Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

Publications

3 Mining Educational Data to Support Students’ Major Selection

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well. 

Keywords: Data mining technique, the decision support system, knowledge and decision rules.

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2 Mining Educational Data to Analyze the Student Motivation Behavior

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

The purpose of this research aims to discover the knowledge for analysis student motivation behavior on e-Learning based on Data Mining Techniques, in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The data mining techniques was applied in this research including association rules, classification techniques. The results showed that using data mining technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: association rule mining, classification techniques, e- Learning, Moodle log Motivation Behavior

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1 Analysis of Student Motivation Behavior on e-Learning Based on Association Rule Mining

Authors: Kunyanuth Kularbphettong, Phanu Waraporn, Cholticha Tongsiri

Abstract:

This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: Motivation behavior, e-learning, moodle log, association rule mining.

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