ConnectED-AI: Connecting Education with Artificial Intelligence

Year : 2024 | Volume :11 | Issue : 01 | Page : 36-50
By

    Abhinandan Alankar Mokal

  1. Yash Ramesh Chorghe

  2. Shubham Nandkishor Mokal

  3. Atharv Varshanand Patil

  4. Ankush Balaram Pawar

  1. Student, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (VIMEET), Khalapur, Maharashtra, India
  2. Student, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (VIMEET), Khalapur, Maharashtra, India
  3. Student, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (VIMEET), Khalapur, Maharashtra, India
  4. Student, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (VIMEET), Khalapur, Maharashtra, India
  5. Head of Department, Department of Computer Science and engineering, Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (VIMEET), Khalapur, Maharashtra, India

Abstract

In 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.

Keywords: Personalized learning, AI-driven education, adaptive study plans, educational resources, student empowerment

[This article belongs to Journal of Open Source Developments(joosd)]

How to cite this article: Abhinandan Alankar Mokal, Yash Ramesh Chorghe, Shubham Nandkishor Mokal, Atharv Varshanand Patil, Ankush Balaram Pawar , ConnectED-AI: Connecting Education with Artificial Intelligence joosd 2024; 11:36-50
How to cite this URL: Abhinandan Alankar Mokal, Yash Ramesh Chorghe, Shubham Nandkishor Mokal, Atharv Varshanand Patil, Ankush Balaram Pawar , ConnectED-AI: Connecting Education with Artificial Intelligence joosd 2024 {cited 2024 Apr 15};11:36-50. Available from: https://journals.stmjournals.com/joosd/article=2024/view=143434


References

  1. Zia T. (2023). Transforming Education: AI-Powered Personalized Learning Revolution. [online] Techopedia. Available from: https://www.techopedia.com/transforming-education-ai-powered-personalized-learning-revolution
  2. Lan Q. Construction of personalized education model for college students driven by big data and artificial intelligence. J Phys Conf Ser. 2021; 1744 (3): 032022.
  3. González-Calatayud V, Prendes-Espinosa P, Roig-Vila R. Artificial intelligence for student assessment: a systematic review. Appl Sci. 2021; 11 (12): 5467.
  4. Troussas C, Krouska A, Kabassi K, Sgouropoulou C, Cristea AI. Artificial intelligence techniques for personalized educational software. Front Artif Intell. 2022; 5: 988289.
  5. Zhang Y, Qin G, Cheng L, Marimuthu K, Kumar BS. Interactive smart educational system using AI for students in the higher education platform. J Multiple-Valued Logic Soft Comput. 2021; 36 (1–3): 83–98.
  6. Bajaj R, Sharma V. Smart education with artificial intelligence based determination of learning styles. Procedia Computer Sci. 2018; 132: 834–842.
  7. Murtaza M, Ahmed Y, Shamsi JA, Sherwani F, Usman M. AI-based personalized e-learning systems: issues, challenges, and solutions. IEEE Access. 2022; 20: 81323–81342.
  8. Chassignol M, Khoroshavin A, Klimova A, Bilyatdinova A. Artificial intelligence trends in education: a narrative overview. Procedia Computer Sci. 2018; 136: 16–24.
  9. Kokku R, Sundararajan S, Dey P, Sindhgatta R, Nitta S, Sengupta B. Augmenting classrooms with AI for personalized education. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Alberta, Canada, April 15–20, 2018.pp. 6976–6980.
  10. Rouhiainen L. (October 14, 2019). How AI and Data Could Personalize Higher Education. [online] Harvard Business Review. Available from: https://hbr.org/2019/10/how-ai-and-data-could-personalize-higher-education
Regular Issue Subscription Review Article
Volume 11
Issue 01
Received April 2, 2024
Accepted April 7, 2024
Published April 15, 2024
Views: 27