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Education management system powered by open AI

Tang, Wei Cherng (2024) Education management system powered by open AI. Final Year Project, UTAR.

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    Abstract

    In the current evolving landscape of education around the world, the need of an effective management and communication platform are increasing in demand for improving the learning experience for both educators and students mutually. This project aimed to develop a comprehensive MERN stack web application that provides a communication hub, classroom management and most importantly AI powered performance analytics for both students and educators. Some of the key feature includes performance analytics report and personalized journey learning plan generation paired with classroom management tools such as messaging, QnA. Besides that, the development methodology chosen for this project is incremental model, each module is iterated based on the previous cycle of design, development and testing. As mentioned above, this project is built with MERN stack which is MongoDB, Express, React and Nodejs which foster a clean architecture where it treat codes as a modular components that are dynamic. For the deployment of the system, the backend services were deployed using render and the front end is deployed using Netlify. The system was tested using a combination of automated unit testing, usability testing, and user acceptance testing (UAT) to validate the system functionalities and ensure it aligns with the requirements provided in the documentation. After the test, feedback from educators and students shows that there are some limitations and there is a need for more advanced student management tools and this paved the road for future enhancements for this project. In the end, the system successfully met the project objectives, offering a platform for educational management, encouraging a more engaging and organized learning environment with AI featured analytic modules.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: Q Science > QA Mathematics > QA76 Computer software
    T Technology > T Technology (General)
    Divisions: Lee Kong Chian Faculty of Engineering and Science > Bachelor of Science (Honours) Software Engineering
    Depositing User: Sg Long Library
    Date Deposited: 21 Nov 2024 13:46
    Last Modified: 21 Nov 2024 13:46
    URI: http://eprints.utar.edu.my/id/eprint/6824

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