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The Intelligent Web-based Instruction Using Data Mining Technique

Yanee Kachai, Narong Sompong


The design of web-based learning mostly does not consider the difference knowledge of individual learners. All contents are designed to be published into the web. Every learner with different knowledge level will force to study in the same content which will lead into information overload problem. This can also lead to misused and eventual failure. The research study aimed to achieve in designing and developing a model of intelligent Web-based Instruction applying Data Mining technique. The population of this research study was nine experts in educational technology, intelligent tutoring system and data mining technique domain. Research tools were structured interview and model evaluation form. Mean and S.D. were used to analyze the data. The result showed that the intelligent web-based instruction using data mining technique: EC-SPEC composed of six components: 1) Student Module 2) Expert Module 3) Content Module 4) Pedagogical Module 5) Communication Module, and 6) Evaluation Module. Data Mining techniques applied were Decision Tree and Sequential Pattern Mining. The overall model evaluation result from 9 experts showed that quality of model definition was ranked as high ( mean = 4.47). Model definition was ranked as high ( mean = 4.38 ). Goals were ranked as high ( mean = 4.74). Objectives were ranked as high ( mean = 4.39). Components were ranked as high ( mean = 4.46). Role of teachers and students were ranked as highest ( mean = 4.56) and evaluation tools were ranked as high ( mean = 4.33).


Web-based Instruction; Data Mining; Intelligent Web-based Instruction

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