Machine Learning in Education: An Overview of Applications and Datasets

Abstract

Artificial intelligence (AI) is a field of research that has attracted a lot of attention in the past few years due to itsrapid development and global reach. From integrating AI into everyday life, technology, and its use has drastically changedalong with the understanding of the world surrounding us. Its application ranges from automating mundane tasks to makingcrucial AI-driven decisions in medicine, entertainment, finance, and even retail. One of the most positive and profound areasof development in AI is in education because if developed further, it can change the ways education is rendered, enhance thequality of education, and most importantly, tailor the learning process according to the needs of students all over the world. AIis not a fad when it comes to educational learning but a very essential shift regarding how information is taught and learned.The goal of this paper is to analyze several applications of Machine Learning (ML), a subfield of artificial intelligence, inthe context of education. In particular, we want to focus on the variety of ML by defining supervised learning, unsupervisedlearning, reinforcement learning, and also deep learning, and their importance to the improved practice of education. Thesetechniques will be further explored in terms of real-life application in teaching and learning processes through illustrativecase studies. These case studies will illustrate how ML models aid in customizing learning, increasing student participation,and enhancing collaboration.