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乌干达医学生中ChatGPT和其他人工智能工具的广泛使用:一项横断面研究。

Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study.

作者信息

Ajalo Elizabeth, Mukunya David, Nantale Ritah, Kayemba Frank, Pangholi Kennedy, Babuya Jonathan, Langoya Akuu Suzan, Namiiro Amelia Margaret, Nsubuga Yakobo Baddokwaya, Mpagi Joseph Luwaga, Musaba Milton W, Oguttu Faith, Kuteesa Job, Mubuuke Aloysius Gonzaga, Munabi Ian Guyton, Kiguli Sarah

机构信息

Department of Community and Public Health, Busitema University, Mbale, Uganda.

Mbarara University of Science and Technology, Mbarara, Uganda.

出版信息

PLoS One. 2025 Jan 9;20(1):e0313776. doi: 10.1371/journal.pone.0313776. eCollection 2025.

Abstract

BACKGROUND

Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, it has introduced new challenges and threats to medical education. We assessed the use of ChatGPT and other AI tools among medical students in Uganda.

METHODS

We conducted a descriptive cross-sectional study among medical students at four public universities in Uganda from 1st November 2023 to 20th December 2023. Participants were recruited by stratified random sampling. We used a semi-structured questionnaire to collect data on participants' socio-demographics and use of AI tools such as ChatGPT. Our outcome variable was use of AI tools. Data were analyzed descriptively in Stata version 17.0. We conducted a modified Poisson regression to explore the association between use of AI tools and various exposures.

RESULTS

A total of 564 students participated. Almost all (93%) had heard about AI tools and more than two-thirds (75.7%) had ever used AI tools. Regarding the AI tools used, majority (72.2%) had ever used ChatGPT, followed by SnapChat AI (14.9%), Bing AI (11.5%), and Bard AI (6.9%). Most students use AI tools to complete assignments (55.5%), preparing for tutorials (39.9%), preparing for exams (34.8%) and research writing (24.8%). Students also reported the use of AI tools for nonacademic purposes including emotional support, recreation, and spiritual growth. Older students were 31% less likely to use AI tools compared to younger ones (Adjusted Prevalence Ratio (aPR):0.69; 95% CI: [0.62, 0.76]). Students at Makerere University were 66% more likely to use AI tools compared to students in Gulu University (aPR:1.66; 95% CI:[1.64, 1.69]).

CONCLUSION

The use of ChatGPT and other AI tools was widespread among medical students in Uganda. AI tools were used for both academic and non-academic purposes. Younger students were more likely to use AI tools compared to older students. There is a need to promote AI literacy in institutions to empower older students with essential skills for the digital age. Further, educators should assume students are using AI and adjust their way of teaching and setting exams to suit this new reality. Our research adds further evidence to existing voices calling for regulatory frameworks for AI in medical education.

摘要

背景

聊天生成预训练变换器(ChatGPT)是一个拥有1750亿参数的自然语言处理模型,它使用深度学习算法,基于大量数据进行训练,以生成类似人类撰写的文本,如文章。因此,它给医学教育带来了新的挑战和威胁。我们评估了乌干达医学生对ChatGPT和其他人工智能工具的使用情况。

方法

2023年11月1日至2023年12月20日,我们在乌干达四所公立大学的医学生中开展了一项描述性横断面研究。通过分层随机抽样招募参与者。我们使用半结构化问卷收集参与者的社会人口统计学信息以及对ChatGPT等人工智能工具的使用情况。我们的结果变量是人工智能工具的使用情况。在Stata 17.0版本中对数据进行描述性分析。我们进行了修正泊松回归,以探讨人工智能工具的使用与各种暴露因素之间的关联。

结果

共有564名学生参与。几乎所有学生(93%)都听说过人工智能工具,超过三分之二(75.7%)的学生曾使用过人工智能工具。在使用过的人工智能工具方面,大多数(72.2%)学生曾使用过ChatGPT,其次是SnapChat AI(14.9%)、必应AI(11.5%)和巴德AI(6.9%)。大多数学生使用人工智能工具来完成作业(55.5%)、准备辅导课(39.9%)、备考(34.8%)和进行研究写作(24.8%)。学生们还报告将人工智能工具用于非学术目的,包括情感支持、娱乐和精神成长。与年轻学生相比,年长学生使用人工智能工具的可能性低31%(调整患病率比(aPR):0.69;95%置信区间:[0.62, 0.76])。与古卢大学的学生相比,马凯雷雷大学的学生使用人工智能工具的可能性高66%(aPR:1.66;95%置信区间:[1.64, 1.69])。

结论

在乌干达的医学生中,ChatGPT和其他人工智能工具的使用很普遍。人工智能工具被用于学术和非学术目的。与年长学生相比,年轻学生更有可能使用人工智能工具。有必要在各院校提高人工智能素养,使年长学生具备数字时代所需的基本技能。此外,教育工作者应假定学生在使用人工智能,并调整教学方式和考试设置以适应这一新现实。我们的研究为现有的呼吁在医学教育中建立人工智能监管框架的声音提供了更多证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50af/11717177/24fa8e18434f/pone.0313776.g001.jpg

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