Discovering sequential concept patterns for behavioural diagnosis by interpreting web‐page contents

Abstract

As web‐based courses become more popular, web systems can accumulate large amounts of log data. Because this data is generated by learners’ behaviour while studying web‐based courses, many researchers agree that analysing web logs could benefit learners, instructors and web‐site managers. This paper describes a study that used data‐mining techniques in order to analyse learners’ online behaviour for the purpose of extracting concept patterns—by transforming general web logs to a content perspective. An important advantage of this approach is that it can be used to identify concept patterns based on learning behaviour—rather than the more conventional browsing patterns based on browsing behaviour.

Acknowledgements

This project was supported by the National Science Council of Taiwan under contract number NSC 90‐2520‐S‐212‐001. The author wishes to express appreciation to Dr Cheryl Rutledge for her editorial assistance.