Acceptance of Chatbot based on Emotional Intelligence through Machine Learning Algorithm

In Artificial Intelligence, machine learning involves analyzing data and algorithms to improve accuracy and make human life more comfortable. In recent years, Artificial Intelligence strategies have been successfully applied to a wide range of educational purposes, including chatbots. Chatbot is an Artificial Intelligence tool that helps to improve academic strategies through its automated and intelligent features which enable the educational industry to develop students' learning abilities. Hence, the current study's goal is to combine the technology acceptance model (TAM) and emotional intelligence (EI) theory to evaluate the elements influencing the adoption of chatbot applications by implementing the proposed theoretical model. The qualitative result was evaluated through a questionnaire survey and data was collected from international students who have already experienced using chatbot applications in their university. Here, to examine the data and comprehend the relationship between the study models, machine learning method was used. After the investigation, according to the study's findings, Simple Logistic, Iterative Classifier Optimizer, and LMT classification classifiers had higher accuracy in predicting users' intention to use chatbots than 97.95% of the other classification classifiers. It is believed that the findings of the research will provide direction for students to promote chatbots better within educational activities in the future.