Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
A Two-Phase Fuzzy Mining and Learning Algorithm for Adaptive Learning Environment
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
ICWL '02 Proceedings of the First International Conference on Advances in Web-Based Learning
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Consistency Queries in Information Extraction
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
High-Level Student Modeling with Machine Learning
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Towards Error-Free and Personalized Web-Based Courses
AINA '03 Proceedings of the 17th International Conference on Advanced Information Networking and Applications
Towards Evaluating Learners' Behaviour in a Web-Based Distance Learning Environment
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Personalized Courseware Construction Based on Web Data Mining
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 2 - Volume 2
Semantic resource management for the web: an e-learning application
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Synthesis and analysis of automatic assessment methods in CS1: generating intelligent MCQs
Proceedings of the 36th SIGCSE technical symposium on Computer science education
Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
User Modeling and User-Adapted Interaction
Student progress monitoring tool using treeview
Proceedings of the 37th SIGCSE technical symposium on Computer science education
Machine learning approaches for inducing student models
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Some useful tactics to modify, map and mine data from intelligent tutors
Natural Language Engineering
Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Using genetic algorithms for data mining optimization in an educational web-based system
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Discovering prediction rules in AHA! courses
UM'03 Proceedings of the 9th international conference on User modeling
A novel kernelized fuzzy C-means algorithm with application in medical image segmentation
Artificial Intelligence in Medicine
A test-sheet-generating algorithm for multiple assessment requirements
IEEE Transactions on Education
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
The role of readiness factors in E-learning outcomes: An empirical study
Computers & Education
Development of a GTM-based patent map for identifying patent vacuums
Expert Systems with Applications: An International Journal
Analysis of students' behaviour in the web-based distance learning environment
CSCC'11 Proceedings of the 2nd international conference on Circuits, Systems, Communications & Computers
Representing instructional design methods using ontologies and rules
Knowledge-Based Systems
An intelligent supplier evaluation, selection and development system
Applied Soft Computing
Relative entropy fuzzy c-means clustering
Information Sciences: an International Journal
| Hi-index | 12.05 |
This paper introduces a hybridization approach of AI techniques and statistical tools to evaluate and adapt the e-learning systems including e-learners. Learner's profile plays a crucial role in the evaluation process and the recommendations to improve the e-learning process. This work classifies the learners into specific categories based on the learner's profiles; the learners' classes named as regular, workers, casual, bad, and absent. The work extracted the statistical usage patterns that give a clear map describing the data and helping in constructing the e-learning system. The work tries to find the answers of the question how to return the bad students who are away back to be regular ones and find a method to evaluate the e-learners as well as to adapt the content and structure of the e-learning system. The work introduces the application of different fuzzy clustering techniques (FCM and KFCM) to find the learners profiles. Different phases of the work are presented. Analysis of the results and comparison: There is a match with a 78% with the real world behavior and the fuzzy clustering reflects the learners' behavior perfectly. Comparison between FCM and KFCM proved that the KFCM is much better than FCM.