Various programs have emerged that provide statistical analysis of WWW access logs. These programs typically detail the number of accesses for a file and so on,
so these approaches are not suitable for the specific e-learning applications.
This research concerns visual e-learning log mining as a novel and specific
application of visual data mining of log data provided by e-learning commercial courses.
In this way it is available a set of graphics for observation of hundred of learners at a glance in order to discriminate between sequence of learning activities that yield good results and sequence that are not so effective. Moreover, using the proposed visualizations of learning track data, instructors identify individuals that need special attention.