Data-driven qualitative methodologies for forest scientists and forestersLaajuus (5 cr)

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

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.

Further information

The course is taught every year (spring term). Lectures in English, exercises and exam in English or in Finnish. In study programs of Forest Sciences, the course (or similar course elsewhere) is a pre-requirement for thesis applying qualitative methodologies. The number of participants for the course may be limited due to number of computers available in the IT room. M.Sc. and doctoral students at the School of Forest Sciences are prioritized; especially students who are doing or are planning to do their thesis applying qualitative methodologies.

Execution methods

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.

Accomplishment methods

Lectures (20 h), exercises (30 h) and their reports (25%), individual project work (25%), exam (50%).