Interdisciplinary Systems Thinking

Schedule:

• 3.2. at 9.15-12.00 (TS128) Aarne Mämmelä, Basics of systems thinking
• 6.2. at 9.15-12.00 (TS128) Aarne Mämmelä, Sciences, theories, and system archetypes ​
• 10.2. at 9.15-12.00 (TS128) Mika Aaltonen, Complex adaptive networks and a cognitive framework​
• 13.2. at 9.15-12.00 (TS128) Enso Ikonen, Process control systems
• 17.2. at 9.15-12.00 (TS128) Heikki Ailisto, Artificial intelligence
• 20.2. at 9.15-12.00 (TS128) Nønne Prisle, Aerosols, climate and people
• 24.2. at 9.15-12.00 (TF331) Heikki Helanterä, Evolutionary biology and systems thinking
• 27.2. at 9.15-12.00 (TS128) Mikko Rajanen, Systems thinking in human-computer interaction

Winter break

• 10.3. at 9.15-12.00 (TS128) Kalle Timperi, System boundaries, complexity, and randomness
• 13.3. at 9.15-12.00 (TS128) Seppo Yrjölä, Techno-economic systems in future mobile communications, 6G
• 17.3. at 9.15-12.00 (TS128) Mikko Sillanpää, Bayesian hierarchical modeling
• 20.3. at 9.15-12.00 (SÄ124) Olli Loukola, Complex cognition in miniature brains: What bumblebees can teach us about intelligence
• 24.3. at 9.15-12.00 (TS128) Tuomas Pernu, The notion of system: Philosophical and historical reflections
• 27.3. at 9.15-12.00 (TS128) Olli Silven, Connecting the dots: Systems thinking toward physical world AI application

Upon completion of the course, the student will be able to:

• appreciate the importance of interdisciplinary systems thinking
• know the history of systems thinking
• understand system theories and generic system models called system archetypes
• understand the limitations of human knowledge.

Aarne Mämmelä (Aarne.Mammela(at)oulu.fi), Mirjami Jutila (Mirjami.Jutila(at)oulu.fi)

Textbook: M. Ramage and H. Shipp, Systems Thinkers, 2nd ed. London: Springer, 2020 (open access through the university library).

Teaching methods

• Contact teaching in 14 sessions (3 hours each)
• Discussion questions in each session
• 2 learning diaries

Study methods

• Lectures (14 sessions, each 3 hours, altogether 42 hours).
• Reflections in the form of discussion questions and two learning diaries.
• 1st learning diary on the textbook M. Ramage and H. Shipp, Systems Thinkers, 2nd ed. London: Springer, 2020 (open access through the university library), including chapters 2 Norbert Wiener, 5 W. Ross Ashby, 6 Ludwig von Bertalanffy, 7 Kenneth Boulding, 10 Jay Forrester, 23 Ilya Prigogine, 24 Stuart Kauffman, 26 Kurt Lewin, and 28 Chris Argyris by 27.2.2026. The diary includes a title page, a brief introduction, a reflection of approximately half a page for each chapter, and a short overall reflection summarizing what the student learned, totaling seven pages. The title page contains the name of the course and student, faculty, research unit, the topic of the doctoral thesis, a table of contents, and the disclaimer “I have written my learning diary in my own words to reflect my personal learning.” Copying of other students’ learning diaries is not allowed. The student must mention any use of AI, such as improving the grammar, in the disclaimer. Orienting questions for the textbook are the following: What was surprising, what was not unexpected, what would you like to know more about, what you disagree with, and what you did not want to know?
• 2nd learning diary on the lectures by 10.4.2026, including at least 9 of the 14 sessions. The diary includes a title page, a brief introduction, a reflection of approximately half a page for each session, and a short overall reflection summarizing what the student learned, totaling seven pages. The title page contains the name of the course and student, faculty, research unit, the topic of the doctoral thesis, a table of contents, and the disclaimer “I have written my learning diary in my own words to reflect my personal learning.” Copying of other students’ learning diaries is not allowed. The student must mention any use of AI, such as improving the grammar, in the disclaimer. The lecturers give orienting questions for the learning diary in each lecture session.

Assessment scale

Pass/fail. Attendance to at least 9 sessions and approved learning diaries to gain credits.