Student Profiling on Academic Performance Using Cluster Analysis

Modelling Engineering Student Academic Performance Using

Mining Student data by Ensemble Classification and Clustering for Profiling and Prediction of Student Academic Performance

Applying Data Mining (DM) in education is an emerging interdisciplinary research field also known as Educational Data Mining (EDM). Ensemble techniques have been successfully applied in the context of supervised learning to increase the accuracy and stability of prediction. In this paper, we present a hybrid procedure based on ensemble classification and clustering that enables academicians to ...

Parent involvement and student academic performance: a multiple mediational analysis.

Parent involvement in a child's education is consistently found to be positively associated with a child's academic performance. However, there has been little investigation of the mechanisms that explain this association. The present study examines two potential mechanisms of this association: the child's perception of cognitive competence and the quality of the student-teacher relationship. T...

Evaluation of Student Academic Performance using Improved Prism

Data mining techniques (DMT) are extensively used in educational field to find new hidden patterns from student’s data. Today, one of the main challenges that educational institutions face is the explosive growth of educational data of students and to use this data to improve the quality of decision-making. The study’s curiosity is in predicting the paths of students, thus identifying the stude...

Predicting Student Academic Performance using Fuzzy ARTMAP Network

Predicting student academic performance plays an important role in academics. Classifying students using conventional techniques cannot give the desired level of accuracy, while doing it with the use of soft computing techniques may prove to be beneficial. A student can be classified into one of the available categories based on his behavioral and qualitative features. The paper presents a Neur...