Introduction to Social Science Methods

Course content

This is an introductory course on social science research methods. 

The course aims to give the students the methodological skills needed in later phases of their study. Further, it aims to provide students relevant skills in professional work life after academia - as practitioners of the introduced methods or as observers that can critically assess social science designs and data analysis.

Students will be introduced to qualitative data collection tools (interviews and fieldwork) as well as quantitative data collection tools (questionnaires).

Focus is on how to decide which methodological design should be used when, how to construct data collection tools and evaluate the quality of them. 

Techniques to analyse data will also be covered, as well as sampling and recruitment of respondents and informants.

The students will be introduced to and instructed in the use of digital tools used in social science methodology, such as data management tools and online survey tools. 

The course consists of two concurrent parts: a theoretical part and a practical part.

The theoretical part of the course gives an overview of common qualitative and quantitative social science methods and outlines their strengths and weaknesses. Further, it provides knowledge about the research process and allignment of research interest, research design and interpretations of results.

The practical part of the course consists of two group assignments, in which students develop their own research designs and conduct small research projects. 

The methodologies that are taught provide the students with general competences that is applicable to many study fields.


Msc Programme in Integrated Food Studies

Learning outcome

After completion of the course it is expected that the student:                                           


- Has knowledge of different types of quantitative and qualitative methods used in the social sciences and can describe their features.

- Understands how to align research question with choice of method and construction of data collection tool, as well as pertinent decision criteria when choosing methodological approach and specific tool(s).

- Has knowledge about a selection of techniques that can be used for qualitative and quantitative data analysis.



- Has the ability to develop research designs and data collection tools based on operationalization of research questions.  

- Has the ability to point out relevant analytical techniques within qualitative and quantitative methods for specific research questions. 

- Can make a basic statistical data analysis in Excel. 

- Has tried to work with an online survey tool. 



- Can evaluate the quality and the limitations of a research design, data collection tools and data.

- Can assess the validity of interpretations of qualitative and qualitative data.

 - Can engage in discussions with other researchers about choice of method, validity criteria and interpretations of data.

- Has practical experience with developing qualitative and quantitative data collection tools and report results using basic descriptive statistics and qualitative content analysis.

The course consists of lectures, practical exercises and group work.
During group work, the students will construct their own data collection tools, collect data and report results based on analysis and interpretation of the collected data.

Teaching material and curriculum will be announced prior to course start-up.

It is recommended that students have knowledge about basic descriptive statistics (e.g. means, standard deviation, frequencies).

Continuous feedback during the course of the semester
7,5 ECTS
Type of assessment
On-site written exam, 4 hours under invigilation
Type of assessment details
Students will receive a number of questions (some of which have sub-questions).
The questions aim to assess the students’ practical understanding and application of the main concepts and methods introduced during the course (e.g. choosing appropriate research design, including choice of method and sampling strategy; developing or choosing relevant questions for a questionnaire or interview guide; interpretation/analysis of qualitative data and output from statistical tables with latent variables; assessing the validity and reliability of a research output).

The course has been selected for ITX exam
See important information about ITX-exams at Study Information, menu point: Exams -> Exam types and rules -> Written on-site exams (ITX)
Exam registration requirements

During the course students will work on two assignments that must be approved in order to take the final exam.

The assignments must be carried out in groups.

All aids allowed

As the exam is an ITX-exam, the University will make computers available to students at the exam. Students are therefore not permitted to bring their own computers, tablets, calculators, or mobile phones.

Marking scale
7-point grading scale
Censorship form
External censorship

Same as the ordinary exam.

If 10 or fewer sign up, the reexam is an oral examination of 20-25 minutes, with 20 minutes preparation time and all aids allowed.

If the student has not gotten the two mandatory assignments approved, then the assignments must handed in individually, and they must be handed in three weeks prior to the deadline of registration for the re-exam. They must be approved before the exam.

Criteria for exam assessment

The assessment is based on the criteria given by the Learning Outcomes

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 45
  • Preparation
  • 65
  • Practical exercises
  • 10
  • Project work
  • 80
  • Guidance
  • 2
  • Exam
  • 4
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 1
42 students
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study Board of Food, Human Nutrition and Sports
Contracting department
  • Department of Food and Resource Economics
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Kia Ditlevsen   (3-73756c48716e7a7736737d366c73)

Kia Ditlevsen
Guest lecturers

Saved on the 19-02-2024

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