Knowledge and Communication

This Master's explores how knowledge and its communication shape society. You will study how knowledge is produced, processed, shared and used—not only scientific knowledge but also everyday and alternative forms of knowing—and examine the societal effects of those processes. The programme takes a broad, interdisciplinary view of “knowledge” and pays close attention to the ways different actors and contexts influence what counts as knowledge.

A distinctive element of the degree is its focus on data and computational approaches: by specialising in computational communication science you learn how to link large data sets with questions about knowledge, and how to organise, analyse and interpret knowledge in data form. Coursework combines topical issues in knowledge communication with methodological training, preparing you to work with digital traces, quantitative text and social data, and related analytical tools.

Three features set this programme apart within the Department of Communication: a sustained focus on knowledge communication, integration with other streams of communication science, and a strong emphasis on computational methods. It is also the department’s first Master's taught in English, making it accessible to an international cohort and preparing graduates for careers in research, public communication, policy advice, data-driven journalism, and other roles where understanding and managing knowledge flows are essential.

Admission essentials (confirm details on the official programme page)

• Check the programme’s official webpage for up-to-date entry requirements, application deadlines and fee/visa information.
• Typical application materials usually include a completed Bachelor’s degree (or equivalent), academic transcripts, a curriculum vitae and a motivation letter.
• Proof of English proficiency is required for non-native speakers (see accepted tests and minimum scores on the programme site).
• Some applications may request letters of recommendation or samples of academic work—verify exact document requirements on the programme’s admissions page.

Curriculum overview

This MA is a consecutive, research-focused programme that builds progressively across four semesters. The first semester establishes core knowledge in knowledge and science communication and strengthens empirical social research methods. Compulsory modules anchor these foundations: Module 1 (Concepts in Knowledge and Science Communication) introduces key definitions, theories and multi-/interdisciplinary perspectives (e.g., psychology, education), while Module 3 (Knowledge Transfer) focuses on the practical mechanisms of communicating knowledge. Module 2 (Quantitative and Qualitative Methods of Empirical Research) expands students’ methodological bases, building on the quantitative and qualitative skills they bring from their BA studies.

In the second and third semesters students deepen specialist and methodological competences and carry out an extended research project. Module 5 introduces computational communication science, giving students tools to generate insight from data, while Module 6 (Specific Aspects of Knowledge Communication I) and later Modules 7–9 (including Specific Aspects II) allow further specialisation. The central Research Module (Module 4) runs across semesters two and three: students design, plan and implement a comprehensive empirical study (research questions, instruments, data collection and analysis) — the research seminar meets for four hours per week to allow sufficient time for project work. The fourth semester is dedicated to an independent empirical Master’s thesis that builds directly on the research experience.

Key learning outcomes

• Advanced understanding of theories, concepts and models in knowledge and science communication, with interdisciplinary perspectives.
• Strong empirical research skills: ability to design studies, select and apply quantitative and qualitative methods, collect and analyse data, and interpret and present findings.
• Practical competence in knowledge transfer and science communication practice.
• Applied data skills through computational communication science, enabling students to generate knowledge from digital data sources.
• Capacity for independent, empirical research culminating in a Master’s thesis.

Program requirements (concise)

• Programme is consecutive: applicants are expected to have basic knowledge of communication studies and social science research methods from a relevant BA.
• Completion of core compulsory modules in Semester 1 (Modules 1–3) to establish theoretical and methodological foundations.
• Completion of the Research Module (Module 4) which spans Semesters 2 and 3 and includes a 4-hour-per-week research seminar.
• Participation in specialist modules (Module 5–6 in Semester 2; Modules 7–9 in Semester 3) to deepen disciplinary skills.
• Submission of an independent empirical Master’s thesis in the fourth semester.

For detailed module descriptions, semester schedules and assessment formats, please consult the programme’s official website or downloadable module catalogue.

Graduates are prepared for roles that require translating knowledge into public, institutional or policy-relevant formats and for positions that combine data skills with communication expertise. Typical career paths include science and research communication, knowledge transfer and outreach for universities or research institutions, data-driven roles in media organisations, policy and public affairs units, NGOs, and consultancies.

The programme’s computational and empirical training also opens opportunities in research institutions and departments that use computational social science methods—such as data analysis, research design, monitoring and evaluation, and evidence synthesis roles—where graduates can bridge data, expertise and public communication.