Abstract
This paper describes the methodology for creating the intelligent, user adapted testing system that has been developed using LMS Moodle. The integration of the intelligent processes into the existing training systems will prevent the drawbacks of the existing knowledge assessment systems and will make it possible to assess the learners’ ability automatically disable problematics or incorrect questions from database question set.
The methodology to provide fast online fault detection in Moodle question database using scan statistics method is described. Scan statistics have long been used to detect statistically significant bursts of events. This research of student faults in time enables to detect the most problematics topics of educational process, check the efficiency of the decisions taken to select the education strategy.
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Jurenoks, A., Jurenoka, S., Novickis, L. (2017). Online Fault Detection Methodology of Question Moodle Database Using Scan Statistics Method. In: Damaševičius, R., Mikašytė, V. (eds) Information and Software Technologies. ICIST 2017. Communications in Computer and Information Science, vol 756. Springer, Cham. https://doi.org/10.1007/978-3-319-67642-5_40
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DOI: https://doi.org/10.1007/978-3-319-67642-5_40
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