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The Impact of Generative AI on Chinese Poetry Instruction: Enhancing Students' Learning Interest, Collaboration, and Writing Ability
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Author(s): Sunyar Bishuang Wang (National Central University, Taiwan), Sandy I Ching Wang (National Central University, Taiwan)and Eric Zhi Feng Liu (National Central University, Taiwan)
Copyright: 2025
Volume: 15
Issue: 1
Pages: 21
Source title:
International Journal of Online Pedagogy and Course Design (IJOPCD)
Editor(s)-in-Chief: Chia-Wen Tsai (Ming Chuan University, Taiwan)and Pei-Di Shen (Ming Chuan University, Taiwan)
DOI: 10.4018/IJOPCD.375626
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Abstract
This study examines the potential of generative artificial intelligence (AI) to enhance Chinese poetry instruction by investigating its impact on students' learning interest, collaborative perception, and writing abilities. Through AI's text-to-image and image-to-poetry translation capabilities, the research explores how AI-generated visuals can deepen students' understanding of poetic imagery and foster creative expression in poetry writing. Using a mixed-methods approach, the study analyzes pre-test, mid-test, and post-test assessments, student surveys, and student-generated poetry to evaluate the effectiveness of this innovative pedagogical approach. The findings contribute to the growing field of educational technology in humanities education, offering insights into how AI can support multimodal learning, enhance students' linguistic creativity, and enrich their poetic sensibilities. By integrating AI technology with traditional literary instruction, this study provides a foundation for further research on the role of generative AI in language and arts education.
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