Exploring the role of AI in education

New advancements in machine learning and AI can be used to augment student learning and teacher capabilities. Examples of AI approaches in education include generating personalized student recommendations, autograding essays, and improving educational resources. AI programs intended to improve education can be categorized informally into three groups: Guidance, Learning, and Teacher. These categories are general and not necessarily mutually exclusive, but provide a framework for organization and further development. This paper intends to look at the past approaches of AI to improve education and categorize them to help guide new development of AI applications in education. The potential benefits of AI-powered education is noteworthy as the current economy is based on higher education. AI can be used to speed up labor-intensive tasks and help close the knowledge gap. Additionally, this paper also looks at potential drawbacks, such as ethics concerns of using student data to power AI. By analyzing the past use of AI in education, this paper seeks to provide a grouping framework to improve understanding of the field and facilitate future development. Framework for organization and further development. This paper intends to look at the past approaches of AI to improve education and categorize them to help guide new development of AI applications in education. The potential benefits of AI-powered education is noteworthy as the current economy is based on higher education. AI can be used to speed up labor-intensive tasks and help close the knowledge gap. Additionally, this paper also looks at potential drawbacks, such as ethics concerns of using student data to power AI. By analyzing the past use of AI in education, this paper seeks to provide a grouping framework to improve understanding of the field and facilitate future development.