Affiliation:
1. University of Jyväskylä, Finland
Abstract
This chapter deals with the learning analytics technique called student agency analytics and explores its foundational technologies and their potential implications for adaptive teaching and learning. Student agency is vital to consider as it can empower students to take control of their learning, fostering autonomy, meaningful experiences, and improved educational outcomes. Beginning with an overview of the technique, its underlying educational foundations, and analytical approaches, the chapter demonstrates the synergy between computational psychometrics, learning analytics, and educational sciences. Considering adaptive artificial intelligence in the context of adaptive learning and teaching, the chapter underscores the potential of these approaches in education. The chapter serves as a brief guide for educators, researchers, and stakeholders interested in the convergence of AI and education.