How Non-native English Speakers Use, Assess, and Select AI-Generated Paraphrases with Information Aids
<|reference_start|>How Non-native English Speakers Use, Assess, and Select AI-Generated Paraphrases with Information Aids: Non-native English speakers (NNESs) often face challenges in achieving fluency in their written English. AI paraphrasing tools have the potential to improve their writing by suggesting more fluent paraphrases to their original sentences. Yet, the effectiveness of these tools depends on the user's ability to accurately assess and select context-appropriate suggestions, which is a significant challenge for those with limited English proficiency. This paper explores how NNESs utilize a paraphrasing tool augmented with information aids designed to facilitate the assessment of paraphrased suggestions. Through a formative study with 15 NNESs, we identify their specific needs when paraphrasing with AI, leading to the design of a paraphrasing tool integrated with five types of information aids, termed "support features." A user study with 22 NNESs demonstrates their heavy reliance on the paraphrasing functionality throughout the writing process, where they leverage the support features to assess and select suggestions efficiently and comprehensively. When equipped with the support features, NNESs experience enhanced writing experience in efficiency, confidence, and trust. Our findings contribute to the HCI community by (i) identifying the distinct needs of NNESs in AI paraphrasing tools, (ii) elucidating how NNESs use paraphrasing tools with support features, and (iii) offering design implications for the development of more effective AI paraphrasing tools tailored to NNESs' requirements.<|reference_end|>
@article{kim2024how,
    title={How Non-native English Speakers Use, Assess, and Select AI-Generated
  Paraphrases with Information Aids},
    author={Yewon Kim, Thanh-Long V. Le, Donghwi Kim, Mina Lee, Sung-Ju Lee},
    journal={arXiv preprint arXiv:2405.07475},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.07475},
    primaryClass={cs.HC}
}