in a science, engineering, or health (SEH) field. The SDR is sponsored by the National Center for Science and Engineering Statistics and by the National Institutes of Health. Conducted since 1973, the SDR is a unique source of information about the educational and occupational achievements and career movement of U.S.-trained doctoral scientists and engineers in the United States and abroad. This dataset includes SDR assets for 2019.

This dataset is used for my PhD about applying machine learning algorithms in the audit practice. Where I focus on comparing different Machine learning algorithms and analyse how they perform.

The Survey of Earned Doctorates (SED) is an annual census conducted since 1957 of all individuals receiving a research doctorate from an accredited U.S. institution in a given academic year. The SED is sponsored by the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF) and by three other federal agencies: the National Institutes of Health, Department of Education, and National Endowment for the Humanities. The SED collects information on the doctoral recipient's educational history, demographic characteristics, and postgraduation plans. Results are used to assess characteristics of the doctoral population and trends in doctoral education and degrees. This dataset includes SED assets for 2022.

Survey questions and raw data results for ‘Library Research Support Staff Survey (White Rose Libraries)’. The survey was conducted by the author on behalf of Leeds University Library, Research Support Team, in May 2017. It investigates the educational background of staff working at the White Rose University Libraries (Leeds, Sheffield, and York) in roles supporting researchers.

Abstract Recent studies show that students applying appropriate self-regulated learning strategies (SRL) are more successful in their academic achievements (AA). However, the relation between SRL and AA is complex. There is evidence that not all SRL strategies contribute equally to AA. A greater understanding of the relationship between students’ SRL strategies and AA can help indicate differences between students. Interviews were conducted to study the relationship between the SRL strategies students use when learning for an achievement test and the resulting AA. Two main aspects that influence this relationship were identified: students’ goal approach, and with this approach, the amount of effort they put into learning, and the deliberateness of using SRL strategies. These aspects address the complex relationship between SRL and AA. From these results we present different student types, based on these aspects found. Suggestions for future research are done to utilise and further explore these student types. Data The quantative dataset comprises the responses to the Motivated Strategies for Learning Questionnaire (MSLQ) and the grades from the Educational Sciences exams in the first and second year of teacher training. In addition, the (qualitative) estimates for awareness status, control and goal orientation, as used in the two articles, are provided. These responses and scores come from the 18 participants in the two articles. The data are provided in an Excel file with separate sheets: 1) article information, 2) grades, 3) MSLQ scores, and 4) the raw data from the MSLQ questionnaire. The qualitative dataset consists of 18 transcripts of approximately one-hour interviews with students. These transcripts are in Dutch, the native language of the students. 18 students from different teacher training programmes at a University of Applied Sciences in the Netherlands participated in this study. All students are given aliases that correspond to the file names of the transcripts and quantitative data in the spreadsheet.

Dataset of relevant newspaper articles that are the primary data underlying the doctoral research project of Marie Garnier. This dataset includes the following files:
(1) Metadata file (text file, information to understand the dataset)
(2) Bilbiographic information file (markup language text file, bibliographic information of newspaper articles retrieved and included)
(3) Coding handbook (text file)
(4) Raw dataset (qualitative data analysis file, newspaper articles included in content analysis)
(5) Processed dataset (qualitative data analysis file, coded newspaper articles included in content analysis)

This collection automatically includes metadata, the source of which is the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL USE OF THE REPUBLIC OF SLOVENIA and corresponding to the source database entitled “Number of new PhDs, average age at doctorate degree and average time to complete studies by field of doctorate science and sex, Slovenia, multiannually”.

Actual data are available in Px-Axis format (.px). With additional links, you can access the source portal page for viewing and selecting data, as well as the PX-Win program, which can be downloaded free of charge. Both allow you to select data for display, change the format of the printout, and store it in different formats, as well as view and print tables of unlimited size, as well as some basic statistical analyses and graphics.

