AI-Driven Personalized Education Systems

Authors

  • Umesh Anand Author

Abstract

Personalized education systems have gained significant attention due to the potential to tailor educational experiences to individual students. Artificial Intelligence (AI) technologies play a pivotal role in the development and implementation of these systems. This paper explores the current landscape of AI-driven personalized education, discussing the key components, challenges, and opportunities in this field. We examine how machine learning algorithms, natural language processing, and data analytics enable the customization of learning paths, content delivery, and assessment methods. The paper also highlights the ethical and privacy considerations associated with personalized education systems. By leveraging AI, educators can better address the diverse learning needs of students, ultimately enhancing the quality of education.

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References

Chaitanya Krishna Suryadevara, “TOWARDS PERSONALIZED HEALTHCARE - AN INTELLIGENT MEDICATION RECOMMENDATION SYSTEM”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 9, p. 16, Dec. 2020.

Suryadevara, Chaitanya Krishna, Predictive Modeling for Student Performance: Harnessing Machine Learning to Forecast Academic Marks (December 22, 2018). International Journal of Research in Engineering and Applied Sciences (IJREAS), Vol. 8 Issue 12, December-2018, Available at SSRN: https://ssrn.com/abstract=4591990

Suryadevara, Chaitanya Krishna, Unveiling Urban Mobility Patterns: A Comprehensive Analysis of Uber (December 21, 2019). International Journal of Engineering, Science and Mathematics, Vol. 8 Issue 12, December 2019, Available at SSRN: https://ssrn.com/abstract=4591998

Chaitanya Krishna Suryadevara. (2019). A NEW WAY OF PREDICTING THE LOAN APPROVAL PROCESS USING ML TECHNIQUES. International Journal of Innovations in Engineering Research and Technology, 6(12), 38–48. Retrieved from https://repo.ijiert.org/index.php/ijiert/article/view/3654

Chaitanya Krishna Suryadevara. (2020). GENERATING FREE IMAGES WITH OPENAI’S GENERATIVE MODELS. International Journal of Innovations in Engineering Research and Technology, 7(3), 49–56. Retrieved from https://repo.ijiert.org/index.php/ijiert/article/view/3653

Chaitanya Krishna Suryadevara. (2020). REAL-TIME FACE MASK DETECTION WITH COMPUTER VISION AND DEEP LEARNING: English. International Journal of Innovations in Engineering Research and Technology, 7(12), 254–259. Retrieved from https://repo.ijiert.org/index.php/ijiert/article/view/3184

Chaitanya Krishna Suryadevara. (2021). ENHANCING SAFETY: FACE MASK DETECTION USING COMPUTER VISION AND DEEP LEARNING. International Journal of Innovations in Engineering Research and Technology, 8(08), 224–229. Retrieved from https://repo.ijiert.org/index.php/ijiert/article/view/3672

Anderson, T., & Whitelock, D. (2021). Personalised learning and AI: An ethical tension. Technology, Knowledge and Learning, 26(2), 201-218.

Blikstein, P., & Worsley, M. (2020). Learning analytics in higher education: Challenges and policies. Educause Review, 55(5), 30-41.

Johnson, M., & Ermolova, T. (2019). Deep learning in personalized education: Benefits, challenges, and trends. In Proceedings of the 10th International Conference on Educational Data Mining (pp. 229-236).

Kim, B., & Jang, H. (2018). Exploring the effects of artificial intelligence on personalized learning. Educational Technology Research and Development, 66(6), 1477-1493.

Siemens, G., & Gasevic, D. (2017). Personalized learning: The latest buzzword or a promising field? *Educational Technology, 57(3), 6-7.

Published

2023-11-05

Issue

Section

Articles

How to Cite

AI-Driven Personalized Education Systems. (2023). International Journal of Machine Learning and Artificial Intelligence, 3(3). https://jmlai.in/index.php/ijmlai/article/view/10

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