基于mamdani推理系统的智能辅导系统动机评估模型

Q2 Decision Sciences
Rajermani Thinakaran, Suriayati Chupra, Malathy Batumalay
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引用次数: 0

摘要

许多教育工作者已经使用了智能辅导系统提供的好处。要成为更加个性化和有效的辅导系统,需要考虑学生的特点。动机是学生的一个重要特征。因此,本研究提出了一个基于自我效能理论的动机评估模型。参照该理论,讨论了努力、活动选择、表现和坚持作为动机属性。此外,时间花费、难度水平、正确答案的数量和跳过的问题的数量是为每个属性定义的参数。该模型是利用Mamdani推理系统作为模糊逻辑技术的优势设计的,用于预测学生的动机水平。该模型能够像传统课堂上的人类导师一样让囚犯了解学生的动机水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motivation assessment model for intelligent tutoring system based on mamdani inference system
Many educators have used the benefit offer by intelligent tutoring system. To become more personalizing and effective tutoring system, student characteristics need to be considered. One of important student characteristic is motivation. Therefore, in this study a motivation assessment model based on self-efficacy theory was proposed. Refer to the theory, effort, choice of activities, performance and persistence were discussed as motivation attributes. Further, time spend, difficulty level, number of correct answers and number of questions skipped are the parameters was defined for each attribute. The model was designed by taking the advantages of Mamdani inference system as fuzzy logic technique to predict students’ motivation level. The model able to inmates like a human tutor does in the traditional classroom to understand students’ motivation level.
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来源期刊
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
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