Description: These are research indicators of doctorate holders in Europe that were compiled from the criteria and factors of the Eurostat. This dataset consists of data in five categories (i.e. Career Development of Doctorate Holders; Labour Market - Job Vacancy Statistics; Skill-related Statistics; European and International Co-patenting in EPO Applications and Ownership of Inventors in EPO Applications). The Eurostat Research Indicators consist of (1) Doctorate holders who have studied, worked or carried out research in another EU country (%); (2) Doctorate holders by activity status (%); (3) Doctorate holders by sex and age group; (4) Employed doctorate holders working as researchers by length of stay with the same employer (%); (5) Employed doctorate holders working as researchers by job mobility and sectors of performance over the last 10 years (%); (6) Employed doctorate holders by length of stay with the same employer and sectors of performance (%); (7) Employed doctorate holders by occupation (ISCO_88, %); (8) Employed doctorate holders by occupation (ISCO_08, %); (9) Employed doctorate holders in non-managerial and non-professional occupations by fields of science (%); (10) Level of dissatisfaction of employed doctorate holders by reason and sex (%); (11) National doctorate holders having lived or stayed abroad in the past 10 years by previous region of stay (%); (12) National doctorate holders having lived or stayed abroad in the past 10 years by reason for returning into the country (%); (13) Non-EU doctorate holders in total doctorate holders (%); (14) Unemployment rate of doctorate holders by fields of science; (15) Employment in Foreign Affiliates of Domestic Enterprises; (16) Employment in Foreign Controlled Enterprises; (17) Employment rate of non-EU nationals, age group 20-64; (18) Intra-mural Business Enterprise R&D Expenditures in Foreign Controlled Enterprises; (19) Job vacancy rate by NACE Rev. 2 activity - annual data (from 2001 onwards); (20) Job vacancy statistics by NACE Rev. 2 activity, occupation and NUTS 2 regions - quarterly data; (21) Job vacancy statistics by NACE Rev. 2 activity - quarterly data (from 2001 onwards); (22) Value Added in Foreign Controlled Enterprises; (23) Graduates at doctoral level by sex and age groups - per 1000 of population aged 25-34; (24) Graduates at doctoral level, in science, math., computing, engineering, manufacturing, construction, by sex - per 1000 of population aged 25-34; (25) Level of the best-known foreign language (self-reported) by degree of urbanisation; (26) Level of the best-known foreign language (self-reported) by educational attainment level; (27) Level of the best-known foreign language (self-reported) by labour status; (28) Level of the best-known foreign language (self-reported) by occupation; (29) Number of foreign languages known (self-reported) by educational attainment level; (30) Number of foreign languages known (self-reported) by degree of urbanisation; (31) Number of foreign languages known (self-reported) by labour status; (32) Number of foreign languages known (self-reported) by occupation; (33) Population by educational attainment level, sex, age and country of birth (%); (34) Co-patenting at the EPO according to applicants’/inventors’ country of residence - % in the total of each EU Member State patents; (35) Co-patenting at the EPO: crossing inventors and applicants; (36) Co-patenting at the EPO according to applicants’/inventors’ country of residence - number; (37) EU co-patenting at the EPO according to applicants’/ inventors’ country of residence by international patent classification (IPC) sections - number; (38) EU co-patenting at the EPO according to applicants’/inventors’ country of residence by international patent classification (IPC) sections - % in the total of all EU patents; (39) Domestic ownership of foreign inventions in patent applications to the EPO by priority year; (40) Foreign ownership of domestic inventions in patent applications to the EPO by priority year; and (41) Patent applications to the EPO with foreign co-inventors, by priority year.

DZHW PhD Panel 2014 - first wave: standardised self-administered survey

The de-identified data is collected due to the PhD research work. It is stored in this platform to fulfill the International Journal of Environmental Health Research publication requirement.

