1. Contrasting Approaches to Interdisciplinarity at Doctoral Level Students’ experiences María del Carmen Calatrava Vienna University of Technology Mary Ann Danowitz North Carolina State University

2. Outline Need for the study Context & Doctoral Programs Methods Results Sense making and implications

3. Need for the study Interdisciplinary approaches needed to solve complex real-world problems European universities responded creating new forms of doctoral education (i.e., doctoral schools and colleges) Little knowledge on interdisciplinary research (IDR) in such new doctoral programs

4. Context & Doctoral programs Parallel programs in the same faculty: Traditional European Multidisciplinary PhD School Specialized PhD College Structured PhD

5. Traditional EuropeanMultidisciplinary CS programSpecialized program Loosely regulated -Admissions -Courses Majority univ and project assist Minority self-funded / scholarship Highly regulated ‐Admissions ‐Courses ‐Milestones Co-organized by multiple faculties Covers 1 area Major area courses Project ass. + scholarship PS Faculty S All 5 research areas in CS faculty Major and 2 nd area courses Scholarship 529 Students43 Students8 Students Research group S

6. Methods Mixed methods design: 1.Quantitative: Bibliometric analysis interdisciplinarity – Examine students’ scientific activity – Identify interdisciplinary students 2.Qualitative: – Factors and processes allowing IDR

7. Quantitative Method Publication data extraction: # students: 223 # students’ publications: 1746 # students’ references: 16817

8. Methods A total of 249 CTs

9. Quantitative Method Top-down approach – Disciplines defined in an existing taxonomy – Interdisciplinarity  incorporates the work of 2 or more disciplines [1]. Ref1Ref2Ref3Ref4Ref5Ref8 Ref6 Ref7 CT1 CT2CT3 CT4 [1] National Academies report. Facilitating Interdisciplinary Research. (2005)

10. Results - Quantitative Method Purposive sampling of interview candidates Trad Prog Multidisc Prog Specialized Prog 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Students Interdisciplinarity

11. Using Rao-Stirling and Porter’s matrix Difficult to believe! Most of their references are in Computer Science, Engineering, Mathematics, Science & Technology. Only 9 references out of 331 are in different fields!

12. Qualitative Method Semi-structured interviews Questions developed from the literature 50-80 minutes 9 Participants Experiences Supervision Networking Publications Doctoral program Faculty Research group Opportunities Difficulties Interdisciplinarity Collaboration Expectations Background Methods

13. Results – Qualitative Method Factors and processes allowing IDR: One would expect influence from: Courses different disciplines Participation of different faculties Interdisciplinary research projects  interdisciplinary thinking Individual background characteristics Program structure and processes

14. “For me it is not so important that I have a big technological invention, but that I solve [a real-world problem]. For me it is not just a use case that I would easily exchange for some other problem.” Results – Qualitative Method Individual background characteristics Values

15. Results – Qualitative Method Individual background characteristics Values Motivation “I suddenly identified my field for me because it is the intersection of computation, which is my profession and my interest, and [other discipline] which is also my passion and my interest.”

16. Results – Qualitative Method Individual background characteristics Values Motivation Skills and knowledge “I have always been interested in [other discipline]. I have been working in [other discipline] for my master's thesis and a job that I had previously.”

17. Results – Qualitative Method Program structure & processes Autonomy “The doctoral school gives you a lot of independence, because no one is telling you what to do. You choose what you want to do. […] It is possible to do a PhD in these areas and this is where I contribute.”

18. Results – Qualitative Method Program structure & processes Autonomy Funding Project assistantship: Topic and contribution fixed by project University assistantship: Topic aligns with research group Scholarship and self-funding: Topic agreed with supervisor

19. Results – Qualitative Method Program structure & processes Autonomy Funding Supervision “My supervisor is not a hard-core disciplinary person, so that's makes it easier for me. […] He encourages us... he finds it very valuable that we combine two topics, one from IT and one from the real world.”

20. Sense making and implications Courses/faculty from different disciplines is insufficient to foster IDR. Greater attention should be directed to: – Students’ characteristics and antecedent experiences – Supervision supporting IDR – Funding – Interdisciplinary project work beyond one faculty

21. Key References European University Association. (2007). Doctoral programmes in Europe’s universities: Achievements and challenges. Brussels, Belgium. Nyhagen, G. M., & Baschung, L. (2013). New organizational structures and the transformation of academic work. Higher Education, 66 (4), 409-423. Wagner, Caroline S., et al. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal of Informetrics 5.1 :14-26. Borrego, M., & Newswander, L. K. (2010). Definitions of interdisciplinary research: Toward graduate-level interdisciplinary learning outcomes. The Review of Higher Education, 34(1), 61-84. Stokols, D. (2012). Training the next generation of transdisciplinarians. Enhancing Interdisciplinary Communication. Thousand Oaks: Sage.

22. Thank you María del Carmen Calatrava Vienna University of Technology carmen.calatrava@tuwien.ac.at Mary Ann Danowitz North Carolina State University mdanowi@ncsu.edu