A3 Book section, Chapters in research books
Adapting Teaching and Learning in Higher Education Using Explainable Student Agency Analytics (2024)

Heilala, V., Jääskelä, P., Saarela, M., & Kärkkäinen, T. (2024). Adapting Teaching and Learning in Higher Education Using Explainable Student Agency Analytics. In Z. Lv (Ed.), Principles and Applications of Adaptive Artificial Intelligence (pp. 20-51). IGI Global. Advances in Computational Intelligence and Robotics. https://doi.org/10.4018/979-8-3693-0230-9.ch002

JYU authors or editors

Publication details

All authors or editors:  Heilala, Ville; Jääskelä, Päivikki; Saarela, Mirka; Kärkkäinen, Tommi

Parent publication: Principles and Applications of Adaptive Artificial Intelligence

Parent publication editors: Lv, Zhihan

ISBN: 979-8-3693-0230-9

eISBN: 979-8-3693-0232-3

Journal or series: Advances in Computational Intelligence and Robotics

ISSN: 2327-0411

eISSN: 2327-042X

Publication year: 2024

Pages range: 20-51

Number of pages in the book: 316

Publisher: IGI Global

Publication country: United States

Publication language: English

DOI: https://doi.org/10.4018/979-8-3693-0230-9.ch002

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/93293

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.

Keywords: higher education (teaching); students; learning; human agency; analysis; artificial intelligence

Contributing organizations

Related projects

Ministry reporting: Yes

VIRTA submission year: 2024

Preliminary JUFO rating: 1