Future research (5 cr)
Code: MU00DT24-3015
General information
- Enrollment
-
07.04.2025 - 21.04.2025
Registration for introductions has not started yet.
- Timing
-
01.09.2025 - 31.12.2025
The implementation has not yet started.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- RDI portion
- 2 cr
- Mode of delivery
- Contact learning
- Unit
- Department of Culture
- Campus
- Kouvola Campus
- Teaching languages
- Finnish
- Seats
- 20 - 40
- Degree programmes
- Degree Programme in Bioproduct Design
- Degree Programme in Graphic Design
- Degree Programme in Fashion and Costume Design
- Degree Programme in Interior Architecture and Furniture Design
- Teachers
- Laura Hakanen
- KY Opettaja
- Teacher in charge
- Laura Hakanen
- Groups
-
SKKV23SPInterior architecture and furniture design, full-time studies
- Course
- MU00DT24
Realization has 15 reservations. Total duration of reservations is 56 h 0 min.
Time | Topic | Location |
---|---|---|
Tue 02.09.2025 time 10:00 - 14:30 (4 h 30 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 09.09.2025 time 10:00 - 14:30 (4 h 30 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
149
Byod-/teorialuokka (32+1), päärakennus
|
Thu 18.09.2025 time 10:00 - 14:30 (4 h 30 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Thu 25.09.2025 time 10:00 - 14:45 (4 h 45 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Thu 02.10.2025 time 10:00 - 14:30 (4 h 30 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Thu 09.10.2025 time 10:00 - 14:15 (4 h 15 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Thu 16.10.2025 time 10:15 - 15:15 (5 h 0 min) |
Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 28.10.2025 time 13:15 - 16:15 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 04.11.2025 time 09:00 - 12:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 04.11.2025 time 13:00 - 16:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 25.11.2025 time 13:15 - 16:15 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 02.12.2025 time 09:00 - 12:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 02.12.2025 time 13:00 - 16:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 16.12.2025 time 09:00 - 12:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Tue 16.12.2025 time 13:00 - 16:00 (3 h 0 min) |
* Tulevaisuuden ennakointi MU00DT24-3015 |
243
DataLAB/Byod-luokka (24+1), päärakennus
|
Objective
You outline potential, probable and desirable futures, which you begin to implement in your design process.
You will be familiar with the different future research methods, which you learn to apply in the developing of your own work and your trade.
Content
What methods are available to forecast the future?
What kind of potential, probable and desirable futures do you see in your field?
How do you start implementing them in your own profession?
Course material
The study materials are provided by the teacher in class or via the Learn platform.
Study forms and methods
• The course is carried out by way of contact teaching on Kouvola's campus according to a weekly schedule. Remote participation is not possible. As a rule, scheduled contact lessons are not recorded nor duplicated by online lectures.
• Students make progress by attending scheduled lessons and completing tasks and assignments individually or in groups.
• The teacher provides guidance during and after contact lessons and via the Learn platform.
• The assessed assignments are completed independently/in groups/in pairs.
• Feedback is provided by different methods, in writing and/or orally. Also, peer feedback can be used.
• The course consists of two parts which are separately assessed: common 3 credits and sustans 2 credits. More detailed information available below in section “Course part description”.
RDI and work-related cooperation
The assignments are based on the needs of operators in the field.
Assignments can be completed with reference to tasks given by one’s employer or in connection to developing a product.
Timing of exams and assignments
There is no exam in this course.
Learning assignment return schedules are published on the Learn platform at the start of the study period. All learning assignments must be completed in accordance with the schedule found on the Learn platform in order to obtain an acceptable performance from the course. Assignments returned late are automatically assessed as rejected.
Student workload
• 1 ECTS credits equals 27 hours of work by the student.
• In a 5-credit course, the student's total maximum workload is approximately 135 hours including lessons, group work and independent study.
Further information
Students who have been accepted for the study course will be transferred to the Learn platform automatically at the start of the study course.
Evaluation scale
1-5
Assessment methods and criteria
The student’s performance is assessed with reference to the learning objectives and assessment criteria of the course. The completion of the course requires all tasks to be completed with a passing grade.