Modeling an Adaptive and Collaborative E-Learning System with Artificial Intelligence Tools

In an educational environment that is undergoing digital transformation, the need to create smarter, learner-centred learning environments is becoming increasingly urgent. This article presents a conceptual modeling of an e-learning system that integrates the adaptive and collaborative dimensions, r...

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Bibliographic Details
Published in:International journal of advanced computer science & applications Vol. 16; no. 7
Main Authors: Zargane, Kawtar, Kemouss, Hassane, Khaldi, Mohamed
Format: Journal Article
Language:English
Published: West Yorkshire Science and Information (SAI) Organization Limited 2025
Subjects:
Adaptive learning
Agents (artificial intelligence)
Artificial intelligence
Collaboration
Conversational artificial intelligence
Distance learning
Instructional design
Knowledge management
Machine learning
Modelling
Online instruction
Pedagogy
ISSN:2158-107X, 2156-5570
Online Access:Get full text
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Summary:In an educational environment that is undergoing digital transformation, the need to create smarter, learner-centred learning environments is becoming increasingly urgent. This article presents a conceptual modeling of an e-learning system that integrates the adaptive and collaborative dimensions, relying on the tools of artificial intelligence (AI), which occupies a central place, both as a dynamic adaptation engine and as a collaboration facilitator and automaton of certain pedagogical activities. This methodical and structured approach makes it possible to develop a hybrid environment capable of adjusting to individual needs while promoting the co-construction of knowledge between peers. Based on instructional design principles and the 2TUP (Two Tracks Unified Process) process, this approach aims to develop a systematic architecture, illustrated by UML (Unified Modeling Language) diagrams, of classes, use cases, activities and sequences, integrating AI (Artificial Intelligence) through adaptive learning, conversational agents and intelligent tutoring systems that make it possible to personalize learning, Provide targeted feedback, optimize learner performance, and guide learners more accurately. This combination of standardized modeling and AI improves the synergy between stakeholders and increases the efficiency of online learning environments. Finally, this model paves the way for a new era of more flexible, inclusive and responsive techno-pedagogical systems, capable of facing the contemporary challenges of online training.
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2025.0160745