ChatISA: A Prompt-Engineered, In-House Multi-Modal Generative AI Chatbot for Information Systems Education
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arXiv
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| Format: | Preprint |
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2024
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| author | Megahed, Fadel M. Chen, Ying-Ju Ferris, Joshua A. Resatar, Cameron Ross, Kaitlyn Lee, Younghwa Jones-Farmer, L. Allison |
| author_facet | Megahed, Fadel M. Chen, Ying-Ju Ferris, Joshua A. Resatar, Cameron Ross, Kaitlyn Lee, Younghwa Jones-Farmer, L. Allison |
| contents | As generative AI ('GenAI') continues to evolve, educators face the challenge of preparing students for a future where AI-assisted work is integral to professional success. This paper introduces ChatISA, an in-house, multi-model AI chatbot designed to support students and faculty in an Information Systems and Analytics (ISA) department. ChatISA comprises four primary modules: Coding Companion, Project Coach, Exam Ally, and Interview Mentor, each tailored to enhance different aspects of the educational experience. Through iterative development, student feedback, and leveraging open-source frameworks, we created a robust tool that addresses coding inquiries, project management, exam preparation, and interview readiness. The implementation of ChatISA provided valuable insights and highlighted key challenges. Our findings demonstrate the benefits of ChatISA for ISA education while underscoring the need for adaptive pedagogy and proactive engagement with AI tools to fully harness their educational potential. To support broader adoption and innovation, all code for ChatISA is made publicly available on GitHub, enabling other institutions to customize and integrate similar AI-driven educational tools within their curricula. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15010 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ChatISA: A Prompt-Engineered, In-House Multi-Modal Generative AI Chatbot for Information Systems Education Megahed, Fadel M. Chen, Ying-Ju Ferris, Joshua A. Resatar, Cameron Ross, Kaitlyn Lee, Younghwa Jones-Farmer, L. Allison Computers and Society Human-Computer Interaction Machine Learning As generative AI ('GenAI') continues to evolve, educators face the challenge of preparing students for a future where AI-assisted work is integral to professional success. This paper introduces ChatISA, an in-house, multi-model AI chatbot designed to support students and faculty in an Information Systems and Analytics (ISA) department. ChatISA comprises four primary modules: Coding Companion, Project Coach, Exam Ally, and Interview Mentor, each tailored to enhance different aspects of the educational experience. Through iterative development, student feedback, and leveraging open-source frameworks, we created a robust tool that addresses coding inquiries, project management, exam preparation, and interview readiness. The implementation of ChatISA provided valuable insights and highlighted key challenges. Our findings demonstrate the benefits of ChatISA for ISA education while underscoring the need for adaptive pedagogy and proactive engagement with AI tools to fully harness their educational potential. To support broader adoption and innovation, all code for ChatISA is made publicly available on GitHub, enabling other institutions to customize and integrate similar AI-driven educational tools within their curricula. |
| title | ChatISA: A Prompt-Engineered, In-House Multi-Modal Generative AI Chatbot for Information Systems Education |
| topic | Computers and Society Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2407.15010 |