Data Management and Data Sharing Training in Social Science Graduate Programs, United States, 2017-2018
- Doonan, Ashley (University of Michigan. Institute for Social Research. Interuniversity Consortium for Political and Social Research)
AbstractThe Data Management and Data Sharing Training in Social Science Graduate Programs collection includes data gathered as part of an exploratory analysis of current graduate training practices for data management and data sharing in the social science fields. The exploratory analysis was conducted in two stages.
In the first stage, a survey of a select set of social science graduate programs was conducted to assess the inclusion of data management and sharing-related content, as well as the experiential development of these skills as a result of participating in the program. The final sections of the survey asked respondents to assess graduates’ skills in research and data management and sharing upon graduation. The survey was sent to program directors, administrators, and other representatives designated as the contact person for the program on their university website. The survey was administered to 150 graduate programs across six social science disciplines, and used a mix of closed and open-ended questions focused on the extent to which programs provide such training and exposure. The survey data is included in the file DS1_Graduate_Program_Survey_Data.sav.
In the second stage of the study, a conducted a syllabus analysis was conducted to further explore the content of graduate programs beyond self-report. Syllabi were gathered to conduct a text-analysis to explore how prominently data sharing or data management material appears in the syllabi for research related courses, if at all, as a means of determining the degree of instruction time devoted to the material. Syllabi were sought for a random sample of 140 programs from seven social science disciplines. The dataset was constructed through text analysis of the syllabi, looking for several key words and phrases that indicated both explicit and implicit inclusion of data management and sharing topics in coursework. Researchers searched through the syllabi to highlight predetermined keywords, highlighting both exact mentions of phrases like “data collection” and “data analysis,” but also synonymous phrases such as “gathering of data.” Additionally, implied use of the word “data,” such as in a list of actions applied to data, were also included as multiple unique mentions (e.g. “data collection, management, and analysis” would be considered three mentions of “data”). Lastly, syllabi were read to identify course requirements of research projects, assignments requiring data collection, or other types of research related presentations. The syllabi analysis data is included in DS2_Syllabi_Analysis_Data.sav
WeightingThese data are unweighted.
2017-01-01 / 2018-12-31Time Period: Sun Jan 01 00:00:00 EST 2017--Mon Dec 31 00:00:00 EST 2018
2017-02-21 / 2017-04-26Collection Date(s): Tue Feb 21 00:00:00 EST 2017--Wed Apr 26 00:00:00 EDT 2017 (Graduate Program Survey Data)
2018-02-26 / 2018-05-11Collection Date(s): Mon Feb 26 00:00:00 EST 2018--Fri May 11 00:00:00 EDT 2018 (Syllabi Analysis Data)
DS1 Graduate Program Survey:
A sampling frame of randomly selected graduate programs from six of the selected social science fields was developed using the graduate school directory gradschools.com. Economics was not included in the original survey. For each of the six disciplines, a simple random sample of 25 programs matching the inclusion criteria was gathered. The survey was sent to a total of 150 programs, and the final dataset includes 24 responses.
The respondent pool was primarily comprised of program directors and program coordinators. Other respondent positions included department chairs, program faculty, and academic coordinators. The 24 programs averaged 54 students for typical enrollment, and the number of full-time faculty in these programs ranged from 2 to 35, with a median of 7 faculty members. The majority of programs offered both masters and doctorate degrees.
DS2 Syllabi Analysis:
The sampling frame of graduate programs for the syllabi analysis was constructed using the same method and inclusion criteria employed for the survey, with the exception of including economics programs. Programs were randomly sampled within each discipline, selecting 20 from each of the seven fields, for a total of 140 programs. For each program included in the sample, one course related to conducting research from their listed degree requirements was identified and a syllabus from 2010 or later was attempted to be obtained. Selected courses fell into five categories related to learning how to conduct research: 1) Research methods courses; 2) qualitative research or data courses; 3) quantitative research or data courses; 4) statistics or analysis courses specific to the discipline; and 5) research design courses. Syllabi for identified courses were obtained from publicly available sources, and were successfully collected for a total of 50 programs.
Most of the programs with syllabi available were doctoral, and a quarter of syllabi came from master’s level programs. The corpus of syllabi consists primarily of documents from political science and economics courses, with the fewest syllabi from history programs. The vast majority of syllabi came from either the research methods course category or the statistics or analysis course category.
Update Metadata: 2019-07-10 | Issue Number: 1 | Registration Date: 2019-07-10