Using Generative AI to help with statistical test selection and analysis

Tom Goodale
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Abstract

One of the most common questions that students ask statistics advisors is ‘What test should I do?’ This paper explores the use of generative AI chatbots, specifically ChatGPT, as a tool to assist students, in particular those with limited experience in statistics, in selecting appropriate statistical tests for their analyses. Traditional methods, such as flowcharts and online test selectors, require at least a basic understanding of measurement scales and research design, which can be an issue for many students who have limited exposure to statistics on their courses. This research focuses on developing and refining prompts to guide ChatGPT in providing accurate and relevant statistical test recommendations. A hypothetical scenario was used to test the effectiveness of various prompts, ranging from simple, naïve questions to more sophisticated ones utilising specific prompt patterns, such as the ‘context manager’ and ‘flipped interaction.’ These patterns were selected to enhance the chatbot’s responses and ensure the relevance and accuracy of the test suggestions. The findings suggest that while AI chatbots like ChatGPT can be a valuable resource for students, their effectiveness is highly dependent on the quality of the prompts used. The paper concludes with a discussion on the potential of these AI tools in educational settings, acknowledging the limitations of current technology and suggesting directions for future research and development.
使用生成式人工智能帮助选择和分析统计测试
学生向统计学顾问提出的最常见问题之一是:"我应该做什么测试?本文探讨了如何使用生成式人工智能聊天机器人(特别是 ChatGPT)作为工具,帮助学生(尤其是统计学经验有限的学生)为其分析选择合适的统计检验。传统的方法,如流程图和在线测试选择器,至少需要对测量尺度和研究设计有基本的了解,而这对许多在课程中接触统计学有限的学生来说是个问题。本研究的重点是开发和改进提示,以指导 ChatGPT 提供准确和相关的统计测试建议。我们使用了一个假设场景来测试各种提示的有效性,从简单、幼稚的问题到使用特定提示模式(如 "上下文管理器 "和 "翻转互动")的更复杂的问题。选择这些模式是为了增强聊天机器人的回复能力,确保测试建议的相关性和准确性。研究结果表明,虽然像 ChatGPT 这样的人工智能聊天机器人可以成为学生的宝贵资源,但其有效性在很大程度上取决于所使用提示的质量。论文最后讨论了这些人工智能工具在教育环境中的潜力,承认了当前技术的局限性,并提出了未来研究和开发的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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