期刊名称：An International Journal of Optimization and Control: Theories & Applications (IJOCTA)
印刷版ISSN：2146-5703
出版年度：2017
卷号：7
期号：3
页码：260-264
DOI：10.11121/ijocta.01.2017.00506
出版社：An International Journal of Optimization and Control: Theories & Applications (IJOCTA)
摘要：Advances in networks, computers and multimedia technology have changed traditional methods for learning and skills training. Nowadays, Virtual Environments for Training (VET) have been popular, they can provide an environment where virtual reality can be used to create interactive interfaces and real-time software that can control every response and action made by the user. VET have proven to be advantageous to put learners into varied training situations to acquire knowledge and competencies, especially when these situations are taking place in uncontrolled circumstances, or when they are dangerous, unrealizable, or expensive to establish in reality. However individual learners find it difficult to select suitable learning situations for their particular situation because often, there is no personalized service to response to the user needs. Personalization of learning in a VET is a very important way of improving the effectiveness and the quality of the training, yet it also a complex process that requires consideration of several factors such as learner‘s profiles. The goal is to associate suitable learning situations to each learner based on his profile. However, personalization of learning becomes an issue with the uncertainty and imprecision of data that may contains a learner profile. To address this issue, this study is an attempt to integrate a fuzzy clustering into the process of the personalization of learning.
其他摘要：Advances in networks, computers and multimedia technology have changed traditional methods for learning and skills training. Nowadays, Virtual Environments for Training (VET) have been popular, they can provide an environment where virtual reality can be used to create interactive interfaces and real-time software that can control every response and action made by the user. VET have proven to be advantageous to put learners into varied training situations to acquire knowledge and competencies, especially when these situations are taking place in uncontrolled circumstances, or when they are dangerous, unrealizable, or expensive to establish in reality. However individual learners find it difficult to select suitable learning situations for their particular situation because often, there is no personalized service to response to the user needs. Personalization of learning in a VET is a very important way of improving the effectiveness and the quality of the training, yet it also a complex process that requires consideration of several factors such as learner‘s profiles. The goal is to associate suitable learning situations to each learner based on his profile. However, personalization of learning becomes an issue with the uncertainty and imprecision of data that may contains a learner profile. To address this issue, this study is an attempt to integrate a fuzzy clustering into the process of the personalization of learning.
