灵活性,迭代:探索大型语言模型在开发和改进访谈协议方面的潜力

Jessica Parker, Veronica Richard, Kimberly Becker
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引用次数: 0

摘要

本文探讨了像ChatGPT这样的大型语言模型(LLM)工具在帮助研究人员开发和改进访谈协议方面的潜力。我们发现ChatGPT可以生成合适的面试问题,制作关键问题,提供关于协议的反馈,并模拟面试,这表明它具有减少时间和精力的潜力,特别是在人力资源有限的情况下。这篇文章建立在以前的作者的见解和建议,关于开发和完善访谈协议,以最大限度地实现研究目标的机会,特别是对新手研究人员。此外,研究人员强调了这些工具在适应不同研究背景和文化考虑方面的灵活性。强调道德考虑和人为监督是负责任地实施这些工具的关键组成部分。该研究也为进一步探索法学硕士与研究过程其他方面的整合铺平了道路,并为法学硕士在访谈协议开发和完善中的应用提供了建议。这一发现鼓励了对技术在学术研究中不断发展的作用的更广泛讨论,并为未来研究人类与人工智能在学术追求中的混合参与提供了一条令人兴奋的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexibility & Iteration: Exploring the Potential of Large Language Models in Developing and Refining Interview Protocols
This article investigates the potential of Large Language Model (LLM) tools like ChatGPT in aiding researchers in the development and refinement of interview protocols. We found that ChatGPT could generate appropriate interview questions, craft key questions, provide feedback on protocols, and simulate interviews, indicating its potential to reduce time and effort, particularly when human resources are limited. This article builds upon previous authors’ insights and suggestions regarding developing and refining interview protocols to maximize the chances of achieving research aims, especially for novice researchers. Additionally, the researchers highlight the flexibility of these tools in adapting to different research contexts and cultural considerations. Ethical considerations and human oversight are emphasized as critical components in the responsible implementation of these tools. The research also paves the way for further exploration into the integration of LLMs into other aspects of research processes and offers suggestions for the use of LLMs in interview protocol development and refinement. The findings encourage a broader discussion on the evolving role of technology in academic research and present an exciting avenue for future studies in hybrid human-AI engagements in scholarly pursuits.
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