Learning is a complex, nonlinear, and ever-evolving process shaped by cognitive, metacognitive, motivational, and affective factors. Traditional Learning Analytics (LA) falls short in explaining these dynamic processes, often relying on reductionist methods that oversimplify the intricate interactions at play.
We recognize the limitations of current LA methodologies and propose a shift towards complex dynamical systems (CDS) as a framework for educational research. CDS leverages insights from the natural sciences, such as physics and thermodynamics, to understand how complex systems change and adapt. Unlike traditional LA approaches, CDS embraces the temporality, interdependencies, and non-linearity inherent in learning data.
In the "Advancing Learning Analytics with Complex Dynamical Systems: Trends and Challenges in Non-Linear Modeling of Learning Data" international workshop, we will explore how Complex Dynamic Systems (CDS) can reshape educational research in areas like writing, self-regulated learning, affective dynamics and emotion regulation, and social learning. This workshop will serve as a platform to educate the Learning Analytics community about the potential of CDS and bring together international experts from both within and outside the field of LA to foster discussions on topics like micro-level and macro-level processes, modeling changes within systems, temporal and spatial considerations, and the application of CDS in various learning contexts, from game-based learning to intelligent tutoring systems.
We invite you to join our CDS workshop at the 14th International Conference on Learning Analytics & Knowledge (LAK24) and explore best practices for implementing non-linear dynamical (NLD) analyses in learning research, ultimately advancing our understanding of complex learning processes and promoting replication through standardized reporting.Â
Join us to transform the status quo!