Practical neural network recipes in C++
Practical neural network recipes in C++
An agent enabling personalized learning in e-learning environments
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
A model of virtual university - some problems during its development
CompSysTech '03 Proceedings of the 4th international conference conference on Computer systems and technologies: e-Learning
Personalized e-learning system using Item Response Theory
Computers & Education
Application of Componential IRT Model for Diagnostic Test in a Standard-Conformant eLearning System
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Intelligent agent supported personalization for virtual learning environments
Decision Support Systems
Expert Systems with Applications: An International Journal
Personalized curriculum sequencing utilizing modified item response theory for web-based instruction
Expert Systems with Applications: An International Journal
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Optimizing time limits for maximum sales response in Internet shopping promotions
Expert Systems with Applications: An International Journal
International Journal of Advanced Intelligence Paradigms
Post review of E-education system performance
ICCC'11 Proceedings of the 2011 international conference on Computers and computing
Context-dependent feedback prioritisation in exploratory learning revisited
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Personalized Learning Course Planner with E-learning DSS using user profile
Expert Systems with Applications: An International Journal
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
User modeling for adaptive e-learning systems
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In web-based educational systems the structure of learning domain and content are usually presented in the static way, without taking into account the learners' goals, their experiences, their existing knowledge, their ability (known as insufficient flexibility), and without interactivity (means there is less opportunity for receiving instant responses or feedbacks from the instructor when learners need support). Therefore, considering personalization and interactivity will increase the quality of learning. In the other side, among numerous components of e-learning, assessment is an important part. Generally, the process of instruction completes with the assessment and it is used to evaluate learners' learning efficiency, skill and knowledge. But in web-based educational systems there is less attention on adaptive and personalized assessment. Having considered the importance of tests, this paper proposes a personalized multi-agent e-learning system based on item response theory (IRT) and artificial neural network (ANN) which presents adaptive tests (based on IRT) and personalized recommendations (based on ANN). These agents add adaptivity and interactivity to the learning environment and act as a human instructor which guides the learners in a friendly and personalized teaching environment.