Learning about Online Learning Processes and Students' Motivation through Web Usage Mining.

This study illustrates the potential of applying Web usage mining the analysis of Web log files in educational research. It consists of two sub-studies and focuses on two types of analysis, both related to the whole learning process: investigating one learner's activity in order to learn about her or his learning process, and examining the activity of a large group of learners, in order to develop a log-based motivation measure. Subjects were 674 adults who used an online learning unit as part of their preparations for the Psychometric Academic Entrance Exam and whose log files were drawn. The first sub-study aimed to illustrate the knowledge about the online learner that can be extracted from log files, and this resulted in a list of computable, non computable, and higher-level learning variables. In the second sub-study, a log-based motivation measuring tool was developed on the basis of a theoretical framework, a mechanism for computing relevant learning variables, and a clustering of these variables into three groups (associated with the theoretical framework). A discussion of the results, in the context of educational Web mining, is provided.