Knowledge discovery through supervised kohonen network to identify student’s knowledge level in adaptive hypermedia learning system

• Main Authors: Shamsuddin, Siti Mariyam, Yusob, Bariah
• Format: Conference or Workshop Item
• Language: English
• Published: 2006
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/25054/1/SitiMariyamShamsuddin2006_KnowledgeDiscoverythroughSupervisedKohonenNetwork.pdf; http://eprints.utm.my/id/eprint/25054/; http://comp.utm.my/pars/files/2013/04/Knowledge-Discovery-through-Supervised-Kohonen-Network-to-Identify-Student%E2%80%99s-Knowledge-Level-in-Adaptive-Hypermedia-Learning-System.pdf
• Institution: Universiti Teknologi Malaysia

SitiMariyamShamsuddin2006_KnowledgeDiscoverythroughSupervisedKohonenNetworkThis paper presents a study on method to identify the students’ characteristics in an adaptive hypermedia learning system. The study involves the use of student profiling techniques to identify the features that may be useful to help the researchers have a better understanding of the student in an adaptive learning environment. We propose a supervised Kohonen network with hexagonal lattice structure to classify the student into 3 categories: beginner, intermediate and advance to represent their knowledge level while using the learning system. An experiment is conducted to see the proposed Kohonen network’s performances compared to the other types of Kohonen networks in term of learning algorithm and map structure. 10-fold cross validation method is used to validate the network performances.