Unlocking subjective answer assessment using ML and NLP

May 2025
Vol-11, Issue-3
Paper ID: 26537
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Django Web Application AI Chatbot NLP Machine learning
Abstract
The Student Management System is a web-based application developed using the Django framework, designed to streamline administrative and academic activities in educational institutions. This system caters to three primary user roles: Admin, Staff, and Students. Each role is assigned specific functionalities, ensuring efficient management and accessibility of resources. The Admin has full control over the system, including the management of users, subjects, courses, and other core data. Staff members can take attendance, manage results, respond to student feedback, and handle leave requests. Students can view their attendance records, exam results, apply for leave, and submit feedback. A key highlight of this system is the integration of an AI-powered chatbot, which helps students navigate the platform and get instant responses to academic or administrative queries. Moreover, the system includes a question-answer module for academic assessment, allowing staff to create quizzes or assignments and students to attempt them online. This project aims to reduce manual workload, improve data accuracy, and enhance communication between students and faculty. By leveraging Django’s secure, scalable architecture, the system ensures user-friendly interaction and role-based access control. The integration of AI and assessment tools makes the SMS not just a management tool but a smart academic companion for modern educational environments. at least 250 words.

Author Information

# Name Institute / Affiliation
1 Shruti Rajendra Patil P.E.S.Modern college of engineering
2 Ishwari Hemant Patil P.E.S Modern College of Engineering
3 Pallavi Nandkumar Ghatwal P.E.S Modern College of Engineering
4 Aanchal Mukesh Oswal P.E.S Modern College of Engineering
5 Mrs. Vidya Nemade P.E.S Modern College of Engineering

How to Cite

Use the following formats to cite this article in your research.

APA Style
Patil, Shruti Rajendra, Patil, Ishwari Hemant, Ghatwal, Pallavi Nandkumar, Oswal, Aanchal Mukesh, & Nemade, Mrs. Vidya (2025). Unlocking subjective answer assessment using ML and NLP. International Journal of Advance Research and Innovative Ideas In Education, 11(3), 1022-1029.
MLA Style
Patil, Shruti Rajendra, et al. "Unlocking subjective answer assessment using ML and NLP." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 3, 2025, pp. 1022-1029.
IEEE Style
Shruti Rajendra Patil, Ishwari Hemant Patil, Pallavi Nandkumar Ghatwal, Aanchal Mukesh Oswal, and Mrs. Vidya Nemade, "Unlocking subjective answer assessment using ML and NLP," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 3, pp. 1022-1029, 2025.
Vancouver Style
Patil Shruti Rajendra, Patil Ishwari Hemant, Ghatwal Pallavi Nandkumar, Oswal Aanchal Mukesh, Nemade Mrs. Vidya. Unlocking subjective answer assessment using ML and NLP. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(3):1022-1029.
Harvard Style
Patil, Shruti Rajendra, Patil, Ishwari Hemant, Ghatwal, Pallavi Nandkumar, Oswal, Aanchal Mukesh, & Nemade, Mrs. Vidya (2025) 'Unlocking subjective answer assessment using ML and NLP', International Journal of Advance Research and Innovative Ideas In Education, 11(3), pp. 1022-1029.
Chicago Style
Patil, Shruti Rajendra, et al. "Unlocking subjective answer assessment using ML and NLP." International Journal of Advance Research and Innovative Ideas In Education 11, no. 3 (2025): 1022-1029.
Turabian Style
Patil, Shruti Rajendra, et al. "Unlocking subjective answer assessment using ML and NLP." International Journal of Advance Research and Innovative Ideas In Education 11, no. 3 (2025): 1022-1029.

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