| Summary: | Gender disparity is an issue among the many science, technology, engineering, and mathematics (STEM) fields. Although many previous studies examine gender issues in STEM as an aggregate discipline, there are unique issues to each of the fields that are considered STEM fields. Some fields, such as physics, have fewer women graduating with degrees than other fields. This suggests that women's experiences vary by STEM field. The majority of previous research also examines gender and other disparities at either the nationwide or individual level.
This project entailed social network analysis through survey and interview data to examine a single physics department's doctoral students in order to provide a comprehensive look at student social experiences. In addition to examining gender, other demographic variables were studied to see if the results are truly associated with gender; these variables include race/ethnicity, year in program, student type, relationship status, research type, undergraduate institute, and subfield. Data were examined to determine if there are relationships to social connections and outcome variables such as persistence in completing the degree and the time to degree. Data collected on faculty were used to rank faculty members; data such as h-indices and number of students graduate over the past 5 years were collected. Fifty-five (55) of 110 possible participants completed the survey; forty-three are male, and twelve are female. Twenty-eight of the fifty-five survey participants were interview; twenty-three are male, and five are female.
Findings for peer networks include that peer networks are established during the first year and do not change drastically as one progresses in the program. Geographic location within the campus affects socializing with peers. Connections to fellow students are not necessarily reciprocated; the maximum percentage of reciprocated connections is 60%. The number of connections one has varies by network purpose, with students having more connections for the more social purposes. Students are isolated when working on their research, even in their early years. Research discussion does not occur, unless one is providing casual updates to a peer.
Findings for student-faculty networks indicate that these relationships are important but complicated. Advisor selection is often done casually, even when one is switching advisors. Faculty have a lot of influence on the doctoral students such as motivating research collaborations among students or aiding in the job search. Most doctoral students feel as though there is a power dynamic that hinders them from socializing with faculty and thus, are not close to the faculty. Opportunities to develop stronger relationships and for professional development are often missed. The total number of peer and faculty ties has significant relationships to whether a student considers leaving the program.
Analyzing the qualitative and quantitative data through demographic variables showed how complex these experiences are. All demographic variables indicated there are statistically significant differences in social experience among the groups, though the extent varies. The year in program variable showed the most differences among cohort years, primarily with those in the fifth year. While gender showed few differences, women tended to have more homophilous peer networks than men and women tended to have more connections to higher prestige faculty. The race/ethnicity, student type, undergraduate institute, subfield, and relationship status variables produced few statistically significant results. Peer networks have statistically significant differences in homophily when examining research type.
The regression model suggests that being female, having a higher year in the program, and/or completing undergraduate studies from a liberal arts college increases the time to degree. Being in a relationship (dating or married) and/or working on experimental research decreases the time to degree. Only research peer network and departmental information network variables remain in this model.
Suggestions for further research for both physics/STEM education and social network analysis are included. Suggestions for ways in which the Jonas University physics department can improve its climate are also included. Although these suggestions are written based upon the Jonas University data, they may be applicable to other physics/STEM graduate programs.
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