Research and development methods (5cr)
Code: YA00CK14-3003
General information
- Enrollment
- 01.12.2025 - 28.02.2026
- Registration for the implementation has begun.
- Timing
- 12.01.2026 - 31.05.2026
- Implementation is running.
- Number of ECTS credits allocated
- 5 cr
- Unit
- KAMK Master School
- Teaching languages
- Finnish
- Seats
- 0 - 50
- Degree programmes
- Energy Transition Management
Realization has 8 reservations. Total duration of reservations is 24 h 0 min.
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Tue 10.03.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 17.03.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 24.03.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 31.03.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 07.04.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 14.04.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 21.04.2026 time 16:30 - 19:30 (3 h 0 min) |
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Tue 05.05.2026 time 16:30 - 19:30 (3 h 0 min) |
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Evaluation scale
Hylätty/Hyväksytty
Content scheduling
The first four lectures cover the research process, and the last four lectures cover research methods.
Objective
The aim of the course is that a student is able to plan, implement and report a working-life research and development project. The specific objective of the course is to prepare students to carry out the final thesis as a work-based research and development project.
Execution methods
Contact online days (distance learning), independent e-learning and exercises and development tasks
Accomplishment methods
Exercises and development tasks passed
Content
- the scientific basis, concepts and purpose of research and development
- research strategies
- use of research data and literature
- qualitative and quantitative research,
- development methods,
- reporting on the research development task - academic writing and
- thesis as a research and development project.
Location and time
Online lectures will be held from March 10 to May 5, 2026, on Tuesdays from 4:30 PM to 7:30 PM. The lectures will be recorded.
The submission dates for the exercises are: March 29 (topic analysis), April 26 (qualitative methods), May 17 (quantitative methods), and May 31, 2026 (methodology).
Materials
Materials announced by the teacher at the beginning of the course. Course materials can be found in the Reppu learning environment of Kajaani University of Applied Sciences.
Teaching methods
8 online lectures, four independent exercises (topic analysis; qualitative methods; quantitative methods; and methodology)
Employer connections
Not related to internship, no cooperation with the working life.
Exam schedules
No exam.
International connections
-
Completion alternatives
No optional methods of completion.
Student workload
The course requires about 135 hours of student work.
The lecture portion is 3 x 8 lessons. The remaining 111 hours are allocated to assessable assignments and independent study, of which the assignments on topic analysis, quantitative and qualitative methods require approx. 22 hours per assignment, and the assignment on writing methodology approx. 44 hours.
These figures are indicative, and the actual workload depends on how much time each student spends on each assignment.
Assessment criteria, approved/failed
o Passed: The student has satisfactorily completed the assessed assignments set for the course by the deadlines, which develop the student's knowledge and skills in planning, implementing, and reporting a research-based development task in working life.
o Failed: The student has not satisfactorily completed all the assessed assignments set for the course by the deadlines.
Assessment criteria, approved/failed
Approved: the student has satisfactorily completed the assessed tasks set for the course by the deadlines, which develop the student's knowledge and skills in planning, implementing and reporting on a research and development project in the workplace.
Fail: The student has not successfully completed all the assessed tasks set for the course by the deadlines.
Qualifications
Does not require previous studies on master level.
Further information
The purpose of the course is to provide tools for developing research-based activities in thesis work and professional life.
Instructions for the use of artificial intelligence – including its possibilities and limitations – will be covered in connection with the course assignments (based on Arene's AI recommendations).
Failure to follow the given instructions may result in failing the course. If this concerns only a specific assignment, the student must redo the assignment to receive a passing grade.