Implementation of Efficient Proactive Computing Using Lazy Evaluation in a Learning Management System

In Zampunieris (2006) we proposed a new kind of learning management system, proactive LMS, designed to help users to better interact online by providing programmable, automatic, and continuous analyses of the users’ actions, augmented with appropriate actions initiated by the LMS itself. The proactive part of our LMS is based on a dynamic rules-based system. However, the main algorithm we proposed in order to implement the rules-running system suffers some efficiency problems. In this article, 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 check(s) failed.