Prediction of Student Achievement through Teacher's Professional Characteristics by using Artificial Intelligence

Abstract

Teacher characteristics are important for teaching learning and are important predictors of students’ achievement. The present study aims to predict students’ academic achievement criteria on teachers’ characteristics with the help of artificial intelligence (AI). The data were collected from 100students from one of the universities in Lahore, Pakistan, through a questionnaire comprising of teachers’ characteristics effective for teaching, against a 4-point scale varying from strongly agree to strongly disagree to the find extant of the existence of certain characteristics in the teachers. The analysis was done to predict the student grade based on teacher characteristics in the class with the help of artificial intelligence. Two machine learning models were built, and their accuracy was compared. Thek-Nearest Neighbor (KNN) and Multiple Linear Regression (MLR) models were built. The accuracies of the KNN and MLR were 83 Percent and 91 Percent, respectively. This work concluded that the MLR model could be effectively used to predict student performance.