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超越边界:探索研究生在线科学课程中的生成式人工智能作业

Beyond boundaries: exploring a generative artificial intelligence assignment in graduate, online science courses.

作者信息

Ganjoo Rohini, Rankin James, Lee Benjamin, Schwartz Lisa

机构信息

The George Washington University, Ashburn, Virginia, USA.

出版信息

J Microbiol Biol Educ. 2024 Dec 12;25(3):e0012724. doi: 10.1128/jmbe.00127-24. Epub 2024 Nov 4.

Abstract

Generative artificial intelligence (GAI) offers increased accessibility and personalized learning, though the potential for inaccuracies, biases, and unethical use is concerning. We present a newly developed research paper assignment that required students to utilize GAI. The assignment was implemented within three online, asynchronous graduate courses for medical laboratory sciences. Student learning was assessed using a rubric, which rated students' effective integration and evaluation of GAI-generated content against peer-reviewed research articles, thus demonstrating their critical thinking and synthesis skills, among other metrics. Overall rubric scores were high, suggesting that learning outcomes were met. After field testing, we administered a 16-item survey about GAI utilization, contribution to learning, and ethical concerns. Data ( = 32) were analyzed, and free-response answers were thematically coded. While 93.8% of respondents found the GAI-generated content to be "very good" or "excellent," 28.1% found inaccuracies, and 68.8% "strongly agreed" or "agreed" that GAI should be allowed to be used as a tool to complete academic assignments. Interestingly, however, only 28.1% "strongly agreed" or "agreed" that GAI may be used for assignments if not explicitly authorized by the instructor. Though GAI allowed for more efficient completion of the project and better understanding of the topic, students noted concerns about academic integrity and the lack of citations in GAI responses. The assignment can easily be modified for different learning preferences and course environments. Raising awareness among students and faculty about the ethical use and limitations of GAI is crucial in today's evolving pedagogical landscape.

摘要

生成式人工智能(GAI)提供了更高的可及性和个性化学习,不过其存在不准确、有偏差和不道德使用的可能性令人担忧。我们展示了一项新开发的研究论文作业,该作业要求学生使用GAI。该作业在三门医学检验科学的在线异步研究生课程中实施。使用评分标准评估学生的学习情况,该评分标准根据同行评审的研究文章对学生有效整合和评估GAI生成的内容进行评分,从而展示他们的批判性思维和综合技能等指标。总体评分标准分数很高,表明达到了学习成果。经过实地测试后,我们进行了一项关于GAI使用、对学习的贡献以及伦理问题的16项调查。对数据(n = 32)进行了分析,并对自由回答的答案进行了主题编码。虽然93.8%的受访者认为GAI生成的内容“非常好”或“优秀”,但28.1%的人发现了不准确之处,68.8%的人“强烈同意”或“同意”应允许使用GAI作为完成学术作业的工具。然而,有趣的是,只有28.1%的人“强烈同意”或“同意”如果未经教师明确授权,GAI可用于作业。尽管GAI使项目能够更高效地完成,并且对主题有了更好的理解,但学生们指出了对学术诚信以及GAI回答中缺乏引用的担忧。该作业可以很容易地根据不同的学习偏好和课程环境进行修改。在当今不断发展的教学环境中,提高学生和教师对GAI道德使用和局限性的认识至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8455/11636326/025880d9a591/jmbe.00127-24.f001.jpg

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