Paper Info
Title
Online Fault Detection Methodology of Question Moodle Database Using Scan Statistics Method.
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.
Year
DOI
Venue
2017
10.1007/978-3-319-67642-5_40
Communications in Computer and Information Science
Keywords
Field
DocType
E-learning,Moodle,Scan statistics
E learning,Knowledge assessment,Fault detection and isolation,Computer science,Database
Conference
Volume
ISSN
Citations 
756
1865-0929
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Aleksejs Jurenoks102.37
Svetlana Jurenoka200.34
Leonids Novickis3349.18