Contrasting Approaches to Interdisciplinarity at Doctoral Level Students’ experiences

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 samefaculty: • Traditional European • Multidisciplinary PhD School • Specialized PhD College Structured PhD

5. TraditionalEuropean MultidisciplinaryCS program Specializedprogram Research group Faculty S S S P • Highly regulated • Admissions • Courses • Milestones • Loosely regulated • Admissions • Courses • Majority univ and project assist • Minority self-funded / scholarship • Co-organized by multiple faculties • Covers 1 area • Major area courses • Project ass. + scholarship • All 5 research areas in CS faculty • Major and 2nd area courses • Scholarship 529 Students 43 Students 8 Students

6. Methods Mixed methods design: • Quantitative: Bibliometric analysis interdisciplinarity • Examine students’ scientific activity • Identify interdisciplinary students • 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]. Ref7 Ref1 Ref2 Ref3 Ref4 Ref8 Ref5 Ref6 CT4 CT1 CT2 CT3 [1] National Academies report. Facilitating Interdisciplinary Research. (2005)

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

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

12. 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

13. Results – Qualitative Method Individual background characteristics • Values “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.”

14. 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.”

15. 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.”

16. 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.”

17. 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

18. 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.”

19. 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

20. 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.

21. 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