Data mining for student performance analysis by Clustering K-Means Algorithm
DOI:
https://doi.org/10.17762/msea.v71i3.467Abstract
Abstract
Data mining may analyse data and give fresh insights into student behaviour. Data mining methods may be used in formative assessment to assist instructors make important pedagogical decisions. It is data mining in education. Educational Data Mining involves discovering information from educational databases in novel ways.We classified the student's academic and personality achievements. This study suggests a method of categorising pupils to identify their ideal stream. Interests and capabilities may help predict student academic development.