Web Usage Mining data preprocessing and multi level analysis on Moodle

This research illustrates the potential of Web Usage Mining on e-Learning domain. We use educational data mining techniques to analyze learners' behavior, to help in learning evaluation and to enhance the structure of a given course. We focus on the preprocessing task, which is considered as the most crucial phase in the whole process. Our objective is to develop a data preprocessing method applied to Moodle logs based on SCORM content structure. In earlier works [1] [2], we proposed a preprocessing tool to implement these new methods and present the first discovered knowledge. In this research, we define new static variables according to the SCORM content tree and we apply more statistics and visualization techniques. In addition, we present multidimensional graphics in order to understand users' accesses. These aggregated variables provide teachers and tutors with interesting knowledge about students' learning process according to different levels of content accessed.

[1]  Sebastián Ventura,et al.  Educational data mining: A survey from 1995 to 2005 , 2007, Expert Syst. Appl..

[2]  Elena Álvarez,et al.  Towards Virtual Course Evaluation Using Web Intelligence , 2007, EUROCAST.

[3]  Jui-Long Hung,et al.  An Educational Data Mining Model for Online Teaching and Learning , 2012 .

[5]  Rajan Vohra,et al.  Applications of Data Mining in Higher Education , 2012 .

[6]  Ernestina Menasalvas Ruiz,et al.  Data Web house to support Web intelligence in e-learning environments , 2005, 2005 IEEE International Conference on Granular Computing.

[7]  Duncan Dubugras Alcoba Ruiz,et al.  A pre-processing tool for Web usage mining in the distance education domain , 2004, Proceedings. International Database Engineering and Applications Symposium, 2004. IDEAS '04..

[8]  Brigitte Trousse,et al.  Advanced data preprocessing for intersites Web usage mining , 2004, IEEE Intelligent Systems.

[9]  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).

[10]  Judy Sheard,et al.  Modelling learner and educator interactions in an electronic learning community , 2003 .

[11]  Bing Liu,et al.  Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data , 2006, Data-Centric Systems and Applications.

[12]  Sebastián Ventura,et al.  An architecture for making recommendations to courseware authors using association rule mining and collaborative filtering , 2009, User Modeling and User-Adapted Interaction.

[13]  Sfenrianto,et al.  A dynamic personalization in e-learning process based on triple-factor architecture , 2012, 2012 8th International Conference on Computing Technology and Information Management (NCM and ICNIT).

[14]  Sebastián Ventura,et al.  Applying Web usage mining for personalizing hyperlinks in Web-based adaptive educational systems , 2009, Comput. Educ..

[15]  Myra Spiliopoulou,et al.  Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis , 2004 .

[16]  Olfa Nasraoui,et al.  Advances in Web Mining and Web Usage Analysis: 6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004Seattle, WA, USA, August 22-25, ... Papers (Lecture Notes in Computer Science) , 2006 .

[17]  D. Jean-Marie,et al.  Méthodologie du recueil d'informations : Fondements des méthodes d'observation, de questionnaire, d'intervieuw et d'études de documents , 2009 .

[18]  Mohamed Jemni,et al.  Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval , 2008, 2008 Eighth IEEE International Conference on Advanced Learning Technologies.

[19]  Raquel Hijon,et al.  E-learning Platforms Analysis and Development of Students Tracking Functionality , 2006 .

[20]  Ilias Petrounias,et al.  A Framework for Using Web Usage Mining to Personalise E-learning , 2007, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007).

[21]  Robert Cooley,et al.  The use of web structure and content to identify subjectively interesting web usage patterns , 2003, TOIT.

[22]  Mykola Pechenizkiy,et al.  Handbook of Educational Data Mining , 2010 .

[23]  Jiang He.  Web Usage Mining , 2002 .

[24]  Karin Becker,et al.  Distance education: a Web usage mining case study for the evaluation of learning sites , 2003, Proceedings 3rd IEEE International Conference on Advanced Technologies.

[25]  Ryan S. Baker,et al.  The State of Educational Data Mining in 2009: A Review and Future Visions. , 2009, EDM 2009.

[26]  Kalina Yacef,et al.  Educational Data Mining: a Case Study , 2005, AIED.

[27]  Nikolaos Avouris,et al.  A Survey of Web-Usage Mining: Techniques for Building Web-Based Adaptive Hypermedia Systems , 2005 .