Review on AI Chatbot for College Event Reminder

As digital technologies reshape higher education, the demand for intelligent systems that enhance communication and student support continues to grow. This paper presents a comprehensive study on the design and deployment of an AI powered chatbot system tailored specifically for college event reminders. The proposed system integrates state-of-the-art technologies including large language models (LLMs), natural language processing (NLP), and voice/multilingual interfaces to create a conversational assistant that is not only informative but also interactive and context aware. Drawing inspiration from various chatbot implementations across educational contexts, the system addresses key challenges such as data accessibility, user engagement, personalization, and emotional tone recognition. Features include scheduling, voice-based interactions, mood-sensitive responses, and dual-language support to ensure inclusivity. The chatbot is further enhanced by adaptive learning capabilities and memory augmentation, allowing it to simulate human-like understanding and recall relevant information over time.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-17
DOI
https://doi.org/10.5281/zenodo.15679228
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Review on AI Chatbot for College Event Reminder

Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Review on AI Chatbot for College Event Reminder

article en

Abstract

As digital technologies reshape higher education, the demand for intelligent systems that enhance communication and student support continues to grow. This paper presents a comprehensive study on the design and deployment of an AI powered chatbot system tailored specifically for college event reminders. The proposed system integrates state-of-the-art technologies including large language models (LLMs), natural language processing (NLP), and voice/multilingual interfaces to create a conversational assistant that is not only informative but also interactive and context aware. Drawing inspiration from various chatbot implementations across educational contexts, the system addresses key challenges such as data accessibility, user engagement, personalization, and emotional tone recognition. Features include scheduling, voice-based interactions, mood-sensitive responses, and dual-language support to ensure inclusivity. The chatbot is further enhanced by adaptive learning capabilities and memory augmentation, allowing it to simulate human-like understanding and recall relevant information over time.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 77%
AI in Service Interactions
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