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Lecturer(s)
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Dzyuba Borys, doc. MSc. Ph.D.
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Boryshpolets Serhii, MSc. Ph.D.
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Course content
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The course is organised into two thematic blocks: 1. Research approaches across disciplines - differences between experimental, observational, quantitative, qualitative, computational and modelling approaches; - how different disciplines formulate research questions, generate evidence and evaluate uncertainty; - strengths, limitations and appropriate applications of different methodological approaches; - differences in terminology, assumptions and standards of evidence across disciplines. 2. Interdisciplinary research and collaboration - Interdisciplinary research and collaboration - identification of research questions that benefit from interdisciplinary approaches; - complementarity and compatibility of methods and evidence from different disciplines; - communication across disciplinary terminology, assumptions and methodological traditions; - integration of contributions from different disciplines into a coherent research approach; - development, in small interdisciplinary groups, of a short collaboration concept based on a shared research question; - presentation and discussion of the proposed collaboration during the final workshop.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Practical training, Group work, Case studies
- Class attendance
- 10 hours per semester
- Preparation for classes
- 16 hours per semester
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Learning outcomes
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The aim of the course is to broaden doctoral students' understanding of research approaches used across different scientific disciplines and to support effective interdisciplinary collaboration. The course introduces major methodological traditions and illustrates how different fields formulate research questions, generate and evaluate evidence, deal with uncertainty, and draw conclusions. Particular attention is given to the differences and complementarities among experimental, observational, quantitative, qualitative, computational, and modelling approaches. The course develops students' ability to understand methodological terminology outside their own field, recognise the strengths and limitations of different approaches, and communicate effectively with researchers from other disciplines. The course is designed as a flexible soft-skills course and may be taken at any stage of doctoral study. It is particularly useful for students engaged in interdisciplinary research, collaborative projects, or research questions that require integrating methods and perspectives from multiple scientific fields.
Upon successful completion of the course, students will be able to: - understand major differences between research approaches used across disciplines; - recognise the strengths and limitations of methods and evidence originating from different scientific fields; - identify research questions that may benefit from interdisciplinary collaboration; - combine complementary disciplinary perspectives into a coherent research concept; - contribute to the development and presentation of a potential interdisciplinary collaboration.
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Prerequisites
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Admission to a doctoral study programme. Previous or parallel participation in Research Data Management, Grant Proposal Preparation, and Open Science may be useful for interdisciplinary projects involving data sharing, reuse, integration, and collaborative project development, but is not required. No additional disciplinary prerequisites are required.
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Assessment methods and criteria
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Student performance assessment, Interview, Seminar work
Active participation in lectures, discussions and interdisciplinary group activities is expected. Students are required to complete the assigned preparatory reading and actively contribute to discussions comparing research approaches across disciplines. A central practical activity of the course will involve pairing or grouping students from different disciplinary backgrounds. Each group will identify a research question or problem of shared interest and develop a short concept for a potential interdisciplinary collaboration, considering how different methodological approaches could contribute to the same research objective. As a final exercise, each group will briefly present its proposed interdisciplinary research concept, including the contribution of the participating disciplines, possible methodological integration, expected advantages and potential limitations. The proposals will be discussed during the final workshop. The course introduces the importance of compatible, reusable and transferable research data in interdisciplinary collaboration. Practical principles of data organisation, documentation, interoperability, and sharing are further developed in Research Data Management and Open Science. The formal development of collaborative ideas into research proposals is further explored in the Grant Proposal Preparation module.
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Recommended literature
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Additional literature and INTERNET resources will be presented during lectures. .
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National Academies of Sciences, Engineering, and Medicine. The Science and Practice of Team Science. 2025.
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Newman, J. Promoting Interdisciplinary Research Collaboration: A Systematic Review, a Critical Literature Review, and a Pathway Forward. 2024.
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