Implementation of efficient proactive computing using lazy evaluation in a learning management system

In [Zampunieris, 2006] we proposed a new kind of Learning Management Systems: proactive LMS, designed to help their users to better interact online by providing programmable, automatic and continuous analyses of users (inter-) actions augmented with appropriate actions initiated by the LMS itself. The proactive part of our LMS is based on a dynamic rules-based system. But the main algorithm we proposed in order to implement the rules running system, suffers some efficiency problems. In this paper, we propose a new version of the main rules running algorithm that is based on lazy evaluation in order to avoid unnecessary and time-costly requests to the LMS database when a rule is not activated, that is: when its actions part will not be performed because preliminary checks failed.