Authoring Academic Resources for Science Education With a Generative AI Tool

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Authors: María Lucía Barrón-Estrada, Ramón Zataraín Cabada, Víctor Manuel Bátiz Beltrán, Aldo Uriarte-Portillo
Cited by: 0
References: 28

Abstract

This book chapter introduces an LLM-powered educational tool for building science learning environments using a fully cloud-based platform. The tool is an educational platform driven by LLM that attempts to save teachers time by automatized processes like lesson planning, grading, and resource generation. Using this platform, educators can modify and update pre-existing materials to fit the needs of any reader, produce unique science-related resources, and edit and distribute these materials to students. Any student can access instructional materials generated with the authoring tool interface through an internet-connected device. The tool accomplishes this by combining several technologies, including frameworks and tools like Ollama, JavaScript, and open-source LLMs like LLaMA 3, DeepSeek, Qwen2, and Gemma 2.

Fields of Study & Subjects

Mathematics Computing and Information Processing Intelligent Tutoring Systems and Adaptive Learning Educational Assessment and Pedagogy

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
207–246
Publication date
9 January 2026
Document type
Book chapter