Analysis of data mining techniques applied to LMS for personalized education


Abstract:

This article describes the models and the use of data mining techniques applied to Learning Management Systems (LMS) which allow institutions to offer the student a personalized education. It considers the ways in which the concepts of educational data mining (EDM) are applied to the information extracted from the LMS. The data from these systems can be evaluated 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 and efficiency of education by recognizing patterns in student performance. This article presents an analysis of the data mining techniques that fit LMS, specifically in terms of a case study applied to the e-learning platform Moodle. The objective is to provide stakeholders with guidance on the use of EDM tools.

Año de publicación:

2017

Keywords:

  • MOODLE
  • Data Mining
  • e-Learning

Fuente:

scopusscopus
googlegoogle

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Minería de datos
  • Ciencias de la computación

Áreas temáticas:

  • Ciencias de la computación