On this website we will inform you about the AAA-Switch project MOCLog – Monitoring Online Courses with Logfiles.

Project Start Date:

Project End Date:

Project Leader:
Marco Bettoni

Teachers, students, study program managers and administrators need feedback about the status of the activities in online-courses. MOCLog will realize a monitoring system, that helps to analyze logfiles of the Moodle LMS more effectively and efficiently thus contributing to improve the quality of teaching and learning. 

Initial Situation

Using logfiles of learning management systems can help to determine who has been active in the course, what they did, and when they did it. Unfortunately, the logfiles provided by a LMS are seldom used mainly because it is difficult to interpret and exploit them; the obstacles to interpretation and exploitation fall into four main categories:

  1. certain types of usage data are not logged;
  2. the data that are logged may seem incomplete;
  3. users are afraid that they could draw unsound inferences from some of the data;
  4. data are not aggregated following a didactical perspective.

In the attempt of overcoming these difficulties, reporting functions of LMS have been extended, for instance Moodle now provides logs of non-anonymous data, a feature which enables teachers to evaluate the activity patterns of individual students. Moreover in the last few years researchers have begun to investigate various data mining methods which allow exploring, visualising, interpreting and analysing e-learning data thus helping teachers in better understanding and improving their e-learning practice.
Another line of research addressing the mentioned interpretation problem is that initiated by the GISMO project (USI.5), which developed a simple graphical interactive visualisation of Moodle logfiles and provides a good starting point for building up a tool.


The main aim consists in the realization of a monitoring system (based on a suitable interpretation model), that can help to analyze the logfiles of Moodle more effectively and efficiently thus contributing to improve the quality of teaching and learning in online courses. For example, logfile analyses can help in better understanding whether the courses provide a sound learning environment (availability and use of discussion forums, etc.) and implement best practices in online learning (students provide timely responses, teachers are visible and active, etc.).
The specific objectives that contribute to reach this aim are:

  • A more effective and efficient process of logfile analysis for online courses (MOCLog-process)
  • The definition of a suitable model of logfile analysis (MOCLog-model)
  • The design and implementation of a monitoring tool (MOCLog-tool) based on the MOC-log-model

MOCLog combines in a useful tool a didactical theory with physical data (logfiles).
One key feature is that it allows analyzing the use of the contents in the online-courses from a didactical point of view, thus going deeper than simply counting and visualising the numbers of posts and clicks.
Another key feature is to avoid using entries by students and to rely instead on logfiles (obtained from system reports) as an input and to evaluate the logfiles automatically. The goal here is to measure the status of activities in the online-course as much as possible without distortions, ‘objectively’, by relying exclusively either on logfile data or on planning data provided by the course administrators and by the teachers as reference values.

Model of logfile analysis
The focus lies on activities (interpreted from logfile data) and orientation (visualization by the MOCLog tool). The model is based on the theory of eLearning functions by Reinmann-Rothmeier (2003) and the methodology for the analysis of websites’ logfiles by Cantoni & Ceriani (2007). The model of the logfile analysis is necessary for interpreting the logfiles that are generated in Moodle by the users in a suitable way in terms of learning activities. The model is used in analyzing the logfiles and creating use cases (scenarios) for each stakeholder.


The benefits of MOCLog for the Swiss higher education sector are:

  • Offering relevant interpretation schemes for logfile analysis
  • Suitability of the interpretation schemes for transfer to other LMS
  • Easier and faster analyzing of the logfiles in the online courses in Moodle
  • Feedback (numeric, graphic) for different stakeholders
  • Serving all important users of the LMS
  • Monitoring the status in the course (students, teachers, etc.) only by using logfiles

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