Toward a Learning Progression of Complex Systems Understanding

Abstract

Recent research on what students know about complex systems shows that they typically have challenges in understanding particular system ideas such as nonlinearity, complex causality, and decentralized control. Yet this research has yet to adopt a systematic approach to learning about complex systems in an ordered way in line with the Next Generation Science Standards’ call for learning pathways that guide teaching and learning along a developmental continuum. In this paper, we propose that learning progressions research can provide a conceptual framework for identifying a learning pathway to complex systems understanding competence. As a first step in developing a progression, we articulate a sequence of complex systems ideas, from the least to most difficult, by analyzing students’ written responses using an item response theory model. Results show that the easiest ideas to comprehend are those that relate to levels or scales within systems and the interconnected nature of systems. The most difficult ideas to grasp are those related to the decentralized organization of the system and the unpredictable or nondeterministic nature of effects. We discuss implications for this research in terms of developing curricular content that can guide learning experiences in grades 8–12 science education.