Leiker, D; Finnigan, S; Gyllen, AR; Cukurova, M; (2023) Prototyping the use of Large Language Models (LLMs) for adult learning content creation at scale. In: Moore, S and Stamper, J and Tong, R and Cao, C and Liu, Z and Hu, X and Lu, Y and Liang, J and Khosravi, H and Denny, P and Singh, A and Brooks, C, (eds.) Proceedings of the Workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation 2023 co-located with 24th International Conference on Artificial Intelligence in Education (AIED 2023). (pp. pp. 3-7). CEUR Workshop Proceedings: Tokyo, Japan.

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Abstract

As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the use of LLMs in asynchronous course creation, particularly within the context of adult learning, training and upskilling. We developed a course prototype leveraging an LLM, implementing a robust human-in-the-loop process to ensure the accuracy and clarity of the generated content. Our research questions focus on the feasibility of LLMs to produce high-quality adult learning content with reduced human involvement. Initial findings indicate that taking this approach can indeed facilitate faster content creation without compromising on accuracy or clarity, marking a promising advancement in the field of Generative AI for education. Despite some limitations, the study underscores the potential of LLMs to transform the landscape of learning and education, necessitating further research and nuanced discussions about their strategic and ethical use in learning design.

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