Adapting Teaching and Learning in Higher Education Using Explainable Student Agency Analytics

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.
Main Authors
Format
Books Book part
Published
2024
Series
Subjects
Publication in research information system
Publisher
IGI Global
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202402071779Käytä tätä linkitykseen.
Parent publication ISBN
979-8-3693-0230-9
Review status
Peer reviewed
ISSN
2327-0411
DOI
https://doi.org/10.4018/979-8-3693-0230-9.ch002
Language
English
Published in
Advances in Computational Intelligence and Robotics
Is part of publication
Principles and Applications of Adaptive Artificial Intelligence
Citation
  • 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
License
In CopyrightOpen Access
Funder(s)
Research Council of Finland
Funding program(s)
Akatemiatutkija, SA
Academy Research Fellow, AoF
Research Council of Finland
Additional information about funding
M. S. research was supported by Otto A. Malm, the Finnish Foundation for Share Promotion, and the Academy of Finland (project no. 356314).
Copyright© 2024 IGI Global

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