An Adaptive E-Learning System Using Justification Based Truth Maintenance System
This addresses the problem of static educational content for students, though it appears incremental as it builds on existing adaptation methods.
The paper tackles the lack of personalization in e-learning systems by proposing an adaptive system using a justification-based truth maintenance system to provide customized learning paths based on student profiles, validated through a meta-model.
In most E learning systems educational activities are presented in a static way without bearing in mind the particulars or student levels and skills. Personalization and adaptation of an E learning management system are dependent on the flexibility of the system in providing different learning and content models to individual students based on their characteristics. In this paper we suggest an Adaptive E learning system which is providing adaptability with support of justification based truth maintenance system. The system is accomplished of signifying students with suitable knowledge fillings and customized learning paths based on the students profile interests and previous results. The validation of proposed framework is performed by meta model.