Sivasakthi M, Assistant Professor
Department of Comp. Science and Application CSH, SRM IST, Vadapalani, Chennai, Tamilnadu, India.
Pandiyan M, Assistant Professor
Department of Comp. Science CSH, SRM IST, Kattankulathur, Chennai, Tamilnadu, India.
Machine Learning Algorithms to Predict Students’ Programming Performance: A comparative Study
Authors
Abstract
Research on students’ academic performance is swiftly greater than ever in the field of
education, especially students’ performance in programming is crucial. Predicting the performance of
students in programming using machine learning algorithms and comparing them to suggest a best
model will bestow benefits to the students and teachers. Thus a study has been carried out to suggest a
best model for students’ learning in program by comparing the experiments results of Naïve Bayes and
Decision Tree, K-Nearest Neighbor, Support Vector Machine and Random Forest algorithms. Data
collection, pre-process and classification process are the sequence of steps for building and comparing
the models. Test results indicate that Naïve Bayes confers the best accuracy of 91.02% and SVM
algorithm has a high accuracy of 88.77%.