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.
Authors
- Xianyi Li (ORCID: https://orcid.org/0009-0007-8962-3712)
- Junyi Chen (ORCID: https://orcid.org/0009-0005-3444-1714)
- Helmut Hahn
- Susan R. Fussell (ORCID: https://orcid.org/0000-0001-8980-5232)
- Xinhe Tian (ORCID: https://orcid.org/0009-0003-0491-9428)
- Madelyn K. Leon Carangui
- Yujia Si
Institutions
- Cornell University (US)
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