Exploring AI-Generated Text in Student Writing: How Does AI Help?

David James Woo, Hengky Susanto, Chi Ho Yeung, Kai Guo, April Ka Yeng Fung
3/10/2023
cs.CLcs.AIcs.CY

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Abstract

English as foreign language_EFL_students' use of text generated from artificial intelligence_AI_natural language generation_NLG_tools may improve their writing quality. However, it remains unclear to what extent AI-generated text in these students' writing might lead to higher-quality writing. We explored 23 Hong Kong secondary school students' attempts to write stories comprising their own words and AI-generated text. Human experts scored the stories for dimensions of content, language and organization. We analyzed the basic organization and structure and syntactic complexity of the stories' AI-generated text and performed multiple linear regression and cluster analyses. The results show the number of human words and the number of AI-generated words contribute significantly to scores. Besides, students can be grouped into competent and less competent writers who use more AI-generated text or less AI-generated text compared to their peers. Comparisons of clusters reveal some benefit of AI-generated text in improving the quality of both high-scoring students' and low-scoring students' writing. The findings can inform pedagogical strategies to use AI-generated text for EFL students' writing and to address digital divides. This study contributes designs of NLG tools and writing activities to implement AI-generated text in schools.

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Cite this paper

@article{woo2023exploring,
  title  = {Exploring AI-Generated Text in Student Writing: How Does AI Help?},
  author = {David James Woo and Hengky Susanto and Chi Ho Yeung and Kai Guo and April Ka Yeng Fung},
  year   = {2023},
  eprint = {2304.02478},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2304.02478v2}
}

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