A Bilateral Self-Recursive ‘STA’ Contextualized Teaching Framework Based on Generative Artificial Intelligence

Xiang Li (), Han Zhang () and Shaozhong Cao ()
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Xiang Li: Beijing Institute of Graphic Communication
Han Zhang: Beijing Institute of Graphic Communication
Shaozhong Cao: Beijing Institute of Graphic Communication

A chapter in LISS 2024, 2025, pp 98-108 from Springer

Abstract: Abstract Education is vital for the development of the country. However, there are students who experience boredom during the school year, which undoubtedly leads to a decline in their learning status. Studies have shown that using contextualized exercises can boost students’ interest, but it would be very exhausting for teachers to consider each student's interest. With the development of generative AI, we can utilize large language models to help us do this. In this paper, we validate the capability of the ChatGPT model and propose a bilateral self-recursive STA contextualized teaching framework based on generative AI, and explore the application of AI in education.

Keywords: Generative AI; ChatGPT; Contextualized Teaching; Prompt Engineering (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-96-9697-0_9

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DOI: 10.1007/978-981-96-9697-0_9

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