Student Problem Solving and College Info Chatbot

Abstract

This paper presents the design and development of a College Information Chatbot System, an intelligent web-based application built to automate the handling of student queries, complaints, and feedback at KBP Polytechnic, Satara. The proposed system employs rule-based Natural Language Processing (NLP) techniques to interpret user input and deliver real-time, accurate responses related to admissions, fee structures, departments, courses, and campus facilities. The system integrates a structured complaint management module with ticket generation, an OTP-based authentication mechanism, a feedback collection interface, and an admin dashboard for complaint tracking and resolution. Additionally, the chatbot is extended to WhatsApp via the Twilio API, significantly improving accessibility. The backend is developed using Python Flask, with Firebase Realtime Database for cloud-based data storage. Evaluation through 30 functional test cases confirms that the system handles valid and invalid inputs correctly, maintains stable performance, and satisfies the primary objectives of automation, security, and usability. The system substantially reduces manual workload on administrative staff while improving student experience and institutional communication.

Introduction

The text describes a College Information Chatbot System designed to improve communication between students and educational institutions by replacing slow, manual query-handling processes with an automated AI-based solution. Traditional methods of answering student queries, managing complaints, and collecting feedback are inefficient, time-consuming, and lack transparency.

The proposed system uses Natural Language Processing (NLP) to understand student queries and provide real-time responses about admissions, fees, courses, and campus facilities. It also includes a structured complaint management system with ticket generation and status tracking, along with feedback collection for service improvement. The chatbot is accessible via a web interface and WhatsApp using the Twilio API, making it widely accessible.

Key objectives include automating student support, improving complaint tracking, enabling secure OTP-based authentication, providing an admin dashboard, and ensuring scalable data storage using Firebase Realtime Database. Literature review shows that while existing chatbots and complaint systems improve efficiency, they often lack integration, real-time tracking, and comprehensive functionality.

Conclusion

This paper presented the design, development, and evaluation of a College Information Chatbot System that automates student query handling, complaint management, and feedback collection at KBP Polytechnic, Satara. The system successfully replaces inefficient manual processes with an intelligent, accessible, and secure digital platform. The chatbot delivers instant, accurate responses to a wide range of student queries without requiring login, thereby reducing barriers to access. The structured complaint module with OTP authentication, ticket generation, and admin-driven resolution ensures transparent and accountable issue handling. Email notifications keep users informed throughout the process, and the admin dashboard provides administrators with comprehensive control and visibility. All 30 functional test cases passed, validating system correctness, stability, and usability. The WhatsApp integration via Twilio further extends the system\'s reach to mobile users on a familiar platform. Future enhancements include integration of machine learning and advanced NLP for improved intent recognition, development of a dedicated mobile application, full WhatsApp Business API deployment, voice-based interaction support, and integration with institutional ERP systems for real-time data synchronization.

References

[1] K. Vyas, N. Sharma et al., \"A Survey on Chatbot Systems and Technologies,\" IEEE, 2018. [2] S. Reshmi, K. Balakrishnan et al., \"Design and Implementation of Intelligent Chatbot System,\" IEEE, 2019. [3] R. Kumar, P. Singh et al., \"Development of FAQ Chatbot Using Natural Language Processing,\" IEEE, 2020. [4] A. Sharma, V. Gupta et al., \"Chatbot for Student Support System Using AI,\" IEEE, 2021. [5] M. Patel, S. Verma et al., \"Smart Helpdesk System Using Chatbot Technology,\" IEEE, 2020. [6] N. Singh, R. Mehta et al., \"Web-Based Complaint Management System,\" IEEE, 2019. [7] Twilio Documentation, WhatsApp Messaging API. Available: https://www.twilio.com/docs [8] Google Firebase Documentation. Available: https://firebase.google.com/docs [9] Flask Documentation, Pallets Projects. Available: https://flask.palletsprojects.com/ [10] Python Software Foundation, Python 3 Documentation. Available: https://docs.python.org/3/

Copyright

Copyright © 2026 Yash Ghadge, Pranav Dalvi, Suyash Chavan, Prof. Aasifa Bagwan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.