GENERATIVE ARTIFICIAL INTELLIGENCE IN BASIC EDUCATION
THE CASE OF THE CYBERSCHOLAR PROTOTYPE
DOI:
https://doi.org/10.32748/revec.v11i27.22720Keywords:
Feedback generation, Writing, Prompt engineering, Human curationAbstract
This study examines the implementation of CyberScholar, a generative artificial intelligence tool under development for providing feedback on student writing in basic education across different school subjects. Trials were conducted with grades 7, 8, 10, and 11, at four schools in the United States. Using “prompt engineering” and “fine-tuning” a Large Language Model (LLM) via Retrieval Augmented Generation (RAG), the study qualitatively analyzes the prototype’s potential to enhance students’ writing skills and support teachers’ work. It also addresses human curation’s role in shaping GenAI outputs and envisions its future in education.
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