arXiv subjects

Erica Ann Metheney

Publications and source records attributed to Erica Ann Metheney.

2 recordsLinked to original sources

arXiv2025

Generative AI as a Safety Net for Survey Question Refinement

Writing survey questions that easily and accurately convey their intent to a variety of respondents is a demanding and high-stakes task. Despite the extensive literature on best practices, the number of considerations to keep in mind is vast and even small errors can render collected data unusable for its intended purpose. The process of drafting initial questions, checking for known sources of error, and developing solutions to those problems requires considerable time, expertise, and financial resources. Given the rising costs of survey implementation and the critical role that polls play in media, policymaking, and research, it is vital that we utilize all available tools to protect the integrity of survey data and the financial investments made to obtain it. Since its launch in 2022, ChatGPT and other generative AI model platforms have been integrated into everyday life processes and workflows, particularly pertaining to text revision. While many researchers have begun exploring how generative AI may assist with questionnaire design, we have implemented a prompt experiment to systematically test what kind of feedback on survey questions an average ChatGPT user can expect. Results from our zero--shot prompt experiment, which randomized the version of ChatGPT and the persona given to the model, shows that generative AI is a valuable tool today, even for an average AI user, and suggests that AI will play an increasingly prominent role in the evolution of survey development best practices as precise tools are developed.

stat.ME↗

arXiv2025

Exploring the Potential Role of Generative AI in the TRAPD Procedure for Survey Translation

This paper explores and assesses in what ways generative AI can assist in translating survey instruments. Writing effective survey questions is a challenging and complex task, made even more difficult for surveys that will be translated and deployed in multiple linguistic and cultural settings. Translation errors can be detrimental, with known errors rendering data unusable for its intended purpose and undetected errors leading to incorrect conclusions. A growing number of institutions face this problem as surveys deployed by private and academic organizations globalize, and the success of their current efforts depends heavily on researchers' and translators' expertise and the amount of time each party has to contribute to the task. Thus, multilinguistic and multicultural surveys produced by teams with limited expertise, budgets, or time are at significant risk for translation-based errors in their data. We implement a zero-shot prompt experiment using ChatGPT to explore generative AI's ability to identify features of questions that might be difficult to translate to a linguistic audience other than the source language. We find that ChatGPT can provide meaningful feedback on translation issues, including common source survey language, inconsistent conceptualization, sensitivity and formality issues, and nonexistent concepts. In addition, we provide detailed information on the practicality of the approach, including accessing the necessary software, associated costs, and computational run times. Lastly, based on our findings, we propose avenues for future research that integrate AI into survey translation practices.

cs.CL↗