Enhance Learning Environments Using Knowledge Flow: A Living Systems, Neuroscience-based Model

Abstract

This study introduces the Knowledge Flow framework, a living systems, neuroscience-based learning model designed to enhance inclusion, engagement, and academic performance for diverse students in large university courses. Moving beyond linear learning models, this approach reconceptualizes learning as energy flow within interconnected systems, specifically addressing barriers faced by first-generation students and those from disadvantaged backgrounds. The framework comprises seven Knowledge Catalysts that create structural foundations and four Knowledge Currents that describe the resultant dynamic energy flow within a living systems classroom model, informed by neuroscientific concepts about how the brain grows and learns. Foundational catalysts Meet Me (scaffolding) and See Me (belonging) are discussed as essential for inclusive learning environments, and the torus is introduced as a new model to visualize the learning process. Knowledge Flow implementation in a large introductory neuroscience course demonstrated significant improvements in student performance compared to traditional lecture formats. Undergraduate teaching assistants served as valuable bridges between instructors and students, enhancing classroom community while developing their own pedagogical skills. This approach offers a practical framework for transforming large introductory courses from potential barriers to gateways for success among underrepresented student populations, directly addressing the "wicked problem" of educational inequality and supporting wider participation in higher education in a novel way. This learning approach is theoretically framed as a potential pathway to greater well-being in students within education.