Deakin University
Browse

File(s) under permanent embargo

An Educational Data Mining System For Predicting And Enhancing Tertiary Students' Programming Skill

Version 2 2024-06-05, 10:09
Version 1 2023-07-06, 03:30
journal contribution
posted on 2024-06-05, 10:09 authored by Md Abu Marjan, MD PALASH UDDINMD PALASH UDDIN, Masud Ibn Afjal
Abstract Educational Data Mining (EDM) has become a promising research field for improving the quality of students and the education system. Although EDM dates back to several years, there is still lack of works for measuring and enhancing the computer programming skills of tertiary students. As such, we, in this paper, propose an EDM system for evaluating and improving tertiary students’ programming skills. The proposed EDM system comprises two key modules for (i) classification process and (ii) learning process,. The classification module predicts the current status of a student and the learning process module helps generate respective suggestions and feedback to enhance the student’s quality. In particular, for the classification module, we prepare a real dataset related to this task and evaluate the dataset to investigate six key Machine Learning (ML) algorithms, Support Vector Machine (SVM), decision tree, artificial neural network, Random Forest (RF), k-nearest neighbor and naive Bayes classifier, using accuracy-related performance measure metrics and goodness of the fit. The experimental results manifest that RF and SVM can predict the students more accurately than the other models. In addition, critical factors analysis is accomplished to identify the critical features toward achieving high classification accuracy. At last, we design an improvement mechanism in the learning process module that helps the students enhance their programming skills.

History

Journal

Computer Journal

Volume

66

Pagination

1083-1101

Location

Oxford, Eng.

ISSN

0010-4620

eISSN

1460-2067

Language

English

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

5

Publisher

Oxford University Press