Supporting adaptive learning in hypertext environments: a high level timed Petri net-based approach

Abstract

A problem for hypertext-based learning application is to control learning paths for different learning activities. This paper first introduces related concepts of hypertext learning state space and high level Petri Nets (PNs), then proposes a high level timed PN based approach used to providing kinds of adaptation for learning activities by adjusting time attributes of targeted learning state space. Examples are given while explaining ways to realising adaptive instructions. Possible future directions are also discussed at the end of this paper.