First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008) 2008
DOI: 10.1109/wkdd.2008.139
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Web Usage Mining to Evaluate the Transfer of Learning in a Web-Based Learning Environment

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Cited by 24 publications
(14 citation statements)
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“…The analysis finds that the factors that affect the final score of the course have the learning type, the activity performance in the learning process, daily test scores and so on. Chanchary et al [25] use the association rule mining and decision tree classification method to find out the relationship between the user's use of learning management system and the final grade.…”
Section: Classification Algorithmmentioning
confidence: 99%
“…The analysis finds that the factors that affect the final score of the course have the learning type, the activity performance in the learning process, daily test scores and so on. Chanchary et al [25] use the association rule mining and decision tree classification method to find out the relationship between the user's use of learning management system and the final grade.…”
Section: Classification Algorithmmentioning
confidence: 99%
“…Log files are easy to record, flexible in the information they capture and useful in debugging. Normally, Web server log files contain the access date and time, the IP address of the request, the method of the request and the name of the file requested [35]. However, log files generated by Moodle are a little different because they not only contain the access date and time and IP address, but also other more specific information such as the user name (full name of the student), action (module and specific action performed by the user), and additional information about the action (see Fig.…”
Section: Data Gatheringmentioning
confidence: 99%
“…After this sorting step, it is easy to identify user sessions by grouping contiguous records from one login record to the next one. Specifically, browsing records picked out between two successive login records are grouped into a browsing session, and an upper limit of the time interval between two successive clicks has to be set (from 15 to 45 min) in order to break the sequence of one student's click stream into sessions [35]. This value may result in increasing or decreasing the total number of identified sessions.…”
Section: User and Session Identificationmentioning
confidence: 99%
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