Seminar Artificial Intelligence - Dr. I. Chounta

Title: Towards computational systems of human cognition for guiding multifaceted personalized learning

Abstract:

The adoption of technology in education provides us with numerous tools and methods to support learning and teaching. Data richness offers great potential for testing analytical approaches to inform new, or revisited, learning paradigms. These developments give us the unique opportunity to employ computational approaches, such as machine- learning and data mining, to address fundamental pedagogical challenges: how to adaptively guide students and how to provide appropriate support to facilitate learning. Most importantly, we have the possibility to document and visualize complex human processes, to provide evidence of learning, and to support established pedagogical theories by exploring and analyzing data traces of human practice.

In my talk, I will present the open challenge my research aims to address: bridging the gap between pedagogical theory and modern, data-driven practice. I will present the concept of the “Grey Area”, a computational, machine-learning approach for modeling the Zone of Proximal Development (ZPD) of individual students. I will demonstrate the application of this approach to existing data and how it can be used to provide personalized and adaptive scaffolding. Finally, I will discuss the theoretical and practical implications of computational analytics and cutting-edge technologies for monitoring and guiding complex human activities.