Development of a Model Using Data Mining Technique to Test, Predict and Obtain Knowledge from the Academics Results of Information Technology Students

Abstract

Due to the huge amount of data obtained from students’ academic results in most tertiary institutions such as the colleges, polytechnics and universities, data mining has become one of the most effective tools for discovering vital knowledge from students’ dataset. The discovered knowledge can be productive in understanding numerous challenges in the scope of education and providing possible solutions to these challenges. The main objective of this research is to utilize the J48 decision algorithm model to test, classify and predict the students’ dataset by identifying some important attributes and instances. The analysis was conducted on the final year students’ academic results in C# programming amongst five universities which was imported in csv excel file dataset in WEKA environment. These training datasets contained the scores obtained in the examinations, grade remarks, grades, gender, and department. The knowledge extracted for the prediction model will help both the tutors and students to determine the success grade performance in the future. Flow lines, J48 decision trees, confusion matrices and a program flowchart were generated from the students’ dataset. The KAPPA value obtained from the prediction in this research ranges from 0.9070–0.9582 which perfectly agrees with the standard for an ideal analysis on datasets.

Knowledge Discovery and Dataset for the Improvement of Digital Literacy Skills in Undergraduate Students

“…This is why decreasing the number of students who drop out before graduating is so crucial. Using data mining techniques, [12] suggested a novel recommendation system based on student data aimed at enhancing the number of university graduates by offering suitable subject selections.…”

“…In order to assess the impact of a VLE on learning outcomes, the VLE dataset was proposed. Some studies [11,12,14] have suggested datasets containing observations of students' ICT skill usage and evaluations of students' new technology learning skills. Digital Kids Asia Pacific (DKAP) published a new dataset encompassing 1061 observations of students' information and communication technology competence rates from several high schools across five Vietnamese regions and cities.…”