Intelligent Learning System Based on SCORM Learning Objects

نویسندگان

  • Liliana Argotte-Ramos
  • Julieta Noguez
  • Gustavo Arroyo-Figueroa
چکیده

This paper shows the creation of the adaptive SCORM sequencing models, taking advantage of the latest developments offered by the artificial intelligence field, to provide the best choice to the student, based in learning objects, using a tutor model in self learning. The Tutor uses decision networks also called influence diagrams, to improve the development of resources and learning materials in a learning content management system, to offer students the best pedagogical decision according to their performance. The intelligent learning system is validated in an online environment. The results of the evaluation process in undergraduate engineering courses are encouraging because they show improvements in student's learning who used this approach, compared to those who did not use it. The paper also shows the potential application of this learning approach for power system's operators.

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تاریخ انتشار 2011