AI Powered student assistance Chabot for department of Technical Education

This paper presents an AI-powered Student Assistance Chabot designed to streamline information access for students and reduce the workload on administrative staff, particularly within the Department of Technical Education, Government of Rajasthan. The Chabot addresses the challenge of efficiently handling a large volume of student inquiries regarding admissions, courses, scholarships, and other administrative information. Developed using Python and integrating web scraping techniques, the Chabot retrieves real-time data from the department's website. Natural Language Processing (NLP) enables the Chabot to understand and respond to user queries effectively. The current implementation focuses on providing information about universities, courses, and basic administrative procedures. The paper discusses the system architecture, including data collection, NLP processing, and response generation modules. Results from initial testing demonstrate the Chabot’s potential to provide accurate and timely information, with future enhancements planned to expand its capabilities and improve user experience.

Publication Details

Journal
REST Journal on Data Analytics and Artificial Intelligence
Published
2025-05-07
DOI
https://doi.org/10.46632/jdaai/4/1/84
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Powered student assistance Chabot for department of Technical Education

REST Journal on Data Analytics and Artificial Intelligence
IoT-based Smart Home Systems
article

AI Powered student assistance Chabot for department of Technical Education

article en

Abstract

This paper presents an AI-powered Student Assistance Chabot designed to streamline information access for students and reduce the workload on administrative staff, particularly within the Department of Technical Education, Government of Rajasthan. The Chabot addresses the challenge of efficiently handling a large volume of student inquiries regarding admissions, courses, scholarships, and other administrative information. Developed using Python and integrating web scraping techniques, the Chabot retrieves real-time data from the department's website. Natural Language Processing (NLP) enables the Chabot to understand and respond to user queries effectively. The current implementation focuses on providing information about universities, courses, and basic administrative procedures. The paper discusses the system architecture, including data collection, NLP processing, and response generation modules. Results from initial testing demonstrate the Chabot’s potential to provide accurate and timely information, with future enhancements planned to expand its capabilities and improve user experience.

REST Journal on Data Analytics and Artificial IntelligenceVol. 4(1 March 2025)
Openalex Percentile: Top 92%
IoT-based Smart Home Systems
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