BEEXPERT: Voice-based Chatbot with Retrieval Augmented Generation for Personal High School Mathematics Tutor

Artificial Intelligence (AI) chatbots are increasingly used as personal tutors, especially in teaching high school mathematics. However, existing tools often lack conversational depth, neglect critical thinking, and risk providing false information. To address these issues, this paper introduces BEEXPERT, a voice-based chatbot designed to assist high school students in learning trigonometry. Powered by a Retrieval-Augmented Generation (RAG) system, it retrieves accurate, contextually relevant information from an OpenWebMath dataset of 515 trigonometry documents, supporting interactions in English and Indonesian. While the RAG system achieved substantial correctness (72.98%), it struggled with faithfulness (31.91%) and relevance (47.87%) due to hallucinations and context fragmentation. Feedback from preliminary testing and the Godspeed Questionnaire Series (GQS) highlights positive user reception, with 88% for likeability, 80% for perceived intelligence, and 75% for anthropomorphism. Expert validation also confirmed alignment with the school curriculum. Suggestions for improvement, such as refined prompts and enhanced features, have been partially implemented, with future updates planned to optimize the system further. In essence, BEEXPERT demonstrates significant potential as a personalized learning tool while highlighting areas for improvement to ensure a more robust and effective educational experience.

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Publication Details

Published
2025-07-30
DOI
https://doi.org/10.1109/icoict66265.2025.11192932
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

BEEXPERT: Voice-based Chatbot with Retrieval Augmented Generation for Personal High School Mathematics Tutor

Rhio Sutoyo, Dennis Alexander, Andry Chowanda, Ubaidah Ubaidah et al.
AI in Service Interactions
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BEEXPERT: Voice-based Chatbot with Retrieval Augmented Generation for Personal High School Mathematics Tutor

Rhio Sutoyo, Dennis Alexander, Andry Chowanda, Ubaidah Ubaidah, Angeline Mary Marchella, Naufal Hardiansyah, Nathaniel Candra
article en

Abstract

Artificial Intelligence (AI) chatbots are increasingly used as personal tutors, especially in teaching high school mathematics. However, existing tools often lack conversational depth, neglect critical thinking, and risk providing false information. To address these issues, this paper introduces BEEXPERT, a voice-based chatbot designed to assist high school students in learning trigonometry. Powered by a Retrieval-Augmented Generation (RAG) system, it retrieves accurate, contextually relevant information from an OpenWebMath dataset of 515 trigonometry documents, supporting interactions in English and Indonesian. While the RAG system achieved substantial correctness (72.98%), it struggled with faithfulness (31.91%) and relevance (47.87%) due to hallucinations and context fragmentation. Feedback from preliminary testing and the Godspeed Questionnaire Series (GQS) highlights positive user reception, with 88% for likeability, 80% for perceived intelligence, and 75% for anthropomorphism. Expert validation also confirmed alignment with the school curriculum. Suggestions for improvement, such as refined prompts and enhanced features, have been partially implemented, with future updates planned to optimize the system further. In essence, BEEXPERT demonstrates significant potential as a personalized learning tool while highlighting areas for improvement to ensure a more robust and effective educational experience.

Binus University (ID)
Openalex Percentile: Top 85%
AI in Service Interactions
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