Title :
Using Bayesian Networks to Implement Adaptivity in Mobile Learning
Author :
Yu Dan ; XinMeng, Chen
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
Abstract :
Mobile learning technologies have the potential to revolutionize distance education by bringing the concept of anytime and anywhere to reality. However, the development of mobile learning is hampered by various technological and access related problems, including the difficulty in implementing adaptivity. In this paper, we use the Bayesian networks to determine mobile learner´s styles exploring the potential of individualization of learning process for the learners to implement adaptive mobile learning.
Keywords :
computer aided instruction; distance learning; mobile computing; Bayesian networks; adaptive mobile learning technology; distance education; learning process; mobile learner; mobile learning adaptivity;
Conference_Titel :
Semantics, Knowledge and Grid, 2006. SKG '06. Second International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7695-2673-X
DOI :
10.1109/SKG.2006.107
