Related Experiment Videos
Systems thinking
Derek Cabrera1, Laura Colosi, Claire Lobdell
1Cornell University, Ithaca, NY USA; Santa Fe Institute, Santa Fe, NM USA; ThinkWorks, Ithaca, NY USA. derekc@thinkandthrive.com
Evaluation and Program Planning
|February 15, 2008
Summary
Systems thinking in evaluation is often unclear. Recent research reveals four simple rules can help evaluators apply systems thinking effectively to existing knowledge for transformative results.
Area of Science:
- Evaluation
- Systems Science
- Complexity Science
Background:
- The concept of systems thinking is widely recognized in evaluation but lacks a clear, unified definition.
- Diverse interpretations exist, ranging from equating it with systems sciences to a mere collection of approaches.
- This ambiguity makes it challenging for evaluators to practically apply systems thinking.
Purpose of the Study:
- To clarify the concept of systems thinking for evaluators.
- To present a practical framework for applying systems thinking in evaluation.
- To demonstrate how systems thinking can yield transformative results in evaluation practice.
Main Methods:
- Analysis of recent scholarly work defining systems thinking.
- Identification of four core conceptual patterns (rules) as the emergent property of systems thinking.
- Application of these four rules to existing evaluation knowledge.
Main Results:
- Systems thinking can be understood as an emergent property of four simple conceptual patterns.
- Evaluators do not need extensive training in nonlinear dynamics or complexity science to become systems thinkers.
- Applying these four rules to existing evaluation knowledge can lead to significant improvements.
Conclusions:
- A simplified, practical approach to systems thinking is achievable for evaluators.
- Mastery of systems thinking does not require years of study in specialized fields.
- The application of four core rules offers a transformative pathway for evaluation practice.
Related Concept Videos
State Space Representation
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
Control Systems
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
At the heart...
Classification of Systems-I
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Visual System
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Once through the pupil, the light passes through the lens, a...
Control Volume and System Representations
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface. For instance, in the case of water flowing...
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface. For instance, in the case of water flowing...
System, Surroundings, and State
Thermodynamics studies the relationship between heat, work, temperature, and energy. A key concept in this field is a "system," the macroscopic part of the universe under observation. Systems can interact with their surroundings, leading to three types: open, closed, and isolated systems.Open systems permit the exchange of both matter and energy with their surroundings, like a boiling pot of water.In contrast, closed systems only allow the transfer of energy, restricting the movement of matter...