Systems thinking is the ability or skill to perform problem solving in complex system. System theory or systems science is the interdisciplinary study of systems in which System Thinking can be learned. A system is an entity with interrelated and interdependent parts; it is defined by its boundaries and it is more than the sum of its parts (subsystem). Changing one part of the system affects other parts and the whole system, with predictable patterns of behavior. Positive growth and adaptation of a system depend upon how well the system is adjusted with its environment, and systems often exist to accomplish a common purpose (a work function) that also aids in the maintenance of the system or the operations may result in system failure. The goal of systems science is systematically discovering a system's dynamics, constraints, conditions and elucidating principles (purpose, measure, methods, tools, etc.) that can be discerned and applied to systems at every level of nesting, and in every field for achieving optimized equifinality.
General systems theory is about broadly applicable concepts and principles, as opposed to concepts and principles applicable to one domain of knowledge. It distinguishes, dynamic or active systems and static or passive systems. Active systems are activity structures or components that interact in behaviours and processes. Passive systems are structures and components that are being processed. E.g. a program is passive when it is a disc file and active when it runs in the RAM memory. The field is related to systems thinking and systems engineering.
Source: This section is imported from Systems Theory from Wikipedia (2017/09/12). In Wikiversity the learning of Systems Thinking is the objective. Learning task introduce to systems thinking and learning addresses the already existing skills and knowledge of the learner and extends the systemic problem solving skill within the Wikiversity, WikiPedia, WikiNews, ... resources as a semantic network to trigger local activities that are inline with the Sustainable Development Goals.
- (User Driven Innovation) Learners have individual experiences and learning about systems thinking could start from the exisiting scope and experience of the learner and attach new systemic links to the previous experience (e.g. adding feedback loops and its impact to the user experience). Apply the new knowledge to the area the learners are working in.
- (Case Studies) Explain the role of case studies for learning systems thinking. Use Climate Change as global challenge for mankind and identify the impact of climate change on
- environment (desertification),
- economy (e.g. agriculture),
- health (e.g. vector-bourne diseases),
- social aspect (migration),
- (Sustainable Development Goals) Look at the Sustainable Development Goals and match SDGs to systems analysis result in the previous learning task. Can you extend your systems analysis result by integration of additional SDGs that you have not considered before? Explain the role of SDGs as a guiding framework for systems analysis.
- (From Data to Problem Solving) A database for mean monthly values of temperature, precipitation, and cloudiness on a global terrestrial grid could help to provide evidence for climate change. There is also evidence for climate projections in future. Why is systemic thinking important for contribution to problem solving?
- (Open Innovation Ecosystem) How can systems thinking be helpful in the context of Open Innovation Ecosystems?
- (Earth Overshot Day) Analyse the web portal of Earth Overshot Day and explain how a event is linked to learning resource for children and teachers. Explain how systems thinking approach can be used to reduce .
- Beven, K. (2006). A manifesto for the equifinality thesis. Journal of hydrology, 320(1), 18-36.
- Paolo Rocchi (2000). Technology + Culture. IOS Press. ISBN 978-1-58603-035-3.
- Systems Theory - Wikipedia - Imported and slightly adapted definition for defining Systems Thinking as Skill (imported on 2017/09/12) - https://en.wikipedia.org/wiki/Systems_theory
- Leemans, R., & Cramer, W. P. (1991). The IIASA database for mean monthly values of temperature, precipitation, and cloudiness on a global terrestrial grid. INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS, Laxenburg, Austria.