An architecture for e‐learning system with computational intelligence

Abstract

Purpose

The purpose of this paper is to introduce a new kind of learning management system: proactive LMS, designed to improve the users' online (inter)actions by providing programmable, automatic and continuous intelligent analyses of the users' behaviours, augmented with appropriate actions initiated by the LMS itself.

Design/methodology/approach

Proactive systems adhere to two premises: working on behalf of, or pro, the user, and acting on their own initiative, without the user's explicit command. The proactive part of the LMS is implemented as a dynamic rules‐based system, and is added next to the initial LMS. They both use the same database as their source of information on the users, their activities, the available resources and the current state of the whole system.

Findings

How the proactive part of the LMS was implemented on the basis of a dynamic expert system is shown. Also how it looks like from a user's point of view is sketched. Finally, examples of intelligent analysis of users' behaviours coded into proactive rules are given.

Research limitations/implications

Future work should include the design and the implementation of sets of rules (packages) dedicated to common users' needs, enabling useful proactivity on the basis of elaborated intelligent analysis.

Originality/value

Current learning management systems (virtual educational and/or training online environments) are fundamentally limited tools. Indeed, they are only reactive software: these tools wait for an instruction and then react to the user's request. Students using these online systems could imagine and hope for more help and assistance tools: LMS should tend to offer some personal, immediate and appropriate support as teachers offer in classrooms. The proactive LMS can, for example, automatically and continuously help and take care of e‐learners with respect to previously defined procedures rules, and even flag other users, like e‐tutors, if something wrong is detected in their behaviour.

Citation

El Alami, M., Casel, N. and Zampunieris, D. (2008), "An architecture for e‐learning system with computational intelligence", The Electronic Library, Vol. 26 No. 3, pp. 318-328. https://doi.org/10.1108/02640470810879473