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2023/2024  KAN-CPOLO1043U  Advanced Mixed Methods

English Title
Advanced Mixed Methods

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory (also offered as elective)
Level Full Degree Master
Duration One Semester
Start time of the course Spring
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc i International Business and Politics, MSc
Course coordinator
  • Christoph Houman Ellersgaard - Department of Organization (IOA)
  • Megan Tobias Neely - Department of Organization (IOA)
Main academic disciplines
  • Methodology and philosophy of science
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 12-01-2024

Relevant links

Learning objectives
Students should:
  • Be analytical with regard to the types of inferences that can be derived from different types of data and analysis, including the ambiguity of complexities, complementarities and contradictions as they appear in mixed methods research in particular;
  • Become better consumers of mixed methods research, developing the skills both to gauge analytical potential and be cognizant of shortcomings and ambiguities in cutting edge social science research;
  • Show the ability to understand how different methods introduced in the course can contribute to answering a social science research question in collaboration as group;
  • Develop the ability to independently use and reflect on the validity and reliability of mixed methods in individual or group research projects;
  • Understand individual ethical responsibilities as researchers working with personal data;
  • Hone the skills to disseminate independent research findings to others in a way that concretely communicates both narrow analytical value added and the broader contribution of the research to the state of the art in scholarship and societal wellbeing
Course prerequisites
Our aim in this course is to open up further avenues from fundamental methods and give concrete examples of how to combine different approaches. Therefore, we expect students to be familiar with core concepts from quantitative and qualitative methods and have experience applying these methods separately in projects or assignments. The course will rely on the statistical software R, but no prior knowledge of the software is assumed.
Joint Exam in Advanced Quantitative Methods and Advanced Mixed Methods:
Exam ECTS 15
Examination form Home assignment - written product
Individual or group exam Group exam
Please note the rules in the Programme Regulations about identification of individual contributions.
Number of people in the group 2-5
Size of written product Max. 25 pages
Page breakdown is
1-2 students max 20 pages
3-5 students max 25 pages
Assignment type Written assignment
Release of assignment An assigned subject is released in class
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure

It is possible to write the exam individually without an exemption.


The exam will be released in 2 parts on Canvas. Hand in will be specified on Digital Exams. 
All learning objectives for both courses will be relevant in the exam and its grading.

Course content, structure and pedagogical approach

The purpose of Advanced Mixed Methods is to make students better consumers and producers of multi-method research. To that end, we will 1) discuss how fundamental building blocks of social scientific research can speak to and qualify one another 2) learn how to apply and combine various concrete methods such as case studies, content analysis, process tracing and relational quantitative methods such as social network analysis, correspondence analysis & sequence analysis and; 3) critically examine and learn from prominent examples of mixed methods in existing research.


Reflecting these learning priorities, the course aims to give students practical experience incorporating mixed methods into their own research design. We will discuss the uses of different types of data in making inference regarding a research question. The goal is to both give students new tools to work with and the ability to consume and assess their past and current application in political research. Each method will be introduced in a set of lectures; then students will get the chance to work with the methods themselves in smaller workshops. These workshops will serve as the foundation of a final research paper - in which mixing methods is a requirement - which functions as the exam assignment for the course.


In relation to Nordic Nine

Advanced Mixed Methods introduces students to a variety of methods, with the aim of teaching them to be analytical and data-driven in making inferences while retaining awareness of the limits, ambiguities, and complexities of such work (NN2). Not only does this make students better producers of knowledge, it also makes them better consumers of it, bolstering their ability to assess the challenges facing humanity and the pathways towards resolving them, incuding the trade-offs and ethical dilemmas this may involve (NN3; NN5; NN7). Pedagogically, the course centers around collaborative group work and mutual learning and teaching within these groups (NN6; NN8).

Description of the teaching methods
The course will be taught in-person. We will focus on making methods concrete by letting students read the excellent examples of existing scholarship while also working on a course-long project in the workshops, which can be used in the exam project. Students are expected to present and share their work with other students during the workshops.
Feedback during the teaching period
The course offers continuous feedback and establishes an ongoing dialogue with students. Particular feedback includes: a) direct feedback on learning attainment during workshops with methodological training; b) the use of in-class quizzes in live lecture sessions; c) focused feedback on ‘work in progress’ presentations of arguments and evidence; d) engagement via regular office hours in person or online. Feedback is given to explain how particular analysis, answers and arguments can be improved.
Student workload
Lectures 24 hours
Workshops 12 hours
Course preparation. Includes: readings for lectures and exercises work on activities (homeworks) 92 hours
Exam 80 hours
Last updated on 12-01-2024