%0 Conference Paper
%A Riofrío Luzcando, Diego
%A Ramírez Rodríguez, Jaime
%B 8th International Conference on Educational Data Mining
%C Madrid, España
%D 2015
%F upm:41758
%I Universidad Nacional de Educación a Distancia
%K Intelligent Tutoring Systems; Educational Data Mining; Elearning; Procedural training; Virtual environments
%P 614-615
%T A model for student action prediction in 3D virtual environments for procedural training
%U https://oa.upm.es/41758/
%V 1
%X This paper presents a predictive student actionmodel, which uses student logs generated by a 3D virtual environment for procedural training to elaborate summarized information. This model can predict the most common behaviors by con- sidering the sequences of more frequent actions, which is useful to anticipate common student? errors. These logs are clustered based on the number of errors made by each stu- dent and the total time that each student spent to complete the entire practice. Next, for each cluster an extended au- tomata is created, which allows us to generate predictions more reliable to each student type. In turn, the action pre- diction based on this model helps an intelligent tutoring sys- tem to generate students? feedback proactively.