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| Title |
Elective course: Research Methods and Writing
|
| Semester |
E2025
|
| Master programme in |
Digital Transformation / Computer Science
|
| Type of activity |
Course |
| Mandatory or elective |
Elective |
| Teaching language |
English
|
| Study regulation |
Read about the Master Programme and find the Study Regulations at ruc.dk |
| REGISTRATION AND STUDY ADMINISTRATIVE | |
| Registration |
You register for activities through stads selvbetjening during the announced registration period, which you can see on the Study administration homepage. When registering for courses, please be aware of the potential conflicts and overlaps between course and exam time and dates. The planning of course activities at Roskilde University is based on the recommended study programmes, which should not overlap. However, if you choose optional courses and/or study plans that goes beyond the recommended study programmes, an overlap of lectures or exam dates may occur depending on which courses you choose. |
| Number of participants |
|
| ECTS |
5
|
| Responsible for the activity |
Raluca Alexandra Stana (raluca@ruc.dk)
|
| Head of study |
Nina Boulus-Rødje (ninabr@ruc.dk)
|
| Teachers |
|
| Study administration |
IMT Registration & Exams (imt-exams@ruc.dk)
|
| Exam code(s) |
U60595
|
| ACADEMIC CONTENT | |
| Overall objective |
The purpose of elective courses is to give the student opportunitities to specialize within a specific subject area, where the student acquires knowledge, skills and competences in order to translate theories, methods and solutions ideas into their own practice. |
| Detailed description of content |
Every successful research endeavor begins with a sense of curiosity about the world around us. But the question arises: how does one pinpoint that pivotal inquiry worth a semester's pursuit in exploration and analysis? This course is designed to help you navigate through the nuances of qualitative research methods, empowering you with the skills to identify, explore, and endeavor to answer such important research questions. An important facet of this course is the development of analytical strategies pertinent to qualitative data, fostering skills in efficient comprehension of scientific literature and the formulation of scientific arguments. Through this exploration of qualitative research methods, students will be equipped with the foundational knowledge and practical skills necessary to embark on their research journeys with confidence and academic integrity. Qualitative research, with its many types of motivations and objectives, demands a thoughtful consideration of the domain of study, whether it be probing into a specific field, testing theoretical frameworks, or addressing organizational challenges. Integral to this process is the positioning of one's research within the broader academic discourse, articulating its significance to existing literature, and delineating its unique contributions. This course delves deep into qualitative research traditions and methodologies. We will explore a spectrum from traditional literature reviews and qualitative studies to theoretical explorations. A critical component of our discussions will focus on how to critically assess and select the methodology that best aligns with your research goals, and the implications of these choices on your study. Central to qualitative research is the art of data collection and analysis, and as such, we will examine a variety of data gathering and analysis techniques and strategies. Furthermore, we will scrutinize evaluation techniques essential for maintaining scientific rigor, such as ensuring validity and reliability, recognizing and mitigating bias, and the role of triangulation. Additionally, how do we best discuss our findings in the broader context of academic discourse, and how do we identify and articulate our research contributions? After completing this course, the student will be able to:
|
| Course material and reading list |
A mixture of literature addressing the various topics in the course. Please consult Moodle for the final literature list. |
| Overall plan and expected work effort |
Study effort: The course's 5 ECTS correspond to a total of 135 hours workload with:
|
| Format |
Learning activities: The teaching is designed as a workshop, combining classic lectures and exercises. |
| Evaluation and feedback |
Evaluation form to be filled out (anonymously) plus open discussion on the last course day. Feedback will be continuously collected during the semester. |
| Programme |
|
| ASSESSMENT | |
| Overall learning outcomes |
After completing this course, students will be able to:
|
| Prerequisites |
|
| Form of examination |
Individual oral exam based on a written product
The character limit of the written product is maximum48,000 characters, including spaces. The character limits include the cover, table of contents, bibliography, figures and other illustrations, but exclude any appendices. Time allowed for exam including time used for assessment: 20 minutes. The assessment is an overall assessment of the written product(s) and the subsequent oral examination. Permitted support and preparation materials for the oral exam: All. Assessment: 7-point grading scale Moderation: Internal co-assessor. |
| Form of Re-examination |
Samme som ordinær eksamen / same form as ordinary exam
|
| Type of examination in special cases |
The same form as ordinary exam |
| Examination and assessment criteria (implemented) |
The assessment is an overall assessment of the written product and the subsequent oral examination and the student will be assessed based on the extent to which they are able to fulfill the following criteria:
and whether the written report meets all the formal requirements. On the use of GAI for this course: In this course, generative AI aids (GAI) are permitted in the work with the exam if the use is declared. You must clearly declare how you have used generative artificial intelligence (GAI). This can be included as part of a methodology section or as a short statement at the end of your exam paper. This means that you must describe how you have used GAI, e.g. for the preparatory work on the assignment, to ask questions and search for information, to receive feedback and criticism on your text, to carry out proofreading or to improve language and readability. It is important that you actively relate to your choice of tools in this way, as it is part of the entire process of creating the assignment, and thus part of your scientific method and professional communication. The use of any specific text that is GAI-generated requires citation, just as when using all other sources from which direct quotations are used. In the library's guide, you can see more about how to cite AI and how you can account for your use of GAI. However, ordinary spell checking and other language suggestions, such as those known from Word or other word processing programs, as well as programs for writing minutes and transcription, are permitted to be used in all written exams and do not need to be declared. The use of generative artificial intelligence (GAI) must always take place within the framework of Roskilde University's ‘Guidelines for using generative artificial intelligence in written exams.’ Read the guidelines here. |
| Exam code(s) | |
| Last changed | 09/09/2025 |
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