Campus Connect - AI Powered Chatbot for Enhanced Student Engagement

Chatbots as question-answering systems can help in solving the challenges in the education sector, which includes the need for personalized learning and managing educator workload. It assists students and faculties by providing instant, accurate responses to answering queries, and offering learning resources. By utilizing Meta Llama's powerful language models and context-aware algorithms, the chatbot adapts to various user inputs, understanding complex queries and responding in conversational and informative manner. LLM chatbots utilize Natural Language Processing (NLP) techniques to link related topics and provide accurate responses to complex queries. In this work, a Groq API key is created to access the services in Groq Cloud platform. It is mainly utilized for build chatbots by leveraging the Llama language model, as it provides a platform to access easily and utilize the power of Llama's large language capabilities with high processing speed due to Groq's specialized hardware, making it ideal for creating fast and responsive chatbots. This work demonstrates the potential of LLMs like Meta Llama in creating efficient, scalable conversational agents for academic and organizational use.

Authors

Institutions

Publication Details

Journal
International Research Journal on Advanced Engineering and Management (IRJAEM)
Published
2025-04-16
DOI
https://doi.org/10.47392/irjaem.2025.0201
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Campus Connect - AI Powered Chatbot for Enhanced Student Engagement

B Sneha, D. Nithya, Sahana Lokesh R, J Rubika et al.
International Research Journal on Advanced Engineering and Management (IRJAEM)
AI in Service Interactions
article

Campus Connect - AI Powered Chatbot for Enhanced Student Engagement

B Sneha, D. Nithya, Sahana Lokesh R, J Rubika, H Swetha
article en

Abstract

Chatbots as question-answering systems can help in solving the challenges in the education sector, which includes the need for personalized learning and managing educator workload. It assists students and faculties by providing instant, accurate responses to answering queries, and offering learning resources. By utilizing Meta Llama's powerful language models and context-aware algorithms, the chatbot adapts to various user inputs, understanding complex queries and responding in conversational and informative manner. LLM chatbots utilize Natural Language Processing (NLP) techniques to link related topics and provide accurate responses to complex queries. In this work, a Groq API key is created to access the services in Groq Cloud platform. It is mainly utilized for build chatbots by leveraging the Llama language model, as it provides a platform to access easily and utilize the power of Llama's large language capabilities with high processing speed due to Groq's specialized hardware, making it ideal for creating fast and responsive chatbots. This work demonstrates the potential of LLMs like Meta Llama in creating efficient, scalable conversational agents for academic and organizational use.

International Research Journal on Advanced Engineering and Management (IRJAEM)Vol. 3(04)
Avinashilingam University (IN)
Openalex Percentile: Top 96%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Campus Connect - AI Powered Chatbot for Enhanced Student Engagement — B Sneha, D. Nithya, et al. · International Research Journal on Advanced Engineering and Management (IRJAEM) (2025) | TGRS Research Map | TGRS