Student Behavior Patterns in a Virtual Learning Environment

This work focuses on the identification of student behavior patterns obtained from their interactions on a virtual learning Environment (VLE). Clustering techniques were used to classify certain indicators and to obta in groups of students with similar characteristics. The activ ities performed are directly related to four Comput er Science degree courses in the Distance Education modality. Generally, our results show that students interacte d more with online forum, followed by the quiz, tasks, instant messaging, resources, and twitter. The knowledge ac quired via the data mining techniques helped to discover certa in characteristics of their online interaction, whi ch should be taken into account when enhancing the teaching-lear ning process.

[1]  Sebastián Ventura,et al.  Data mining in course management systems: Moodle case study and tutorial , 2008, Comput. Educ..

[2]  Heikki Mannila,et al.  Principles of Data Mining , 2001, Undergraduate Topics in Computer Science.

[3]  Pilar Rodríguez,et al.  A Mixed Approach to Modelling Learning Styles in Adaptive Educational Hypermedia , 2004 .

[4]  Jesus Boticario,et al.  Clustering learners according to their collaboration , 2009, 2009 13th International Conference on Computer Supported Cooperative Work in Design.

[5]  Paulo Blikstein,et al.  Using learning analytics to assess students' behavior in open-ended programming tasks , 2011, LAK.

[6]  Alfred Kobsa,et al.  The Adaptive Web, Methods and Strategies of Web Personalization , 2007, The Adaptive Web.

[7]  J. G. Boticario,et al.  Supporting a collaborative task in a web-based learning environment with Artificial Intelligence and User Modelling techniques , 2004 .

[8]  Ryan Shaun Joazeiro de Baker,et al.  Contextual Slip and Prediction of Student Performance after Use of an Intelligent Tutor , 2010, UMAP.

[9]  Jesus G. Boticario,et al.  Aplicación de métodos de diseño centrado en el usuario y minería de datos para definir recomendaciones que promuevan el uso del foro en una experiencia virtual de aprendizaje , 2012 .

[10]  Peter Brusilovsky,et al.  User Models for Adaptive Hypermedia and Adaptive Educational Systems , 2007, The Adaptive Web.

[11]  Gautam Biswas,et al.  Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning , 2012, EDM.

[12]  Elena Gaudioso,et al.  Mining Student Data To Characterize Similar Behavior Groups In Unstructured Collaboration Spaces , 2004 .

[13]  Ralf Klamma,et al.  Learning Analytics for Communities of Lifelong Learners: A Forum Case , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[14]  Sebastián Ventura,et al.  Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[15]  Judy Kay,et al.  Clustering and Sequential Pattern Mining of Online Collaborative Learning Data , 2009, IEEE Transactions on Knowledge and Data Engineering.