Predicting Teachers� ICT Competence in a Philippine University Using J48 Algorithm

Abstract

Objectives: The advent of information technology causes a significant impact on pedagogy and using ICT technologies in school-related activities. With this argument, determining the teacher’s ICT competence is expected to yield a better or positive impact on the learners and the performance of the teachers itself, however, no model was developed in predicting teachers ICT competence. In line with this, it is empirical to study and develop a model that will help the university in predicting teacher’s ICT competence. Methods: Data mining approach utilizing J48 algorithm was applied in this paper to create a model suitable for the actual teachers’ characteristics in the University. Moreover, Cross-validation technique was used to validate the dataset to have an optimum and acceptable model and generating the Receiving Operating Characteristics Curve (ROC) Area under ROC Curve technique. Findings: Decision tree model and decision rule for classification were created. Additionally, there were 92.78% correctly classified with an AUC weighted mean of 92.4%. Also, the model has very high acceptability and accuracy in predicting Teacher’s ICT Competence. However, it also revealed that many teachers still need more exposure in utilizing ICT technologies in pedagogy and any school-related activities. Application/Improvements: The result of this study can be a basis for developing software that will automatically categorize or classify the Teacher’s ICT competence. For more improvement of this paper and the model, it is suggested to add additional parameters to have more factors involved in predicting Teacher’s ICT competence. Keywords: Blended Learning, Decision Tree, ICT Competency, ICT Domain, ICT Pedagogy, J48 Algorithm, Machine Learning