Analysison Students’ Learning Habits: Identifyingthe Contributory Factorsof Learning Duringthe Covid-19 PandemicUsing Radial Basis Function (RBF)

Abstract

: The Artificial Neural Network (ANN) is an Artificial Intelligence technique that offer many benefits including the ability to process a vast amount of data, the ability to learn from experiences, and the good generalization capability. It was invented based on the concept of imitation of the human brain and built up of nodes that are like human neurons. The Radial Basis Function (RBF) is one of the established types of ANN. Considering the advantages and great performance of the RBF, this study aims to investigate the contributory factors of students’ learning habits during the Coronavirus Disease 2019 (or known as COVID-19) pandemic using RBF. Responses from a total of 420 respondents were collected from Vietnamese students’ learning habits during the COVID-19 pandemic dataset that was established from the questionnaires distributed in the period of 7th February 2020 to 28th February 2020. Fifteen independent variables were used as the input for the RBF network which is based on the 15-9-1 structure. Based on the experiment conducted, the implementation of the RBF model was found to be fair and effective with the small number of Sum of Square Error (SSE) and Relative Error (RE) produced. It could also be concluded that the most contributing factor of students’ learning habits during the COVID-19 pandemic is the learning hours per day for self-learning before the pandemic.