Application of Machine Learning

  Application of Machine Learning Techniques to Web-  Based Intelligent Learning Diagnosis System.

  This work proposes an intelligent learning

diagnosis system that supports a Web-based thematic

learning model, which aims to cultivate learners’ ability

of knowledge integration by giving the learners the opportunities

to select the learning topics that they are

interested, and gain knowledge on the specific topics by

surfing on the Internet to search related learning courseware

and discussing what they have learned with their

colleagues. Based on the log files that record the

learners’ past online learning behavior, an intelligent

diagnosis system is used to give appropriate learning

guidance to assist the learners in improving their study

behaviors and grade online class participation for the

instructor. The achievement of the learners’ final reports

can also be predicted by the diagnosis system accurately.

Our experimental results reveal that the proposed learning

diagnosis system can efficiently help learners to

expand their knowledge while surfing in cyberspace

Web-based “theme-based learning” model.

Keywords: Web-based learning, Theme-based learning,

Fuzzy expert system, K-nearest neighbor, Naïve Bayesian

classifier, Support vector machines, Learning diagnosis