Summary
The paper is a systematic review that analyzed 75 empirical studies to determine whether the research (a) collectively represents the goals of educational policy and real-world science, (b) has considered a variety of settings and populations, and (c) has demonstrated systematic investigation of interventions with a view to scale. Τhis review does not include studies in the field of systems dynamics that focus on macro-level systems functions (typically of engineered systems) and generally aim to quantitatively track the rate of flow of resources to optimize whole system efficiencies. Similarly, it does not include studies of dynamic systems, which hail from the field of developmental psychology and focus mainly on identifying the dynamics occurring within and between individual actors that support or constrain mental and behavioral growth.
Authors claim that for understanding complex systems students need to be able to recognize the conditions in which aspects of a system are changing or not, and these can be dependent on the time span during which the observations are made. The mechanisms of feedback loops in a system also serve to regulate processes and maintain or destabilize the system.
Authors found that complex systems researchers address issues in multiple scientific knowledge domains and search for underlying principles that are universal in nature. They found an abundance of complex systems in science education studies in the domains of biology and ecology. The biological systems in these studies included human body systems such as the circulatory and respiratory systems, cellular systems, and genetics or genetic engineering. These studies have revealed several issues in student reasoning about complex systems. Studies focused on the domain of ecology, which represent more than half of the total complex systems in science education research in the sample of this review, and they have highlighted student learning challenges.
The review analysis of the complex systems concepts found that within the complex systems in science education studies demonstrated relative depth in the areas of systems structures and processes. Within these categories, several studies attended to learning about connections between systems components, and how they form aggregate levels at different scales.
This review also indicates that few studies examine the critical nature of how complex systems can differ based on initial variables, and how triggers can influence how systems self-organize. Such investigations are important to be able to model phenomena and make predictions, which are two scientific practices at the core of real-world complex systems research. Similarly, the review revealed only a few studies that focused on complex systems states such as equilibrium and decentralization and no complex systems in science education studies that investigated system robustness and resilience.
Two theoretical frameworks that locate learning in different aspects of systems had been revealed: (a) The Structure–Behavior–Function framework comes from the field of engineering systems design and considers systems understanding as a hierarchical knowledge of system characteristics. The components or structures (e.g., hybrid or electric motor) and behaviors (e.g., energy consumption) must first be understood in order to work with the system to achieve the desired output or function (e.g., how far a car can travel). (b) The “clockwork” versus “complex systems” encompasses a clockwork orientation which views the world from a Cartesian perspective (consisting of machines). It is based on a method of analytic thinking that involves breaking up complex phenomena into pieces to understand the behavior of the whole from the properties of its parts. This is in contrast to a complex system view, according to which the essential properties of a complex system with a constant influx of energy are properties of the whole-properties that none of the parts have on their own. A system’s central properties arise from the interactions and relationships among the parts, which is the dynamic process of emergence. This framework investigates the processes that fuel emergence and change in systems from micro to macro levels.
In conclusion, the paper reports critical needs in five areas of research: (a) a need for more research in different knowledge domains outside of the content areas of biology and ecology, (b) a need for more research on system states as opposed to structures and processes, (c) a need to develop a common understanding of the complex systems content that is essential to be learned, (d) a need to consider contextual factors that will affect the learning environment and population including teacher learning, and (e) more comparative research to determine the value of complex systems in science education interventions over traditional forms of instruction, including an emphasis on what teachers need in professional development activities.
Relevance for Complex Systems Knowledge
The paper deals with complex systems and complexity.
Authors point out that the study of complex systems can be summarized as understanding how behavior of phenomena at different scales is related and how larger scale patterns emerge from the interdependent components at lower scales. By studying the patterns that emerge and the interactional processes that lead to these patterns, researchers can better understand how systems adapt, self-organize, fluctuate, and reach and maintain equilibrium.
For example, to understand the complexity of a particulate system, it is important to recognize that at the component level, particles in a gas system move in straight lines, collide with one another, and alter their speed and direction of motion. Changes in these behaviors such as the number of particles, the energy of particles, and the frequency of collisions can affect the system’s outcomes such as energy transfer, random motion of particles, and diffusion.
