AI Powered Chatbot for College Information and Student Support

This study presents the development of an AI-powered chatbot tailored to assist college students with academic, campus-related, and personal development queries. Designed as a student-support software prototype, the system integrates natural language processing (NLP), text-to-speech (TTS), speech-to-text (STT), and machine learning models to deliver real-time information and interactive responses. Key features include course recommendations, timetable access, placement updates, NPTEL/hackathon alerts, library book availability, and image-based building identification. The chatbot also supports media uploads and provides mental health resources and career guidance through a conversational interface. Tested with over 50 student queries, it achieved a 92% response accuracy, identified college buildings from images with 85% accuracy, and reduced average information-seeking time by 65% compared to manual methods. Additionally, the inclusion of TTS and STT functionalities enhanced accessibility for differently abled users. This AI-driven solution fosters a smarter and more connected campus environment by streamlining support services and promoting student engagement. Future enhancements will focus on expanding the knowledge base, improving multilingual support, and refining interactive capabilities through broader user testing.

Authors

Publication Details

Journal
Asian Journal of Research in Computer Science
Published
2025-05-15
DOI
https://doi.org/10.9734/ajrcos/2025/v18i6680
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Powered Chatbot for College Information and Student Support

V. Kesavan, Santosh Kumar, Vidyut Prakash, S.Oviyan et al.
Asian Journal of Research in Computer Science
AI in Service Interactions
article

AI Powered Chatbot for College Information and Student Support

V. Kesavan, Santosh Kumar, Vidyut Prakash, S.Oviyan, R.Vishva
article en

Abstract

This study presents the development of an AI-powered chatbot tailored to assist college students with academic, campus-related, and personal development queries. Designed as a student-support software prototype, the system integrates natural language processing (NLP), text-to-speech (TTS), speech-to-text (STT), and machine learning models to deliver real-time information and interactive responses. Key features include course recommendations, timetable access, placement updates, NPTEL/hackathon alerts, library book availability, and image-based building identification. The chatbot also supports media uploads and provides mental health resources and career guidance through a conversational interface. Tested with over 50 student queries, it achieved a 92% response accuracy, identified college buildings from images with 85% accuracy, and reduced average information-seeking time by 65% compared to manual methods. Additionally, the inclusion of TTS and STT functionalities enhanced accessibility for differently abled users. This AI-driven solution fosters a smarter and more connected campus environment by streamlining support services and promoting student engagement. Future enhancements will focus on expanding the knowledge base, improving multilingual support, and refining interactive capabilities through broader user testing.

Asian Journal of Research in Computer ScienceVol. 18(6)
Openalex Percentile: Top 95%
AI in Service Interactions
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