Reference : An architecture for e-learning system with computational intelligence (extended version)
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/17179
An architecture for e-learning system with computational intelligence (extended version)
English
El Alami, Marc mailto [University of Luxembourg > Central Administration > IT Department]
Casel, Nicolas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Zampunieris, Denis mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2008
Electronic Library
26
3
Artificial intelligence applications in Digital Content
318-328
Yes (verified by ORBilu)
International
0264-0473
[en] Learning Management System ; Proactive Computing ; Rule-Based Expert System
[en] Purpose of this paper
We introduce a new kind of Learning Management Systems: 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 (see e.g. Tennenhouse D., “Proactive Computing”, Communications of the ACM, 43 (5), 2000, pp. 43-50.) adhere to two premises: working on behalf of, or pro, the user, and acting on their own initiative, without user’s explicit command. The proactive part of our 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
We show how we implemented the proactive part of our LMS on the basis of a dynamic expert system. We also sketch how it looks like from a user’s point of view. Finally, we give examples of intelligent analysis of users’ behaviours coded into proactive rules.

Research limitations/implications (if applicable)
Future work includes 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 and value of paper
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 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 like teachers do in classrooms. Our 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 behaviours.
http://hdl.handle.net/10993/17179
10.1108/02640470810879473
http://www.emeraldinsight.com/0264-0473.htm

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
2008 [Marc El Alami, Nicolas Casel, Denis Zampunieris] An Architecture for e-Learning System with Computational Intelligence.pdfPublisher postprint20.18 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.