Implementation of a Generative AI Assistant in K-12 Education: The CyberScholar Initiative
This paper focuses on the piloting of CyberScholar, a Generative AI (GenAI) assistant tool that aims to provide feedback on writing K-12 contexts. The aim was to use GenAI to provide formative and summative feedback on students' texts in English Language Arts (ELA), Social Studies, and Modern World History. The trials discussed in this paper involved Grades 7, 8, 10, and 11 and were conducted in three schools in the Midwest and one in the Northwest of the United States. The tool used two main mechanisms: "prompt engineering" based on participant teachers' assessment rubric and "fine-tuning" a Large Language Model (LLM) from a customized corpus of teaching materials using Retrieval Augmented Generation. This paper focuses on CyberScholar's potential to enhance students' writing abilities and support teachers in diverse subject areas requiring written assignments.
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Language ModelingLanguage ModellingLarge Language ModelPrompt EngineeringRAGRetrieval-augmented GenerationSimilar Papers 제목 키워드 기반
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