用GSP和GSM对英语阅读成绩进行聚类

IF 1 4区 工程技术 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Bor-tyng Wang, T. Sheu, Jung-Chin Liang, J. Tzeng, M. Nagai
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引用次数: 1

摘要

本文的目的是运用一种综合的方法对大学生的英语阅读表现进行聚类,因为很难找到适合单个学生的最佳教学策略。采用40道题的英语阅读统考来明确日间班和扩展班的不同表现,日间班和扩展班分别有38人和37人。然后生成包含Rasch模型方程的灰色学生问题(GSP)图。然后采用灰色结构建模(GSM)方法对学生进行分组。根据GSP图表和GSM,学生的阅读表现根据他们的水平分组。最后,我们使用解释结构模型(ISM)来显示各组的概念结构。此外,通过清晰的图表,家长可以更好地了解孩子的学习情况。我们建议GSP图不仅可以应用于教育领域,还可以应用于现实生活中,如医疗数据分析、工程或决策领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering the English Reading Performances by Using GSP And GSM
The purpose of this paper is to apply an integrated approach to cluster the English reading performances among college students because finding the optimal teaching strategy for an individual student is difficult. The unified English reading exam with forty questions was used to clarify the different performances between day-time and extension classes which have thirty-eight students and thirty-seven students, respectively. The Grey Student-Problem(GSP) chart, which includes the equation of Rasch model, was then generated. Then the method of Grey Structural Modeling (GSM ) was used to cluster the students into appropriate groups. According to the GSP chart and GSM, students' reading performances are clustered into classes based on their levels. Finally, we used Interpretive Structural Model (ISM) to display the concept structure of each group. The results indicate that the teachers could provide adaptive teaching methods and remedial instructions based on the graphic models. Also, parents could understand their children's learning conditions better by reading the clear graphs. We suggested that the GSP chart can not only be applied to the educational field, but also be used in real-life applications, like medical data analysis, engineering, or decision-making fields.
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来源期刊
Journal of Grey System
Journal of Grey System 数学-数学跨学科应用
CiteScore
2.40
自引率
43.80%
发文量
0
审稿时长
1.5 months
期刊介绍: The journal is a forum of the highest professional quality for both scientists and practitioners to exchange ideas and publish new discoveries on a vast array of topics and issues in grey system. It aims to bring forth anything from either innovative to known theories or practical applications in grey system. It provides everyone opportunities to present, criticize, and discuss their findings and ideas with others. A number of areas of particular interest (but not limited) are listed as follows: Grey mathematics- Generator of Grey Sequences- Grey Incidence Analysis Models- Grey Clustering Evaluation Models- Grey Prediction Models- Grey Decision Making Models- Grey Programming Models- Grey Input and Output Models- Grey Control- Grey Game- Practical Applications.
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