Complex Systems in Education: Scientific and Educational Importance and Implications for the Learning Sciences

Abstract

The multidisciplinary study of complex systems in the physical and social sciences over the past quarter of a century has led to the articulation of important new conceptual perspectives and methodologies that are of value both to researchers in these fields as well as to professionals, policymakers, and citizens who must deal with challenging social and global problems in the 21st century. The main goals of this article are to (a) argue for the importance of learning these ideas at the precollege and college levels; (b) discuss the significant challenges inherent in learning complex systems knowledge from the standpoint of learning sciences theory and research; (c) discuss the "learnability issue" of complex systems conceptual perspectives and review a body of literature that has been exploring how learning sciences pedagogical approaches can lead to student learning of important dimensions of complex systems knowledge; (d) argue that the cognitive and sociocultural factors related to learning complex systems knowledge are relevant and challenging areas for learning sciences research; and (e) consider ways that concepts and methodologies from the study of complex systems raise important issues of theoretical and methodological centrality in the field of the learning sciences itself.

Instruction in Computer Modeling Can Support Broad Application of Complex Systems Knowledge

“…Complex systems are systems made up of many independent units (aka "agents") whose interaction produce higher order emergent behavior [for more details, see Goldstone and Wilensky (2008)]. Complex systems approaches, which enable researchers to study phenomena that have multiple causes and consequences and have structure at many different temporal, spatial, and organizational levels, have had a large impact on the fields of math and science (e.g., Deneubourg et al, 1986;Forrest, 1991;Dawkins, 1996;Epstein and Axtell, 1996) and are having an increasing impact on engineering, medicine, finance, law, and management (Jacobson and Wilensky, 2006). Despite the widespread influence of complex systems approaches in science and engineering, the tools and perspectives of complex systems have had significantly less influence in STEM curriculum (Jacobson and Wilensky, 2006).…”

Diagramming prior knowledge in the classroom

“…The visible nature of prior knowledge incoherence when communicating new material in the classroom is rooted in the interdisciplinary nature of learning sciences research (Jacobson & Wilensky, 2006). There is a significant body of literature on diagrams, prior knowledge, and the assessment of prior knowledge.…”

The Contribution of Learning by Modeling (LbM) toStudents' Understanding of Complexity Concepts

“…For example people observed bird flocks for thousands of years before anyone suggested that flocks are leader-less, and people participate in traffic jams without much understanding of what cause the jams, such phenomena may be regarded as complex systems. Observation and participation are not enough; people need a richer sense of involvement with systems in order to understand them [5], [9], [10], [14], [16], [21]. Modeling can provide students with the power to understand and explore systems that were previously difficult to trace and predict their behavior, new techniques that help to learn important concepts on complex systems, to generate relevant questions, theories and hypothesis about phenomena, and to build and run models related to their theories [7], [12], [15], [19], [20].…”

“…Despite the utilization of new learning approaches with models, students experience difficulties in learning concepts relevant to understanding complex systems currently taught in existing science courses -student thinking may be counter-intuitive or might conflict with the scientific models, and the learning ideas concerning emergence or stochastic processes are difficult because of difference with teleological beliefs, where students tend to think of systems having centralized control [8], [13], [14], [20]. Hmelo-Silver and Pfeffer (2004) argue that the characteristics of complex systems make them difficult to understand, since they are comprised of multiple levels of organization that often depend on local interactions (the causes and effects are not obviously related); also it requires that students should construct a network of concepts and principles about the phenomena with complexity and their interrelationships [14], [17], [20].…”

“…Hmelo-Silver and Pfeffer (2004) argue that the characteristics of complex systems make them difficult to understand, since they are comprised of multiple levels of organization that often depend on local interactions (the causes and effects are not obviously related); also it requires that students should construct a network of concepts and principles about the phenomena with complexity and their interrelationships [14], [17], [20]. Some researchers argue that modeling did not contribute a lot in understanding complexity since it increases the cognitive load on students (see [11]).…”