Frank Rogers


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.


Student Learning Environment, Educational Fuzzy Data-sets, Linear Fuzzy Real Numbers, Machine Learning

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Journal of Honai Math
Universitas Papua
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