EDUCATIONAL FUZZY DATA-SETS AND DATA MINING IN A LINEAR FUZZY REAL ENVIRONMENT

Frank Rogers
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Abstract

Educational data mining is the process of converting raw data from educational systems to useful information that can be used by educational software developers, students, teachers, parents, and other educational researchers. Fuzzy educational datasets are datasets consisting of uncertain values. The purpose of this study is to develop and test a classification model under uncertainty unique to the modern student. This is done by developing a model of the uncertain data that come from an educational setting with Linear Fuzzy Real data. Machine learning was then used to understand students and their optimal learning environment. The ability to predict student performance is important in a web or online environment. This is true in the brick and mortar classroom as well and is especially important in rural areas where academic achievement is lower than ideal.
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线性模糊真实环境下的教育模糊数据集与数据挖掘
教育数据挖掘是将来自教育系统的原始数据转换为可供教育软件开发人员、学生、教师、家长和其他教育研究人员使用的有用信息的过程。模糊教育数据集是由不确定值组成的数据集。本研究的目的是开发和检验一个现代学生特有的不确定性分类模型。这是通过开发一个不确定数据模型来完成的,这些数据来自一个教育环境,具有线性模糊真实数据。然后使用机器学习来了解学生和他们的最佳学习环境。在网络或在线环境中,预测学生表现的能力很重要。这在实体教室里也是如此,在学习成绩低于理想水平的农村地区尤其重要。
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0.00%
发文量
11
审稿时长
6 weeks
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