Identification of the Behavior and Preferences of the Users of a Virtual Campus Through Data Mining Techniques

• Published in: 2023 12th International Conference On Software Process Improvement (CIMPS) pp. 100 - 105
• Main Authors: Langs, Oswaldo Enrique Velez, Alvarez, Daniel Jose Salas, Arango, Alexander Fernandez
• Format: Conference Proceeding
• Language: English; Spanish
• Published: IEEE 18.10.2023
• Subjects: Analytical models; Data mining; Data models; Data visualization; Knowledge engineering; Learning management systems; predictive modeling; Predictive models; Web mining; web mining tools
• DOI: 10.1109/CIMPS61323.2023.10528816

This paper search for the understanding of the general behavior of users of the Learning Management System of the University of Cordoba (Montería-Colombia), using web usage mining of log files. For this purpose, it was necessary to carry out a process of exploration of the data stored in the virtual campus in the access reference files, through usage mining. Exploratory mining techniques were implemented, with which the way to approach the data obtained was identified, then the results were consolidated, which allowed for their contrast with the descriptive analysis and the results of the web data mining. It should be noted that the behavior suggested by the model in the grouping of data is like that of the users in the descriptive part of the analysis. It could be concluded that the generation of predictive models using web mining techniques can be a tool of great importance for the knowledge of the patterns and behavior of the users of the virtual platform of the University of Cordoba, as well as the possibility of using this as support for a future process of updating and analysis of these patterns and behaviors.