The dataset was produced for a scientometric study on French PhD theses in the field of sustainable development, presented at the Twenty-Fifth International Conference on Grey Literature "Confronting Climate Change with Trusted Grey Resources", OBA Congres, November 13-14, 2023, Oosterdokskade, Amsterdam, The Netherlands. We reused a dataset with metadata of 431,997 theses ("Thèses soutenues en France depuis 1985") produced by ABES and available as public open data at the following address: https://www.data.gouv.fr/fr/datasets/theses-soutenues-en-france-depuis-1985/ The ABES dataset was downloaded in csv format on August 16, 2023. Our dataset is a subsample of the ABES dataset; it contains 3,467 theses which represent 0.8% of the total number of theses in the ABES file. The purpose of the study is to assess the French PhD theses on sustainable development, with two objectives: to give a scientometric overview on the French PhD landscape in the field of sustainable development; and to show how PhD theses (as a major part of grey literature) and related tools can be helpful for the scientometric study of science. The review is based on data from the French national portal theses.fr. The results of our study provide a detailed review of the French PhD research on sustainable development from 1985 to 2022, including the main French research universities in the field of sustainable development and the most eminent academic scholars, the disciplinary distribution of the research on sustainable development, and the accessibility of the PhD theses on sustainable development (open science). The analysis of the year of defense will allow a longitudinal approach to these aspects. The dataset contains personal data from theses.fr This is the personal data notice of ABES regarding theses.fr https://www.theses.fr/donnees_personnelles « theses.fr, which includes personal information concerning in particular doctors, thesis directors and members of the defense jury, has been the subject of a normal declaration to the CNIL No. 1537454 v0. In accordance with the European General Data Protection Regulation (GDPR), you have the right to access, rectify and delete data concerning you, online on this site. To exercise this right, you can contact the ABES help desk. » https://www.data.gouv.fr/fr/datasets/theses-soutenues-en-france-depuis-1985/#/resources/a826e757-a68a-46d5-8319-e784bb80ba73 https://vocabularies.unesco.org/browser/thesaurus/en/

Purpose Medical schools increasingly rely on near-peer tutors for ultrasound teaching. We set out to compare the efficacy of a blended near-peer ultrasound teaching program to that of a faculty course in a randomized controlled trial. Methods 152 medical students received 21 hours of ultrasound teaching either by near-peer teachers or medical doctors. The near-peer course consisted of blended learning that included spaced repetition. The faculty-led course was the European common course for abdominal sonography. The primary outcome measurement was the students' ultrasound knowledge at month 6, assessed by structured examination (score 0 to 50). Secondary outcomes included scores at month 0 and changes in scores after the course. ResultsStudents in the near-peer group scored 37 points, and students in the faculty group scored 31 points six months after course completion. The difference of 5.99 points (95% CI 4.48;7.49) in favor of the near-peer group was significant (p<0.001). Scores immediately after the course were 3.8 points higher in the near-peer group (2.35; 5.25, p<0.001). Ultrasound skills decreased significantly in the six months after course completion in the faculty group (-2.41 points, [-3.39; -1.42], p<0.001]) but barely decreased in the near-peer group (-0.22 points, [-1.19; 0.75, p=0.66]). ConclusionThe near-peer course that combined blended learning and spaced repetition outperformed standard faculty teaching in basic ultrasound education. This study encourages medical schools to use peer teaching combined with e-learning and spaced repetition as an effective means to meet the increasing demand for ultrasound training. Explanation of all the instruments used in the data collection (including phrasing of items in surveys) Baseline Questionnaire, Exam Sheets OSCE 1, Questionnaire at OSCE 1, Exam Sheets OSCE 2, Questionnaire at OSCE 2. Items see separate table "Instrumente_SIGNATURE_v13" Explanation of the data files: what data is stored in what file? "Full data set" contains all the data from the 3 questionnaires and the 2 exams mentioned above. The second file "Instrumente_SIGNATURE_v13" explains the meaning of the columns in the data set In case of quantitative data: meaning and ranges or codings of all columns See separate table "Instrumente_SIGNATURE_v13"

Full edition for scientific use. The data collection was carried out for an exploratory needs-assessment at the University of Vienna, Austria in the course of the FAIR Data Austria project. PhD students from various disciplines were asked about their research data and their approach to data sharing, as well as about their individual use of the university's research data management services. Moreover, the survey assessed students' expectations and needs regarding data management training and the introduction of data stewards as another service provided by the university.

