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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.02850 |
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| _version_ | 1866916618730209280 |
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| author | Kloker, Simon Luyima, Alex Cedric Bazanya, Matthew |
| author_facet | Kloker, Simon Luyima, Alex Cedric Bazanya, Matthew |
| contents | This paper introduces WASHtsApp, a WhatsApp-based chatbot designed to educate rural African communities on clean water access, sanitation, and hygiene (WASH) principles. WASHtsApp leverages a Retrieval-Augmented Generation (RAG) approach to address the limitations of previous approaches with limited reach or missing contextualization. The paper details the development process, employing Design Science Research Methodology. The evaluation consisted of two phases: content validation by four WASH experts and community validation by potential users. Content validation confirmed WASHtsApp's ability to provide accurate and relevant WASH-related information. Community validation indicated high user acceptance and perceived usefulness of the chatbot. The paper concludes by discussing the potential for further development, including incorporating local languages and user data analysis for targeted interventions. It also proposes future research cycles focused on wider deployment and leveraging user data for educational purposes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_02850 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | WASHtsApp -- A RAG-powered WhatsApp Chatbot for supporting rural African clean water access, sanitation and hygiene Kloker, Simon Luyima, Alex Cedric Bazanya, Matthew Computers and Society Artificial Intelligence Human-Computer Interaction Information Retrieval This paper introduces WASHtsApp, a WhatsApp-based chatbot designed to educate rural African communities on clean water access, sanitation, and hygiene (WASH) principles. WASHtsApp leverages a Retrieval-Augmented Generation (RAG) approach to address the limitations of previous approaches with limited reach or missing contextualization. The paper details the development process, employing Design Science Research Methodology. The evaluation consisted of two phases: content validation by four WASH experts and community validation by potential users. Content validation confirmed WASHtsApp's ability to provide accurate and relevant WASH-related information. Community validation indicated high user acceptance and perceived usefulness of the chatbot. The paper concludes by discussing the potential for further development, including incorporating local languages and user data analysis for targeted interventions. It also proposes future research cycles focused on wider deployment and leveraging user data for educational purposes. |
| title | WASHtsApp -- A RAG-powered WhatsApp Chatbot for supporting rural African clean water access, sanitation and hygiene |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction Information Retrieval |
| url | https://arxiv.org/abs/2411.02850 |