Assessing Human Evaluations of Cover Letters Written or Edited by AI and Non-Native English Speakers

The assistance of AI plays a significant role in non-native English speakers’ (NNES) formal writing. To investigate the impact of AI on cover letter writing, we designed a survey-embedded experiment. In this study, participants read and evaluated the hireability and writing quality of cover letters created by 4 types of authors respectively: NNES-edited, NNES-written, AI-edited, and AI-written. We ultimately received 118 valid responses from native English Speakers (NES). The results indicated that (1) AI-edited cover letters perform significantly better than other three types of cover letters, but (2) The editing of NNES made the performance of AI-written cover letter worse. Our research provides insights into how artificial intelligence (AI) impacts NNESs with regards to cover letter writing, a critical part of the job application process. This outcome allows us to conclude that NNES would greatly benefit from using AI as an assistive writing tool during their job search.

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Publication Details

Published
2024-12-28
DOI
https://doi.org/10.1145/3688828.3699644
Citations
6
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
2.08
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article

Assessing Human Evaluations of Cover Letters Written or Edited by AI and Non-Native English Speakers

Xianyi Li, Junyi Chen, Helmut Hahn, Susan R. Fussell et al.
6 citations
Topic Modeling
2.08
article

Assessing Human Evaluations of Cover Letters Written or Edited by AI and Non-Native English Speakers

Xianyi Li, Junyi Chen, Helmut Hahn, Susan R. Fussell, Xinhe Tian, Madelyn K. Leon Carangui, Yujia Si
article en
6 citations

Abstract

The assistance of AI plays a significant role in non-native English speakers’ (NNES) formal writing. To investigate the impact of AI on cover letter writing, we designed a survey-embedded experiment. In this study, participants read and evaluated the hireability and writing quality of cover letters created by 4 types of authors respectively: NNES-edited, NNES-written, AI-edited, and AI-written. We ultimately received 118 valid responses from native English Speakers (NES). The results indicated that (1) AI-edited cover letters perform significantly better than other three types of cover letters, but (2) The editing of NNES made the performance of AI-written cover letter worse. Our research provides insights into how artificial intelligence (AI) impacts NNESs with regards to cover letter writing, a critical part of the job application process. This outcome allows us to conclude that NNES would greatly benefit from using AI as an assistive writing tool during their job search.

Cornell University (US)
Quality Education
Openalex Percentile: Top 11%
Topic Modeling
2.08
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Assessing Human Evaluations of Cover Letters Written or Edited by AI and Non-Native English Speakers — Xianyi Li, Junyi Chen, et al. · (2024) | TGRS Research Map | TGRS