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PROBLEM SELECTION TO CONTROL CENTRE OPERATORS TRAINING

机译:控制中心操作员培训的问题选择

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Usually, the training programs available in industrial environment do not consider the particular training needs of each trainee. Individualized instruction is the main goal of an ITS. To achieve this, an ITS maintains a trainee model, which models the trainee's understanding of domain concepts. In a learning-by-doing system, one way to achieve this individualization is to provide the system with means to choose the next problem for the trainee. The chosen problem must be the most appropriate to the trainee's knowledge status. This paper presents a Curriculum Planning module used in an ITS to train Control Centre operators of the Portuguese electrical transmission network. The Curriculum Planning module involves two stages. First, the tutor must define the difficulty level of the problem, considering the trainee's progression. Heuristic rules are used to calculate the difficulty level. In the second phase, the tutor must use the contents of the user model to choose the type or types of the most suitable incidents to be included in the problem. A classification is performed in order to get the types of incidents that better match the trainee needs. The classification algorithm is based on a simple neural network in which activation values of the output units represent a measure of the adequacy of each type of incident to the trainee.
机译:通常,在工业环境中可用的培训计划不会考虑每个受训者的特定培训需求。个性化教学是ITS的主要目标。为了实现这一目标,ITS维护了受训者模型,该模型建立了受训者对领域概念的理解。在边做边学的系统中,实现这种个性化的一种方法是为系统提供选择受训者下一个问题的方法。选择的问题必须最适合学员的知识状况。本文介绍了在ITS中使用的课程计划模块,以培训葡萄牙电力传输网络的控制中心操作员。课程计划模块涉及两个阶段。首先,导师必须考虑学员的进度来定义问题的难度级别。启发式规则用于计算难度级别。在第二阶段,导师必须使用用户模型的内容来选择要包含在问题中的最合适事件的类型。进行分类是为了获得与学员需求更匹配的事件类型。分类算法基于简单的神经网络,其中输出单元的激活值表示对学员的每种类型的事件的适当性的度量。

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