IE489 SYSTEMS THINKING
| Course Code: | 5680489 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 5.0 |
| Department: | Industrial Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. SEÇİL SAVAŞANERİL TÜFEKCİ |
| Offered Semester: | Spring Semesters. |
Course Objectives
At the end of the course, the students will
1. gain competency and critical understanding of systemic inquiry by studying systems and systems thinking.
2. learn about the concept of problem identification, interaction between the problem and its context, and learn the methods to construct the relevant system models and understand their effect on solving the problems.
3. get an understanding of hard versus soft systems thinking, and gain knowledge on structuring methodologies that are used for studying the problems encountered in complex systems.
Course Content
Inquiry and research. Methods of science. Fundamental systems concepts and notions. Systems thinking as a mode of inquiry; historical and methodological account. Contrasting and clarifying the systems position vis-à-vis science. The relation between systems thinking and operational research. Principal stains of systems thinking and the systems approaches.
Course Learning Outcomes
1.1. be able to recognize reductionist thinking, cause-and-effect thinking and systems thinking, and appreciate that each complements the other two.
1.2. be able to distinguish between narrow system of interest and wider system of interest.
1.3. recognize the boundary judgements.
1.4. appreciate that system definition is subjective.
2.1. be able to identify six elements of a problem description.
2.2. be able to identify the stakeholders of the problem situation.
2.3. be able to apply system identification rules for identifying inputs, outputs, and system elements.
3.1. be able to classify the complexity of the problem for a given problem situation.
3.2. be able to identify the appropriate systems approach (such as functionalist, interpretive or emancipatory) for a given problem situation, and distinguish between the issues of ‘what’ and ‘how’.
3.3. be able to perform the analysis steps in Chekland’s soft systems methodology.
3.4. Appreciate that for many problem situations, facts and values are not separable, but that what we see as facts and their interpretation depends on the worldviews and values.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ✔ | |||
| 2 | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ✔ | |||
| 3 | An ability to communicate effectively with a range of audiences | ✔ | |||
| 4 | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ✔ | |||
| 5 | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ✔ | |||
| 6 | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ✔ | |||
| 7 | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | ✔ | |||
| 8 | An ability to design, analyze, operate, and improve integrated systems that produce and/or supply products and/or services in an effective, efficient, sustainable, and socially responsible manner | ✔ | |||
| 9 | An ability to apply critical reason and systems thinking in problem solving and systems design | ✔ | |||
| 10 | An ability to use scientific methods and tools (such as mathematical models, statistical methods and techniques) necessary for industrial engineering practice | ✔ | |||