ChatGPTest: opportunities and cautionary tales of utilizing AI for questionnaire pretesting
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866911872935002112 |
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| author | Olivos, Francisco Liu, Minhui |
| author_facet | Olivos, Francisco Liu, Minhui |
| contents | The rapid advancements in generative artificial intelligence have opened up new avenues for enhancing various aspects of research, including the design and evaluation of survey questionnaires. However, the recent pioneering applications have not considered questionnaire pretesting. This article explores the use of GPT models as a useful tool for pretesting survey questionnaires, particularly in the early stages of survey design. Illustrated with two applications, the article suggests incorporating GPT feedback as an additional stage before human pretesting, potentially reducing successive iterations. The article also emphasizes the indispensable role of researchers' judgment in interpreting and implementing AI-generated feedback. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_06329 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ChatGPTest: opportunities and cautionary tales of utilizing AI for questionnaire pretesting Olivos, Francisco Liu, Minhui Computers and Society Artificial Intelligence The rapid advancements in generative artificial intelligence have opened up new avenues for enhancing various aspects of research, including the design and evaluation of survey questionnaires. However, the recent pioneering applications have not considered questionnaire pretesting. This article explores the use of GPT models as a useful tool for pretesting survey questionnaires, particularly in the early stages of survey design. Illustrated with two applications, the article suggests incorporating GPT feedback as an additional stage before human pretesting, potentially reducing successive iterations. The article also emphasizes the indispensable role of researchers' judgment in interpreting and implementing AI-generated feedback. |
| title | ChatGPTest: opportunities and cautionary tales of utilizing AI for questionnaire pretesting |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2405.06329 |