Discussion
As it was found, homework assignments, demo exams, prior programming knowledge are correlated with final exam grade. Still, individual characteristics aren't considered in these variables that can explain low accuracy of the model 52%. Also, here as the authors have explained, they have multicollinearity issue. Lack of the features can also be the reason for having low performance. In case of predicting students who are at risk, there was even lower performance(46 4).
0
1
Tags
Data Science
Related
Introduction (Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model)
Literature Review (Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model)
Research Method (Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model)
Data Analysis and the Results (Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model)
Discussion