International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 181 - Number 42 |
Year of Publication: 2019 |
Authors: Esther Khakata, Vincent Omwenga, Simon Msanjila |
10.5120/ijca2019918466 |
Esther Khakata, Vincent Omwenga, Simon Msanjila . Student Performance Prediction on Internet Mediated Environments using Decision Trees. International Journal of Computer Applications. 181, 42 ( Feb 2019), 1-9. DOI=10.5120/ijca2019918466
A decision tree is a data classification technique that is used in mining data. The use of data mining techniques on data related to student performance assists in extracting valuable information from large data sets available within the institutions. This paper discusses the factors that influence the student learning process in an internet mediated environment and presents results from data collected within universities in Kenya. Additionally, this paper uses a decision tree to affirm these factors that affect student performance within the universities. The decision tree generated acts as a prediction tool that assists in the prediction of student performance while using internet technology in the learning process. This enables us determine whether a student is likely to perform well or not while using internet technology in the learning process.