Artifi cial Intelligence Generated Content for Language Teaching and Learning Reform

Jing Xuan, Qiong Wu, Zhi Chen, Xingye Wu

Abstract


Artifi cial Intelligence Generated Content (AIGC) is a generative method that matches language patterns with existing data
and thus provides relevant content with appropriate generalization capabilities. The educational demand is to combine AIGC with teaching
resources, expanding traditional monomodal language teaching modes with Digital Multimodal Composing(DMC), so as to carry out
language teaching and learning reform. As a new Artifi cial Intelligence involved practice, language teachers lack technological experiences
to ensure class performance. In the process of creating DMC, learners pay more attention to entertainment rather than the practicability of its
content. AIGC can facilitate teaching with feasible methods to improve learning effi ciency and promote outcome.

Keywords


Artifi cial Intelligence Generated Content, Digital Multimodal Composing, Teaching and Learning Reform

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References


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DOI: https://doi.org/10.18686/esta.v10i3.457

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