Implications of Artificial Intelligence for Teaching and Learning

Abstract

Artificial Intelligence (AI) has significantly transformed teaching and learning, facilitating a shift from teacher-centered to student-centered education. This review outlines the broad implications of AI for education and synthesizes both the opportunities and challenges associated with its implementation. Examining over 55 papers related to the impacts of AI on education, the review encompasses various educational contexts, avoiding a singular focus on specific types of education or the teaching of AI alone. According to the review, AI introduces new opportunities for creating intelligent content that enhances learning experiences, fostering interactivity and a student-centered approach. Smart content enables instructors to integrate multimedia, interactive tools, AI-related wearables, and information technologies, diversifying learning modes and engaging students more effectively. The creation of smart content aligns with smart education frameworks to ensure efficient content development. AI also contributes to the development of intelligent tutoring systems, which simulate human tutors to deliver personalized and adaptive educational experiences. These systems can host smart content, enabling independent learning. Additionally, AI improves virtual learning environments by analyzing student data to tailor content and delivery methods based on individual needs. It automates tasks such as grading and feedback, allowing teachers to concentrate on other essential responsibilities. While AI brings significant benefits, it is not without limitations. Challenges include infrastructure requirements, considerations of inclusion and equity, teacher readiness and preparation, data quality and inclusivity, profit orientation, data privacy and ethical concerns, and the potential for unequal access. Addressing these limitations is crucial for maximizing the positive impacts of AI in the realm of education.