Advancing Education: An In-depth Analysis of Artificial Intelligence in Children`s Learning
Keywords:
Advanced Education, Artificial Intelligence, AI integration, children`s education, Personalized LearningAbstract
The rapid advancements in artificial intelligence (AI) have brought forth new opportunities and challenges for education, particularly in the learning experiences of children. This research paper delves into the multifaceted application of AI in children`s education, aiming to provide an in-depth analysis of its impact on various aspects of learning. The paper explores the advantages of AI integration in personalized learning, adaptive teaching methodologies, and cognitive development of young learners. Additionally, it examines the ethical considerations and potential risks associated with AI implementation in educational settings. By investigating case studies and experimental projects, this study seeks to offer valuable insights for educators, policymakers, and stakeholders to harness the potential of AI while ensuring responsible and effective integration in children`s learning environments.
References
Muhammad Ali Chaudhry & Emre Kazim , “Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021”, Springer : AI and Ethics, pp:157–165, 2022.
Pedró, Francesc , Subosa, Miguel , Rivas, Axel, Valverde, Paula ,” Artificial intelligence in education: challenges and opportunities for sustainable development”, Book Published in 2019 by the United Nations Educational, Scientific and Cultural Organization.
Xuesong Zhai, Xiaoyan Chu, Ching Sing Chai et al. “A Review of Artificial Intelligence (AI) in Education from 2010 to 2020” Hindawi Complexity Volume 2021, Article ID 8812542, 18 pages.
Weipeng Yang .,“Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation”, Computers and Education: Artificial Intelligence-Elsevier, Volume 3, 2022
Matthew N. O. Sadiku1, Tolulope J. Ashaolu, and Abayomi Ajayi-Majebi, and Sarhan M. Musa, “ Artificial Intelligence in Education”, International Journal of Scientific Advances, ISSN: 2708-7972 Volume: 2 | Issue: 1 | Jan - Feb 2021.
Ravi Kokku, Sharad C Sundararajan, Prasenjit Dey, Renuka Sindhgatta, “Augmenting Classrooms with AI for Personalized Education”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),Apr 2018 Pages 6976–6980 https://doi.org/10.1109/ICASSP.2018.8461812
Jiahong Su , Weipeng Yang ,“Artificial intelligence in early childhood education: A scoping review”, Computers and Education: Artificial Intelligence Volume 3, 2022
Heloísa Orsi Koch Delgado, Aline Fay de Azevedo, Maria José Sebastiany, Asafe Davi Cortina Silva “Artificial intelligence adaptive learning tools: The teaching of English in focus”, Brazilian English Language Teaching Journal BELT, Porto Alegre, V. 11, n. 2, p. 1-19, jul - 2020 e-ISSN: 2178-3640
Jiahong Su , Weipeng Yang ,“Artificial intelligence in early childhood education: A scoping review”, Computers and Education: Artificial Intelligence Volume 3, 2022.
Tinghong Lai, Chuyin Xie, Minhua Ruan, Zheng Wang, Hong Lu, Shimin Fu, “Influence of artificial intelligence in education on adolescents’ social adaptability: The mediatory role of social support” PLOS ONE Research Article Published: March 17, 2023.
KjhsdsjdsKevin M. Bonney ,“Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains”, Journal of Microbiology & Biology Education Published online 2015 May 1.
Ajv Yaqiong Zhu, “A Data Driven Educational Decision Support System” Educational Decision Support System. International Journal of Emerging Technologies in Learning (iJET), 13(11), pp. 4–16 Vol. 13 No. 11 (2018).
Jaba Wisnu Priambodo1,, Kristiawan Nugroho,, Kristophorus Hadiono3, “Impact of mBlock Interface Design on Student Interest and Motivation in Primary School Robotics: A Case Study in Indonesia”, International Journal of Scientific Research in Computer Science and Engineering Vol.11, Issue.4, pp.01-07, August 2023 E-ISSN: 2320-7639
Neetu Anand1* , Tapas Kumar, “Prediction of User Interest and Behaviour using Markov Model”, International Journal of Scientific Research Computer Science and Engineering, June, Vol.5, Issue.3, pp.119-123, 2017.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
