A multi-level model for tracking analysis in e-learning platforms

The generalized use of e-learning platforms both on campus and on distance learning scenarios promote a widespread dissemination of information among the users, however, an effective loss of "face-to-face" contact between tutor and student occurs. In this paper, a new 3-level classification model for tracking analysis on e-learning platforms is presented. In order to adopt this 3-level model a new data management system is introduced allowing the implementation of an information support system, an intelligent tutoring system and a decision support system, this way, improving the learning efficiency and overcoming the lack of "face-to-face" contact in previous e-learning approaches.

[1]  W. H. Inmon,et al.  Building the data warehouse , 1992 .

[2]  C. H. Ling,et al.  Correspondence between gated-diode drain current and charge pumping current in hot-carrier stressed n- and p-MOSFET's , 1997, 1997 21st International Conference on Microelectronics. Proceedings.

[3]  Osmar R. Zaïane,et al.  Building a Recommender Agent for e-Learning Systems , 2002, ICCE.

[4]  Margaret H. Dunham,et al.  Data Mining: Introductory and Advanced Topics , 2002 .

[5]  Sang Chan Park,et al.  Web mining for distance education , 2000, Proceedings of the 2000 IEEE International Conference on Management of Innovation and Technology. ICMIT 2000. 'Management in the 21st Century' (Cat. No.00EX457).

[6]  David Simões,et al.  VIANET-a new Web framework for distance learning , 2003, Proceedings 3rd IEEE International Conference on Advanced Technologies.

[7]  Tom Murray,et al.  Authoring Intelligent Tutoring Systems: An analysis of the state of the art , 1999 .