Ali Kamran, Barhom Noha, Tamimi Faleh, Duggal Monty
College of Dental Medicine QU Health, Qatar University, Doha, Qatar.
Eur J Dent Educ. 2024 Feb;28(1):206-211. doi: 10.1111/eje.12937. Epub 2023 Aug 7.
Open-source generative artificial intelligence (AI) applications are fast-transforming access to information and allow students to prepare assignments and offer quite accurate responses to a wide range of exam questions which are routinely used in assessments of students across the board including undergraduate dental students. This study aims to evaluate the performance of Chat Generative Pre-trained Transformer (ChatGPT), a generative AI-based application, on a wide range of assessments used in contemporary healthcare education and discusses the implications for undergraduate dental education.
This was an exploratory study investigating the accuracy of ChatGPT to attempt a range of recognised assessments in healthcare education curricula. A total of 50 independent items encompassing 50 different learning outcomes (n = 10 per item) were developed by the research team. These included 10 separate items based on each of the five commonly used question formats including multiple-choice questions (MCQs); short-answer questions (SAQs); short essay questions (SEQs); single true/false questions; and fill in the blanks items. Chat GPT was used to attempt each of these 50 questions. In addition, ChatGPT was used to generate reflective reports based on multisource feedback; research methodology; and critical appraisal of the literature.
ChatGPT application provided accurate responses to majority of knowledge-based assessments based on MCQs, SAQs, SEQs, true/false and fill in the blanks items. However, it was only able to answer text-based questions and did not allow processing of questions based on images. Responses generated to written assignments were also satisfactory apart from those for critical appraisal of literature. Word count was the key limitation observed in outputs generated by the free version of ChatGPT.
Notwithstanding their current limitations, generative AI-based applications have the potential to revolutionise virtual learning. Instead of treating it as a threat, healthcare educators need to adapt teaching and assessments in medical and dental education to the benefits of the learners while mitigating against dishonest use of AI-based technology.
开源生成式人工智能(AI)应用正在迅速改变信息获取方式,使学生能够准备作业,并对广泛的考试问题给出相当准确的答案,这些问题通常用于包括本科牙科学生在内的各类学生评估。本研究旨在评估基于生成式AI的应用程序Chat Generative Pre-trained Transformer(ChatGPT)在当代医疗保健教育中使用的各种评估中的表现,并讨论其对本科牙科教育的影响。
这是一项探索性研究,旨在调查ChatGPT在尝试医疗保健教育课程中一系列公认评估时的准确性。研究团队共开发了50个独立项目,涵盖50个不同的学习成果(每个项目n = 10)。这些项目包括基于五种常用问题格式中的每一种的10个单独项目,包括多项选择题(MCQs);简答题(SAQs);短文题(SEQs);单项是非题;以及填空题。使用Chat GPT尝试这50个问题中的每一个。此外,ChatGPT还用于根据多源反馈生成反思报告;研究方法;以及文献的批判性评价。
ChatGPT应用程序对基于MCQs、SAQs、SEQs、是非题和填空题的大多数基于知识的评估都提供了准确的答案。然而,它只能回答基于文本的问题,不允许处理基于图像的问题。除了文献的批判性评价外,对书面作业生成的回答也令人满意。字数是免费版ChatGPT生成的输出中观察到的关键限制。
尽管目前存在局限性,但基于生成式AI的应用程序有可能彻底改变虚拟学习。医疗保健教育工作者不应将其视为威胁,而应使医学和牙科教育中的教学和评估适应学习者的利益,同时防止不诚实地使用基于AI的技术。