TY - JOUR
T1 - An adaptive sequencing method of the learning objects for the e-learning environment
AU - Seki, Kazuya
AU - Matsui, Tatsunori
AU - Okamoto, Toshio
PY - 2005/3
Y1 - 2005/3
N2 - In this study, an e-learning system is developed to handle the e-learning environment based on the learning ecological model. In the learning ecological model, which represents the comprehensive e-learning environment, not only the contents of learning, but also the learning environment are managed and provided, based on the content, the goal, and the configuration of the learning. The major purpose of this study is to realize the function that can manage the diversified learning objects with various information granularities and representation formats, using the learning object metadata, so that each learner can utilize the learning object based on the learning scenario, which is matched to the individual learner. The learning scenario is constructed by sequencing the learning objects based on the learning necessity, the learning history information, and the curriculum information of the object of learning, according to the characteristics of the learning object. As the sequencing procedure, the sequencing of the learning objects is considered, by applying the optimization technique of the multi-objective optimization problem, so that multiple evaluation viewpoints are simultaneously satisfied. The genetic algorithm is used as the optimization procedure. The learning object metadata and the sequencing of the learning objects are discussed in detail in this paper. The evaluation of the developed e-learning system is also described.
AB - In this study, an e-learning system is developed to handle the e-learning environment based on the learning ecological model. In the learning ecological model, which represents the comprehensive e-learning environment, not only the contents of learning, but also the learning environment are managed and provided, based on the content, the goal, and the configuration of the learning. The major purpose of this study is to realize the function that can manage the diversified learning objects with various information granularities and representation formats, using the learning object metadata, so that each learner can utilize the learning object based on the learning scenario, which is matched to the individual learner. The learning scenario is constructed by sequencing the learning objects based on the learning necessity, the learning history information, and the curriculum information of the object of learning, according to the characteristics of the learning object. As the sequencing procedure, the sequencing of the learning objects is considered, by applying the optimization technique of the multi-objective optimization problem, so that multiple evaluation viewpoints are simultaneously satisfied. The genetic algorithm is used as the optimization procedure. The learning object metadata and the sequencing of the learning objects are discussed in detail in this paper. The evaluation of the developed e-learning system is also described.
KW - Genetic algorithm
KW - LOM
KW - Multi-objective optimization problem
KW - Remote learning
KW - Sequencing of learning objects
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U2 - 10.1002/ecjc.20163
DO - 10.1002/ecjc.20163
M3 - Article
AN - SCOPUS:11144313734
SN - 1042-0967
VL - 88
SP - 54
EP - 71
JO - Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
JF - Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
IS - 3
ER -