Reimaging Linear Models: Complex Systems as a Framework for Understanding Mathematics Teacher Learning

• In Event: Complexity theories in education: Concepts, methods, and challenges

Abstract

Despite widespread agreement on features of effective professional learning —such as collaboration, content focus, and active learning—many initiatives fail to achieve sustained outcomes. This study reframes teacher learning as a dynamic system by applying complexity theory to examine interactions among professional learning features and mechanisms. Using a qualitative multiple-case study of a province-wide mathematics professional learning initiative, we analyzed interview data from teacher participants. Findings reveal that mechanisms such as neighbor interactions, decentralized control, and nestedness support emergent learning outcomes, including pedagogical change and shifts in school culture. This paper argues for a departure from linear learning frameworks toward more adaptive models that recognize teacher agency and systemic interactions, offering a perspective on teacher professional learning.

Authors

• Kelly A. McKie, University of Delaware

• Robin Keturah Anderson, North Carolina State University