SI-APRENDE: An Intelligent Learning System Based on SCORM Learning Objects for Training Power Systems Operators

被引:0
作者
Argotte, Liliana [1 ]
Arroyo-Figueroa, G. [1 ]
Noguez, Julieta [2 ]
机构
[1] Inst Invest Elect, Cuernavaca 62490, Morelos, Mexico
[2] Tecnol Monterrey, Mexico City 14380, DF, Mexico
来源
DEVELOPING CONCEPTS IN APPLIED INTELLIGENCE | 2011年 / 363卷
关键词
adaptive learning; intelligent environment; learning objects; SCORM; sequencing model; TUTORING SYSTEMS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the architecture of the Intelligent Learning Systems for training of power systems operators and describes one of its components: the tutor module. Operators can acquire knowledge in different ways or with different paths of learning, also called models of sequence. The tutor model is an adaptive intelligent system that selects the sequence of the learning material presented to each operator. The adaptive sequence is represented as a decision network that selects the best pedagogical action for each specific operator. The decision network represents information about the current state of the tutor, their possible actions, the state resulting from the action of the tutor and the usefulness of the resulting state. The model was evaluated using graduate students with good results. Based on the adaptive model, we developed an Intelligent Learning System called as SI-Aprende. The SI-Aprende system manages, spreads and promotes the knowledge by mean of the search and recovery of SCORM Learning Objects.
引用
收藏
页码:33 / +
页数:2
相关论文
共 6 条
[1]  
ARGOTTE L, 2010, THESIS I TECNOLOGICO
[2]   Intelligent Environment for Training of Power Systems Operators [J].
Arroyo-Figueroa, G. ;
Hernandez, Yasmin ;
Reyes, Alberto ;
Sucar, L. Enrique .
CERMA 2008: ELECTRONICS, ROBOTICS AND AUTOMOTIVE MECHANICS CONFERENCE, PROCEEDINGS, 2008, :27-+
[3]  
Brusilovsky P., 2003, International Journal of Continuing Engineering Education and Life-Long Learning, V13, P75
[4]   Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses [J].
Hake, RR .
AMERICAN JOURNAL OF PHYSICS, 1998, 66 (01) :64-74
[5]  
Hernández Y, 2005, LECT NOTES ARTIF INT, V3789, P1175
[6]   USING PLANNING TECHNIQUES IN INTELLIGENT TUTORING SYSTEMS [J].
PEACHEY, DR ;
MCCALLA, GI .
INTERNATIONAL JOURNAL OF MAN-MACHINE STUDIES, 1986, 24 (01) :77-98