Analysis of web-based learning systems by data mining
William Villegas-Ch, Sergio Luján-Mora, Diego Buenaño-Fernández, Milton Román-Cañizares
IEEE Second Ecuador Technical Chapters Meeting (ETCM 2017), p. 1-5, Salinas (Ecuador), October 16-20 2017. ISBN: 978-1-5386-3894-1. https://doi.org/10.1109/ETCM.2017.8247553
(ETCM'17)
Congreso internacional / International conference
Resumen
This article describes the trend in the use of learning systems that aims to analyze information generated by students. This information is obtained from the activities of the learning management systems (LMS). The objective is to improve the quality of education and to allow institutions to offer the student a personalized education. For analysis of information, a description of the algorithms associated the data mining is provided. Another aspect considered are the tools that used to manage the data mining algorithms and present the information. Data can be evaluated in such a way as to convert the information collected into useful information, to provide an education tailored to the needs of each student. This approach seeks to improve the effectiveness of education by recognizing patterns in student performance. This article presents a study of the processes for the discovery of knowledge in LMS and the use of data mining techniques for data analysis. This analysis performed in a case study applied to the e-learning platform Moodle. The aim is to provide stakeholders with guidance on the use of information and communication technology tools.