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Abhinandan Alankar Mokal, Yash Ramesh Chorghe, Shubham Nandkishor Mokal, Atharv Varshanand Patil, Ankush Balaram Pawar
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- Student, Student, Student, Student, HOD, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (ViMEET), Khalapur, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (ViMEET), Khalapur, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (ViMEET), Khalapur, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (ViMEET), Khalapur, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (ViMEET), Khalapur, Maharashtra, Maharashtra, Maharashtra, Maharashtra, Maharashtra, India, India, India, India, India
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Abstract
nIn a rapidly evolving educational landscape, the role of technology and artificial intelligence (AI) in enhancing learning experiences has gained immense importance. The “ConnectED-AI” project represents a pioneering effort to leverage AI to empower students with personalized and effective educational resources.
This report provides an overview of the “ConnectED-AI” project, which is designed to address the diverse and dynamic learning needs of students. Our project aims to connect students with AI-driven educational resources, offering tailored study plans and curated question sets for various exams based on individualized preferences and available preparation time.
Through the integration of machine learning algorithms and data-driven insights, “ConnectED-AI” offers a user-friendly interface that allows students to input their exam details and study constraints. Subsequently, the system generates personalized study plans, recommends important questions, and provides access to relevant study materials.
This report discusses the methodology employed in data collection and system development, along with the system’s architecture and functionalities. We present the results of the “ConnectED-AI” project, demonstrating its effectiveness in assisting students in achieving their academic goals. Additionally, we engage in a thorough discussion of our findings, highlighting both the project’s successes and areas for improvement.
In response to these critical issues, the “ConnectED-AI” project adopts a data-driven, AI-powered approach to education. Anchored in cutting-edge technologies such as machine learning, natural language processing, and neural networks, this initiative aspires to deliver a transformative educational experience.
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Keywords: Personalized Learning, AI-Driven Education, Adaptive Study Plans, Educational Resources, Student Empowerment
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Open Source Developments(joosd)]
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References
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- https://www.techopedia.com/transforming-education-ai-powered-personalized-learning-revolution
- Lan, Q. (2021, February). Construction of personalized education model for college students driven by big data and artificial intelligence. In Journal of Physics: Conference Series(Vol. 1744, No. 3, p. 032022). IOP Publishing.
- González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467.
- Troussas, C., Krouska, A., Kabassi, K., Sgouropoulou, C., & Cristea, A. I. (2022). Artificial intelligence techniques for personalized educational software. Frontiers in Artificial Intelligence, 5, 988289.
- Zhang, Y., Qin, G., Cheng, L., Marimuthu, K., & Kumar, B. S. (2021). Interactive Smart Educational System Using AI for Students in the Higher Education Platform. Journal of Multiple-Valued Logic & Soft Computing, 36.
- Bajaj, R., & Sharma, V. (2018). Smart Education with artificial intelligence based determination of learning styles. Procedia computer science, 132, 834-842.
- Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022). AI-based personalized e-learning systems: Issues, challenges, and solutions. IEEE Access.
- Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24.
- Kokku, R., Sundararajan, S., Dey, P., Sindhgatta, R., Nitta, S., & Sengupta, B. (2018, April). Augmenting classrooms with AI for personalized education. In 2018 IEEE international conference on acoustics, speech and signal processing (ICASSP)(pp. 6976-6980). IEEE.
- https://hbr.org/2019/10/how-ai-and-data-could-personalize-higher-education
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| Volume | 11 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | April 2, 2024 | |
| Accepted | April 7, 2024 | |
| Published | April 15, 2024 |
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