Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
Individualized tutoring using an intelligent fuzzy temporal relational database
International Journal of Man-Machine Studies
Neurocomputations in Relational Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural networks applied to knowledge acquisition in the student model
Information Sciences: an International Journal
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Knowledge representation in fuzzy logic
Fuzzy sets, fuzzy logic, and fuzzy systems
Advances in local student modeling using informal fuzzy reasoning
International Journal of Human-Computer Studies
Effective backpropagation training with variable stepsize
Neural Networks
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
Informing the Detection of the Students' Motivational State: An Empirical Study
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
A Neuro-Fuzzy Approach to Detect Student's Motivation
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis
Information Sciences—Informatics and Computer Science: An International Journal
Expert Systems with Applications: An International Journal
A neuro-fuzzy approach in student modeling
UM'03 Proceedings of the 9th international conference on User modeling
An Artificial Intelligence Course Used to Investigate Students' Learning Style
ICWL '08 Proceedings of the 7th international conference on Advances in Web Based Learning
Dynamic question generation system for web-based testing using particle swarm optimization
Expert Systems with Applications: An International Journal
Addressing Learning Style Criticism: The Unified Learning Style Model Revisited
ICWL '009 Proceedings of the 8th International Conference on Advances in Web Based Learning
Expert Systems with Applications: An International Journal
Modeling personalized learning styles in a web-based learning system
Transactions on edutainment IV
Student modeling for a web-based self-assessment system
Expert Systems with Applications: An International Journal
Fuzzy linguistic modelling cognitive/learning styles for adaptation through multi-level granulation
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: users and applications - Volume Part IV
Supporting teachers in adaptive educational systems through predictive models: A proof of concept
Expert Systems with Applications: An International Journal
A Unified Learning Style Model for Technology-Enhanced Learning: What, Why and How?
International Journal of Distance Education Technologies
Review Article: Applications of neuro fuzzy systems: A brief review and future outline
Applied Soft Computing
Hi-index | 12.06 |
In this paper, the implementation of a neural network-based fuzzy modeling approach to assess aspects of students' learning style in the discovery learning environment ''Vectors in Physics and Mathematics'' is presented. Fuzzy logic is used to provide a linguistic description of students' behavior and learning characteristics, as they have been elicited from teachers, and to handle the inherent uncertainty associated with teachers' subjective assessments. Neural networks are used to add learning and generalization abilities to the fuzzy model by encoding teachers' experience through supervised neural-network learning. The neural network-based fuzzy diagnostic model is a general diagnostic model which is implemented in an Intelligent Learning Environment by eliciting teachers' expertise regarding students' characteristics based on real students' observation and on data being collected from students' interaction. The model has been successfully implemented, trained and tested in the learning environment ''Vectors in Physics and Mathematics'' by using the recommendations of a group of five experienced teachers. The performance of our model in real classroom conditions has been evaluated during an experiment with an experienced Physics teacher and 49 students of secondary school attending Physics lessons.