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

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

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

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

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

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

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

Methods A total of 249 CTs

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)

Results - Quantitative Method Purposive sampling of interview candidates Trad Prog Multidisc Prog Specialized Prog Students Interdisciplinarity

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!

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

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

“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

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.”

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.”

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.”

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

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.”

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

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), 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 : Borrego, M., & Newswander, L. K. (2010). Definitions of interdisciplinary research: Toward graduate-level interdisciplinary learning outcomes. The Review of Higher Education, 34(1), Stokols, D. (2012). Training the next generation of transdisciplinarians. Enhancing Interdisciplinary Communication. Thousand Oaks: Sage.

Thank you María del Carmen Calatrava Vienna University of Technology Mary Ann Danowitz North Carolina State University