Fig 1.
The spectrum of interdisciplinarity.
Note. The dashed arrow represents the cycle beginning again. For example, with the field of bioinformatics, a bioinformaticist incorporates tools/frameworks from another outside discipline.
Fig 2.
Models of interdisciplinary graduate education adapted from Pennington et al. [19].
Note. Adjacent, primary, and secondary refer to disciplines (e.g., primary discipline).
Fig 3.
The COMBINE model of integrated interdisciplinary graduate education.
Fig 4.
The COMBINE program.
Table 1.
COMBINE program objectives.
Table 2.
COMBINE program components.
Table 3.
Planned alignment between COMBINE objectives and components determined by the leadership team.
Table 4.
COMBINE student demographics upon starting the program.
Table 5.
COMBINE student and faculty disciplines.
Fig 5.
Student ratings of the usefulness of COMBINE components.
Note. Percentages were calculated out of the total number of students who participated in each component: Data Practicum Course (n = 23), Discipline Bridging 3-4-Credit Elective (n = 22), Research-in-Progress Seminar (n = 21), Career Development Workshop (n = 16), Literature Survey Seminar (n = 20), COMBINE Annual Symposium (n = 22), Network Analysis Course (n = 23), Peer-to-Peer Tutorial (P2P; n = 19), Outreach (n = 21), Discipline-Bridging Elective Seminar (n = 18). Only students in the second cohort were asked about the usefulness of Peer Mentoring (n = 10). Percentages may sum to greater than 100% due to rounding.
Table 6.
Student reports of whether COMBINE objectives were met by each component.
Fig 6.
Faculty advisor ratings of how helpful the COMBINE program was to their student in the three program objective areas.
Note. Percentages were calculated out of the total number of survey responses (n = 16). Percentages may sum to greater than 100% due to rounding.