Artificial Intelligence in Teacher Education: Challenges, Opportunities and Implications

Author(s): Dr. Mandeep Kumar and Ritu Garg

Abstract:

Artificial intelligence has substantially altered teaching and learning, supporting the transition from teacher-centered to student-centered education. The article discusses the broad implications of AI in education and synthesizes the opportunities and problems related with its adoption. Examining the impacts of AI on education, the article covers an extensive spectrum of educational contexts, ignoring any particular emphasis on specific forms of education or AI instruction alone. AI provides us opportunities for developing intelligent content that improves learning experiences while encouraging engagement and an approach that priorities learners. Smart content allows teachers to include multimedia, interactive tools, AI-related smart watches, and information technologies, thereby diversifying ways of learning and engaging students more effectively. Smart content creation connects with smart education frameworks, ensuring efficient content development. AI also aids in developing of intelligent tutoring systems, which replicate human tutors to provide personalized and adaptive learning experiences. These systems may store smart content, allowing for self-directed learning. Additionally, AI enhances virtual learning environments by analysing student data to adjust content and delivery methods to individual needs. It automates processes like grading and feedback, freeing teachers to focus on other important obligations. While AI provides numerous advantages, it is not without restrictions. Infrastructure requirements, considerations for inclusion and equity, teacher readiness and preparation, data quality and inclusivity, profit orientation, data privacy and ethical concerns, and the possibility of uneven access are all challenges. Addressing these restrictions is critical for maximizing the benefits of AI in education.

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Pages: 17-19     |    3 View     |    0 Download