Model-Facilitated Inquiry Learning to Promote Understanding Complex Science Systems
OU Research Council
Phase 1: 01/2008-08/2011
Phase 2: 02/2012-Present
Yu (Bryan) Guo
How do ecological physical, and chemical processes work together to govern the flows of biologically active molecules such as CO2, N, P, and so on? Why are the ecosystems in the waters off two neighboring Aleutian Islands so different? How does the immune system respond to constantly changing bacterial and viral invaders? These questions point to phenomena that are regarded as complex systems. Complex systems are best characterized by interconnected components whose behavior is not explained exclusively by the properties of their components. Rather, the behavior emerges from the interconnectedness of the components. Complex systems depend on feedback, respond to multiple causes and effects, involve multiple interconnected levels and operate at multiple time scales.
Understanding complex systems is fundamental to learning in many scientific domains such as physics, physiology, environmental biology, and ecology. For example, to develop a proper conceptual understanding in ecology, students must be able to understand the dynamic interrelationships among different organisms within and across species. However, prior research suggests that humans have difficulty in understanding and monitoring complex systems, which calls for complex, and sometimes also ill-structured, problem solving competencies.
This project investigates the effectiveness of various promising instructional strategies (such as question prompts, system dynamic model progression, model-building and model-using) to scaffold learners’ cognitive regulation and their development of complex problems-solving competencies in the context of a simulation-based inquiry learning environment that is developed to support 8th grade students’ understanding of complex lake ecology system.
*This study is still in progress. More details will be provided as soon as available.