Objectives and competences
The objective of this course is:
• presenting natural, technical, social systems;
• presenting the relationship between the structure, dynamics, and evolution of systems;
• presenting basics of qualitative and quantitative analysis of system dynamics;
• presenting basics of learning analytics;
• presenting basics in network theory;
• presenting basics of self-organization.
Students will gain:
• competence of analysing structure, dynamics, and evolution of natural, technical, and social systems;
• competence of system thinking;
• ability of basic qualitative and quantitative analysis of systems dynamics;
• ability to use computer programmes Madonna and NetLogo;
• ability of knowledge transfer from system dynamics to other fields.
Content (Syllabus outline)
• Universal view on natural, technical, and social systems: structure, dynamics, and evolution of systems.
• Determination of interrelations between system parts, internal and external influences, positive and negative feedback loops.
• Qualitative description of systems dynamics: causal-loop diagrams and stock-flow diagrams.
• Quantitative description of systems dynamics and mathematical modeling.
• Analysis of contents in curriculum appropriate for developing of system thinking in school.
• Learning analytics.
• Complex networks.
• Self-organization.
• Structure of systems, fractals.
• Development (evolution) of systems and basics of game theory.
• Using of computer programs developed for modeling of systems dynamics in school: DynaSys, Stella, Madonna, NetLogo.
Learning and teaching methods
• Lectures,
• computer exercises,
• experiments,
• reflection,
• discussion,
• case studies.
Intended learning outcomes - knowledge and understanding
On completion of this course the student will:
• understand the relationship between structure, dynamics, and evolution of systems;
• understand the role of positive and negative feedback loops in complex systems;
• know to present the dynamics of systems with causal-loop diagrams and stock-flow diagrams;
• be able to construct simple mathematical models;
• understand principles of modelling of multi-agent dynamical systems;
• understand basic properties of networks;
• know basics of game theory.
Intended learning outcomes - transferable/key skills and other attributes
Readings
• G. Ossimitz, Entwicklung systemischen Denkens, Theoretische Konzepte und empirische Untersuchungen, Profil Verlag, München 2000.
• P.M. Senge, N. Cambron-McCabe, T. Lucas, B. Smith, J. Dutton, A. Kleiner, Schools that Learn: A Fifth Discipline Fieldbook for Educators, Parents, and Everyone Who Cares About Education. Doubleday, New York 2000.
• D.H. Meadows, (ed. Diana Wright), Thinking in Systems: A Primer, Chelsea Green Publishing Company, White River Junction, VT, 2008.
• J. Gharajedaghi, Systems thinking: Managing chaos and complexity: A platform for designing business architecture, Elsevier, M. Kaufmann, Burlington, MA, 2011.
• Bejan, J.P. Zane, Design in Nature: How the Constructal Law Governs Evolution in Biology, Physics, Technology, and Social Organization, Doubleday, New York, 2012.
• Strokovni in znanstveni članki v revijah / Articles published in professional and scientific journals.
Prerequisits
Prerequisits for acceding the course:
None.
Conditions for prerequisits:
Accomplished obligations given during tutorials and lectures.
Additional information on implementation and assessment • Written exam (80%)
• Portfolio (20%)
Written exam can be recognized on the basis of partial written examinations.