Weber Educational Research & Instructional Studies

February 2019, Vol. 12 (4), ISSN:2449-1608

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 3.0 License.

Research Article

Use of the Data Mining Clustering Technique to Identify Student Behaviors in Virtual Environments

Felipe de Jesús Núñez Cardenas1, Ana María Felipe Redondo2   &  Víctor Tomás Tomás Mariano1

1Universidad Autónoma del Estado de Hidalgo - Escuela Superior Huejutla.
2Universidad Tecnológica de la Huasteca Hidalguense.



Accepted 17th February, 2019; Available Online 20th February, 2019.


Today, universities around the world are incorporating virtual platforms in order to bring their academic offer closer and increase their coverage. Under this context new schemes emerge that incorporate elements focused on meeting the needs of students in these environments. Although it is true that each student has a different learning style [1], according to different studies and models, it is also true that the development of materials within virtual learning environments must be addressed in these schemes [2]. Under this new teaching context, new questions emerge about the use that the students make of the new Information and Communication technologies that are included within the different platforms that implement the Universities for such effect [3]. This research focuses on the application of data mining algorithms, using the Clustering technique on the Weka tool, to describe the pattern of behavior of university students in virtual environments, specifically on the Moodle Platform. In this way, when knowing the different patterns of behavior, improvement projects can be implemented on the materials and activities of the virtual environment that match the learning styles predicted.

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