Study 5: Down from the Ivory Tower: Exploring Implementation of the ESTRO Core Curriculum at the National Level. An anonymous, 37-item, survey was designed and distributed to the Presidents of the National Societies who have endorsed the ESTRO Core Curriculum (n=29). The survey addressed perceptions about implementation factors related to context, process and curriculum change. The data was summarized using descriptive statistics.

She Figures 2018 investigates the level of progress made towards gender equality in research & innovation (R&I) in Europe. It is the main source of pan European, comparable statistics on the representation of women and men amongst PhD graduates, scientists and engineers, researchers throughout their career and academic decision makers. The data also sheds light on differences in the experiences of women and men working in research – such as pay-gap, working conditions and success in obtaining research funds. It also presents the situation of women and men as authors of scientific publications and as patent inventors. A last subset of data focuses on the integration of sex and gender analysis in the content of scientific literature.

This compendium is produced in close cooperation with Member States, Associated Countries, and Eurostat. Methodological insight, including details on data sources, is provided in the She Figures Handbook 2018.

This is the subnational dataset to recreate Table 4.3 in Chapter 4 of my PhD thesis.

This is a zip file containing the dataset of the results presented in the PhD thesis "Enabling interoperability between MAC-heterogeneous sensor networks". The archive is organised per chapter and contains both the "raw" data obtained for the individual tests and the "aggregated" data that is calculated from the "raw" data and used to generate the graphs in the thesis.

Publication reference: Donner, P. (2020). A validation of co-authorship credit models with empirical data from the contributions of PhD candidates. Quantitative Science Studies, v. 1, i. 2, p. 551-564. https://doi.org/10.1162/qss_a_00048.

The file contains one row per authorship contribution statement. Rows of publications and theses are grouped.

Description of columns:

dissertation_id - an integer identifying each dissertation thesis

university - university at which the dissertation thesis was written and PhD degree conferred

year - publication year of the dissertation thesis

author - dissertation thesis author name

title - dissertation thesis title

subject - the field of research

publication_id - an integer identifying each publication; publication associated with more than one thesis have the same id across theses

reference - bibliographic reference for the publication associated with the thesis

author_count - number of authors of the publication

author_position - position in the author byline of the credited author

credit - claimed credit of the author in percent

corresponding_author - flag for whether the publication author of this row is a orresponding author

The dataset is associated with the paper entitled: How Academics and the Public Experienced Immersive Virtual Reality for Geo-education.

It contains feedback regarding users’ experience with Immersive Virtual Reality for geological exploration, through a tailored approach developed by Tibaldi et al. (2020) where the Virtual Landscape is based on 3D photogrammetry-based high-resolution models.

Such feedback has been acquired through anonymous questionnaires during nine dissemination events held in 2018 and 2019 in various locations (Vienna in Austria, Milan and Catania in Italy and Santorini in Greece), in the framework of the following projects: i) the MIUR project ACPR15T4_00098–Argo3D (http://argo3d.unimib.it/); ii) 3DTeLC Erasmus+Project 2017-1-UK01-KA203-036719 (http://www.3dtelc.com); iii) EGU 2018 Public Engagement Grant (https://www.egu.eu/outreach/peg/) .

In the dataset, feedback has been grouped into categories, based on users age and background:

i) Middle and High School Students (Schools students, results in Sheet 1);

ii) MSc Students in Earth Sciences (MSc, results in Sheet 2);

iii) Academics/Researchers in Earth Sciences, that include PhD students and postdocs (Academics, results in Sheet 3);

iv) Lay Public (i.e. participants that do not belong to the other groups, results in Sheet 4).

It lists a total of 459 records; further details are available in the manuscript.

If you use this dataset, please do cite the following papers:

Bonali et al., How Academics and the Public Experienced Immersive Virtual Reality for Geo-education. Geosciences.

Tibaldi, A.; Bonali, F.L.; Vitello, F.; Delage, E.; Nomikou, P.; Antoniou, V.; Becciani, U.; Van Wyk de Vries, B.; Krokos, M.; Whitworth, M. Real world–based immersive Virtual Reality for research, teaching and communication in volcanology. Bull. Volcanol. 2020, 82, 1–12.