The proliferation of Large Language Models (LLMs), such as ChatGPT, has
raised concerns about their potential impact on academic integrity, prompting
the need for LLM-resistant exam designs. This article investigates the
performance of LLMs on exams and their implications for assessment, focusing on
ChatGPT's abilities and limitations. We propose guidelines for creating
LLM-resistant exams, including content moderation, deliberate inaccuracies,
real-world scenarios beyond the model's knowledge base, effective distractor
options, evaluating soft skills, and incorporating non-textual information. The
article also highlights the significance of adapting assessments to modern
tools and promoting essential skills development in students. By adopting these
strategies, educators can maintain academic integrity while ensuring that
assessments accurately reflect contemporary professional settings and address
the challenges and opportunities posed by artificial intelligence in education.

研究探讨了大型语言模型（LLMs），例如 ChatGPT 在考试中的表现及对评估的影响，并提出了创建 LLM 抗拒力考试的指南，旨在确保评估的公正性和准确性。