AI EMPOWERED EDUCATION: TRANSFORMING TOMORROW’S LEARNERS WITH ARTIFICIAL INTELLIGENCE
Article Sidebar
Main Article Content
Abstract
Artificial Intelligence (AI) has emerged as a transformative force in education, revolutionizing the way we teach and learn. This research paper explores the impact of AI on education, focusing on its role in transforming learners’ experiences and outcomes. The paper begins with an overview of the evolution of AI in education, tracing its historical development and highlighting key milestones. It then delves into the various applications of AI in education, including personalized learning, adaptive assessments, and virtual tutoring, examining how these technologies enhance student engagement, achievement, and mastery of concepts. The paper also addresses the benefits of AI in education, such as improved learning outcomes, increased efficiency, and greater accessibility. However, it also acknowledges the challenges and considerations associated with AI implementation, such as data privacy concerns, bias in algorithms, and ethical considerations. Through case studies and success stories, the paper illustrates real-world examples of AI in educational settings and analyzes their impact on teaching practices and student learning. Looking ahead, the paper discusses future directions and implications of AI in education, including emerging trends and opportunities for innovation. Overall, this research paper underscores the transformative potential of AI in empowering tomorrow’s learners and shaping the future of education.
Downloads
Article Details
Section
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
References
Luckin, R. (2018). “Artificial Intelligence in Education: Promise and Implications for Teaching and Learning.” Pearson.
Maybury, M. T. (Ed.). (1998). “Intelligent Tutoring Systems: Evolutions in Design.” Springer.
Siemens, G., & Baker, R. S. (2012). “Learning Analytics and Educational Data Mining: Towards Communication and Collaboration.” Proceedings of the 2 nd International Conference on Learning Analytics and Knowledge.
Koedinger, K. R., & Corbett, A. T. (2006). “Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom.” The Cambridge Handbook of the Learning Sciences, 61-78.
Heffernan, N. T., & Heffernan, C. L. (2014). “The ASSISTments ecosystem: building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching.” International Journal of Artificial Intelligence in Education, 24(4), 470-497.
Smart Sparrow. (2021). “Adaptive Learning: The Ultimate Guide.” Retrieved from: https://www.smartsparrow.com/adaptive-learning-guide/
Riva, G., Baños, R. M., Botella, C., Mantovani, F., & Gaggioli, A. (2016). “Transforming experience: The potential of augmented reality and virtual reality for enhancing personal and clinical change.” Frontiers in Psychiatry, 7, 164.
Winter, S., & DeBotte, D. (2019). “Educational chatbots: A systematic review of the current state of the art.” IEEE Access, 7, 45165-45188.
Russell, S. J., & Norvig, P. (2016). “Artificial intelligence: A modern approach.” Malaysia; Pearson Education Limited.
Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., … & Gebru, T. (2019). “Model cards for model reporting.” In Proceedings of the conference on fairness, accountability, and transparency (pp. 220-229).