AGDK14017U Interdisciplinary Field Research

Volume 2025/2026
Education

MSc Programme in Global Development

Content

This course gives students an opportunity to prepare, implement and report on field research in interdisciplinary groups. The course emphasizes qualitative and quantitative methods commonly used in the social sciences. Students will experience the difficulties, trade-offs, limitations and possible benefits of applying various methods in real world situations.

The main objective of this course is for students to gain experience of the research process in its entirety: from identifying and formulating a research question; preparing a research design; planning and implementing data collection, analyzing data and writing an academic report. The course gives students the possibility to appreciate how different approaches to data collection affect the findings obtained, and to reflect upon the material gained (or not gained) from the specific methods used. Additionally, an important aim is to create awareness of research ethics.

The course includes preparing a (small scale) research project and two weeks of field research in a context of relevance to themes of global development. With point of departure in a specific field site and logistical setup, students work in groups refining their research design and applying relevant methods in order to collect the data necessary to answer their research questions. Based on the field work, the groups write a report on the findings of their research, which form part of the exam along with an individual essay reflecting on the methods used and empirical findings.

The trip is mandatory and the cost is app. 12.000 - 15.000 DKK which is not included in the program.

Learning Outcome

The learning outcomes of the course relate both to design and implementation of research in a complex and messy field situation and to knowledge and reflection upon social science methods and ethics.

 

Knowledge:

  • identify, define and justify a set of research questions  
  • describe and define central concepts of relevance to social science data collection and interpretation

 

Skills:

  • design a research plan for field study, incorporating relevant methods 
  • collect, process and analyze relevant data during and after fieldwork 
  • clearly communicate research findings

 

Competences:

  • critically discuss the different kinds of data and forms of knowledge obtained by alternative data collection and analytical methods, including how these methods shape research findings 
  • reflect on ethical concerns in relation to empirical research
The course will be undertaken on a full-time basis over 8 weeks. This will involve 3 weeks of preparation with methods training and research preparation, including the formulation of a research design; 2 weeks of field work; and 3 weeks of report writing and a final evaluation. Throughout the course, students work in groups to design, undertake and report on their own piece of field research. Students will receive feedback on their work-in-progress throughout the course in supervision sessions. Before fieldwork students receive feedback on their proposals, during the field trip they receive feedback on their methodological approach, and after field work, they receive feedback on their drafts for their research reports.
  • Category
  • Hours
  • Lectures
  • 40
  • Preparation
  • 120
  • Field Work
  • 100
  • Seminar
  • 20
  • Exam Preparation
  • 120
  • Exam
  • 20
  • Total
  • 420
Continuous feedback during the course of the semester
Credit
15 ECTS
Type of assessment
Home assignment
Type of assessment details
Home assignment in groups of maximum 20 pages with individual contributions marked out.
Examination prerequisites

To qualify for the exam, the student must participate in the oral feedback seminar, which is held the last days of the field work in Bolivia.

Aid
All aids allowed

Use of Generative AI in Written Examinations at Global Development

At the MSc in Global Development, the use of generative AI software and Large Language Models (AI/LLMs), such as ChatGPT, is permitted in all written examinations categorized as ‘All Aids Allowed’. The use of generative AI/LLMs must, however, comply with the conditions outlined below:

 

  1. Generative AI/LLMs must never be used to generate new and original content, as written examinations are expected to reflect the student’s own knowledge and understanding of the subject matter.
  2. However, students are allowed to use generative AI/LLMs as an exam aid to enhance the presentation of their own original work, for example, for text editing, argument validation, or improving statistical code.

 

Regardless of how AI/LLMs are used, students must clearly disclose their use in an appendix, which will not count towards the overall length of the examination submission. This appendix must specify how the AI/LLMs were used and for what purpose(s).

 

Please note the specific requirements for quotations marks and source referencing when using GAI as an exam aid. Failure to provide proper attribution will be considered plagiarism.

Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assesment

Students are assessed to the extent to which they master the learning outcome for the course.

 

To obtain the top grade “12”, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material and can make use of the knowledge, skills and competencies listed in the learning outcomes. Furthermore, the student must apply a mixed methods/​​interdisciplinary approach to obtain the top grade “12”.

 

To obtain the passing grade “02”, the student must in a satisfactory way be able to demonstrate a minimal acceptable level of the knowledge, skills and competencies listed in the learning outcomes.”