Identifying the Interest of Learning from Adult Learner Using Machine Learning

Abstract

The process of learning is continuous which will continue lifelong. This is potentially an essential tool for human survival and environment adaptation in both internally and externally. When instruction is catered to a learner's physical and mental capabilities, learning plays an important role. Adults are driven to learn for different reasons whereas the students expand on their prior learning and experience. Adults have a strong desire to take control of their learning and develop their own interests. The program's beneficiaries are adult learners, and without their participation, the initiative cannot succeed, wasting money, people, and other material resources which is not confused to reveal in sending people to the moon and accomplish fantastic possessions but this nation forgot to understand that the adult illiterates can able to render illiterate rate quickly. Teaching adults in the centers has become a monumental task. Adult education benefits from educational psychology's broader applicability, which encompasses learning theories, interest, memory, forgetting training transfer, theories of teaching, attitudes, skills, and environment. Therefore, this research concentrates on detecting the interest of adult learner using Tree-based Pipeline Optimization Tool (TPOT) for Automatic Machine Learning (AutoML) in the dataset collected from the Adult Learner Center in Tamil Nadu, India. Based on this pipeline, the resulted accuracy is better in Stochastic Gradient Descent (SGD) classifier while compared to another classifier in the TPOT for AutoML.