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This study introduces an end-to-end framework for deploying artificial intelligence (AI) enabled educational assistants tailored specifically for environmental sciences learning needs in higher education. Leveraging state-of-the-art AI and natural language processing (NLP) technologies, the framework provides personalized learning experiences by facilitating access to complex environmental data and integrating seamlessly with Learning Management Systems (LMS) like Canvas and Moodle. The Educational AI Hub agents are designed to enhance course-specific learning by utilizing innovative document parsing methods, such as the Nougat technique, to accurately interpret educational content. The system offers tailored academic support, adapting to individual student needs and extending its capabilities to quantitative subjects through code execution. This study also emphasizes the importance of accessibility, inclusivity, and user privacy. The results showcase the potential for enhanced engagement and improved understanding of environmental concepts and software tools, demonstrating the significant impact of AI in educational settings, especially in disciplines involving complex data interactions. A case study, presented at the 12th International Congress on Environmental Modelling and Software, illustrates the Educational AI Hub's effectiveness in improving student engagement and personalized learning experiences in environmental sciences education.
Sajja et al. (2024) studied this question.