Detailed Information on Publication Record
2024
Adaptive Learning is Hard: Challenges, Nuances, and Trade-offs in Modeling
PELÁNEK, RadekBasic information
Original name
Adaptive Learning is Hard: Challenges, Nuances, and Trade-offs in Modeling
Authors
Edition
International Journal of Artificial Intelligence in Education, NEW YORK, SPRINGER, 2024, 1560-4292
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Impact factor
Impact factor: 4.900 in 2022
Organization unit
Faculty of Informatics
UT WoS
001190058700001
Keywords in English
Adaptive learning; Student modeling; Domain modeling; Trade-offs
Tags
International impact, Reviewed
Změněno: 22/4/2024 10:45, doc. Mgr. Radek Pelánek, Ph.D.
Abstract
V originále
While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue that a key factor contributing to this relatively slow progress is the inherent complexity of developing adaptive learning environments. I focus specifically on the modeling techniques that provide the foundation for adaptive behavior. The design of these models presents us with numerous challenges, nuances, and trade-offs. Awareness of these challenges is essential for guiding our efforts, both in the practical development of our systems and in our research endeavors.
