Motivational Factors in ELT and Machine Learning

Generally, psychologists give more importance to motivation than intelligence. Motivation in education can drastically affect students’ learning. Subsequently, parents, teachers, and society are the factors to motivate youngsters to do better in future life. Among them, the teacher is the most important one. Thus, the experts in the field of education attempt to find a relationship between motivational factors and students' learning outcomes to put the students at a higher level in terms of motivation to look for a better result at the end of the course. Therefore, making use of random sampling, the researchers arranged with a total of ۹۹ students who were selecting General English to participate in the survey from both genders in PNU and AU. The data required were mainly gathered via a questionnaire that was in a ۵-point Likert-type scale using motivational factors. So, analyzing the data by Machine learning (ML) which is the innovative technology in the present study is the source of information for predicting students' performance in English courses. Usually, Linear Regression or Logistic Regression are used for analyzing data according to the dependent variables. Thus, Artificial Neural Network (ANN) is utilized to compare with logistic regression (LR). The accuracy of ۷۳.۳۳% for LR and ۹۳.۳۳% for ANN, indicated a much higher accuracy in ANN.

کلیدواژه ها:

Motivational Factors ، Learning ، Machine learning ، Logistic Regression ، Artificial Neural Network