Artificial Intelligence is A Key to Transforming Education
Abstract: Artificial intelligence is rapidly transforming several sectors, including education. This study investigates Artificial intelligence's expanding role in the education industry, focusing on its potential to improve learning experiences, increase administrative efficiency, and personalize educational material. The study concentrates on Artificial intelligence-powered tools such as intelligent tutoring systems, adaptive learning platforms, and natural language processing applications that are changing traditional classroom paradigms. The study examines different material and existing implementations to show how Artificial intelligence can adapt to various learning styles, provide real-time feedback, and create scalable solutions for learners and teachers. The study discusses the obstacles and ethical considerations related to Artificial intelligence adoption, including data privacy, algorithmic biases, and the need for teacher-student interactions. The study also explores the application of artificial intelligence, its key benefits, various challenges and limitations, and its impact on teachers and students. The findings imply that, while Artificial intelligence has great potential for transforming education, a balanced approach is required to effectively integrate it without compromising human-centric. The study concludes the significance of ongoing innovation, collaboration, and legislative frameworks for guiding Artificial intelligence incorporation in educational environments. However, today it is necessary to use different artificial intelligence tools in the education sector by taking care of its ethical considerations. With this, we can develop a technology-based citizen who can acquire 21st-century skills for a better lifestyle. So, this study will encourage the government to shift our education system to an AI-based one with an inculcated AI-based curriculum in the education system.
Institutions
- Rajarshee Chhatrapati Shahu Maharaj Government Medical College and CPR Hospital Kolhapur (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-11-30
- DOI
- https://doi.org/10.5281/zenodo.15016371
- Primary Topic
- Subterranean biodiversity and taxonomy
- Type
- article
- Field-Weighted Citation Impact
- 0.00