Large Language Models Meet User Interfaces: The Case of Provisioning Feedback
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910413203963904 |
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| author | Pozdniakov, Stanislav Brazil, Jonathan Abdi, Solmaz Bakharia, Aneesha Sadiq, Shazia Gasevic, Dragan Denny, Paul Khosravi, Hassan |
| author_facet | Pozdniakov, Stanislav Brazil, Jonathan Abdi, Solmaz Bakharia, Aneesha Sadiq, Shazia Gasevic, Dragan Denny, Paul Khosravi, Hassan |
| contents | Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning. Current LLM usage involves conversational user interfaces (CUIs) for tasks like generating materials or providing feedback. However, this presents challenges including the need for educator expertise in AI and CUIs, ethical concerns with high-stakes decisions, and privacy risks. CUIs also struggle with complex tasks. To address these, we propose transitioning from CUIs to user-friendly applications leveraging LLMs via API calls. We present a framework for ethically incorporating GenAI into educational tools and demonstrate its application in our tool, Feedback Copilot, which provides personalized feedback on student assignments. Our evaluation shows the effectiveness of this approach, with implications for GenAI researchers, educators, and technologists. This work charts a course for the future of GenAI in education. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_11072 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Large Language Models Meet User Interfaces: The Case of Provisioning Feedback Pozdniakov, Stanislav Brazil, Jonathan Abdi, Solmaz Bakharia, Aneesha Sadiq, Shazia Gasevic, Dragan Denny, Paul Khosravi, Hassan Human-Computer Interaction Artificial Intelligence Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning. Current LLM usage involves conversational user interfaces (CUIs) for tasks like generating materials or providing feedback. However, this presents challenges including the need for educator expertise in AI and CUIs, ethical concerns with high-stakes decisions, and privacy risks. CUIs also struggle with complex tasks. To address these, we propose transitioning from CUIs to user-friendly applications leveraging LLMs via API calls. We present a framework for ethically incorporating GenAI into educational tools and demonstrate its application in our tool, Feedback Copilot, which provides personalized feedback on student assignments. Our evaluation shows the effectiveness of this approach, with implications for GenAI researchers, educators, and technologists. This work charts a course for the future of GenAI in education. |
| title | Large Language Models Meet User Interfaces: The Case of Provisioning Feedback |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2404.11072 |