Course code REIS310

REIS310 Social Science Research Methods in Nature-Based Tourism, Outdoor Recreation and Natural Resource Management

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Showing course contents for the educational year 2022 - 2023 .

Course responsible: Hilde Nikoline Hambro Dybsand
Teachers: Lovisa Ulrica Molin, Øystein Aas, Stian Stensland
ECTS credits: 10
Faculty: Faculty of Environmental Sciences and Natural Resource Management
Teaching language: NO
(NO=norsk, EN=Engelsk)
Limits of class size:
35
Teaching exam periods:
The course starts at the spring semester. The course involves teaching/grading during the spring semester. 
Course frequency: Annually
First time: Study year 2022-2023
Last time: 2023V
Preferential right:
M-REIS
Course contents:

The course enables you to plan and carry out a master's thesis or research project using social science methods for nature-based tourism, outdoor recreation and natural resource managemnet (including forestry or renewable energy). The course deals with research design / method, data collection and analysis, and is built around the requirements and skills set for the students' master's thesis using a qualitative (eg interview) or quantitative (eg questionnaire) method. From the design of a researchable problem via the choice of method and implementation of data collection to processing, analysis and presentation of results.

Statistical analyzes are reviewed, such as the most commonly used parametric and non-parametric tests, analysis of variance (ANOVA), factor analysis and regression. Furthermore, qualitative data, digital data (incl. Images) and observational studies are analyzed.

The course contains two assignments:

A group assignment based on available quantitative data, where students will analyze, interpret and then write a report.

An individual assignment that consists of creating a project plan for completion of the master's thesis, ie first a brief introduction to the topic and a small outline of an intended problem, and then a more detailed justification for the choice of method and a more detailed description of the chosen method.

Learning outcome:

Knowledge: The student shall be able to plan a master's thesis or research studies using a social science method. The student should be able to describe and evaluate possibilities and limitations of the most common quantitative and qualitative methods used in social science research. Furthermore, be able to assess which method should be chosen for different issues, and how the design of a study determines which conclusions can be drawn.

Skills: Students shall be able to design and use different methods for data collection (interview, questionnaire, digital data, observation, etc.) for qualitative and quantitative analyzes. Students shall be able to use questionnaire tools and programs for analyzes of qualitative and quantitative data. Furthermore, be able to apply statistical analyzes, and analyze digital data (incl. Images) and observational studies.

General competence: The student shall be able to practice good research ethics in the organization and implementation of a research project / master's thesis. Furthermore, be able to conduct empirical research and collaborate with researchers.

Learning activities:
The course is based on a combination of lectures, exercises, group and individual work. 
Teaching support:
Teachers are available during lectures and exercises, or upon appointment.
Syllabus:
Literature will be uploaded in the canvas room.
Prerequisites:
Basic statistics, STAT100 or equivalent.
Recommended prerequisites:
Mandatory activity:
Compulsory attendance at exercises, and presentation of individual project plan
Assessment:
Assessment of an individual assignment and a group assignment. Both must be passed in order to pass the course.
Nominal workload:
250 hours.
Entrance requirements:
General study competense (GSK).
Type of course:
2 x 2 hours of lectures/exercises per week.
Examiner:
An external examiner sets the grade on the group paper in cooperation with an internal examiner. Internal sensors grade the individual paper.
Examination details: :