Data-driven qualitative methodologies for forest scientists and foresters (5 cr)
Code: C-10088-LM00CO17-3003
General information
- Enrollment
- 01.08.2024 - 28.01.2025
- Registration for the implementation has ended.
- Timing
- 04.02.2025 - 30.04.2025
- Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Blended learning
- Institution
- University of Eastern Finland
- Teaching languages
- English
- Seats
- 0 - 1
- Course
- C-10088-LM00CO17
Evaluation scale
Five step scale
Objective
In forest sciences and development projects in forestry practice, results and practical conclusions are often drawn from varying qualitative information like interviews, written comments, workshop materials etc. Researchers and practitioners encounter overload of versatile materials, which make consistent and transparent conclusions difficult. After this course students understand different approaches of qualitative analysis. They are able to use modern software in collecting, handling, and analysing qualitative data effectively. Furthermore, they are able to compile sound and transparent interpretations and draw conclusions from their data analysis. The course develops the following generic skills: digitalization, ethics, critical thinking, identification and development of expertise, interaction and communication
Methods of completion
The course will be organised as multi-modal teaching. Lectures and exercises are partly organised as distance learning, and partly as hybrid teaching (simultaneously in the classroom and as distance learning). Exam in the computer classroom. The course can be completed entirely remotely if you acquire the software needed for the exercises.
Methods of completion
Lectures (20 h), exercises (30 h) and their reports (25%), individual project work (25%), exam (50%).
Content
Differences and common features of qualitative and quantitative research orientations. Data collection strategies and practices (prevailing documents vs. for-research materials, such as observation, interviews, focus-groups, nominal-group methodologies, open-ended responses in surveys). Introduction to data analysis practices: from messages via codes to interpretation. Technologies to support qualitative analysis: recording and transcribing, data management, computer-supported analysis. Reporting qualitative research understandably, transparently, and ethically. Examples of qualitative analysis in forest sciences and practices.
Materials
NVivo and Atlas.ti software. Eriksson and Kovalainen (2008, 2016). Qualitative Methods in business Research. Sage Publication Ltd.
Exam schedules
After course examinations electronical exam (Exam) until 30.4.2025.