The Use of Data Mining in the Development of a Web-Based Adaptive Teaching Style Model Based on David Kolb’s Learning Styles

Abstract

The purpose of this research was to develop a web-based adaptive teaching style model based on David Kolb’s learning styles. The data mining techniques are used to analyze student learning styles before they began the lessons. A teaching style system was divided into four subsystems according to a synthesized model recommended by selected experts. The system can adaptively provide contents based on student learning style. The results of an evaluation of the model indicate that the qualities of each teaching style, as well as the contents provided, were at the good level. After students used the teaching style system developed in the experimental phase, their learning achievement increased by a statistically significant value of .01. Additionally, student satisfaction with learning using the system was at the good level.