The use of AI large language models by university students for assignment preparation

Using an opportunity where students were explicitly permitted to use artificial intelligence (AI) applications to prepare an assignment, we compared the practices and beliefs of two distinct student cohorts: second-year science students at a large metropolitan university in Australia and students at a partner institution in the People's Republic of China (PRC). Data from an anonymous survey revealed that over 50% of students employed AI tools, primarily for idea generation and initial drafting, instead of using these tools as a source of text they would use in the assignments without editing or attribution. Reasons for use showed differences between native English speakers, their nonnative speaking classmates, and their classmates attending the PRC campus. Across the cohorts, there was a measured engagement with AI tools when preparing assignments. Notably, all cohorts declared a greater willingness to use such tools if institutional licenses were made available. Most students believed that they would use AI in their future professional roles and that their institutions should be providing guidance on the proper use of AI tools. At the Australian campus, sanctioning the use of AI in preparing the class assignment was not associated with any change in the average assignment marks from those gained by a cohort from the previous year where no sanction was in place. At the same time, there was a significant improvement in the average mark for the PRC students, which was associated with the same sanction.<b>NEW & NOTEWORTHY</b> We compared second-year science students at an Australian university and a partner institution in China on their use of AI tools for assignments. Over 50% used AI for idea generation and drafting. Notably, PRC students showed improved grades when AI was permitted, while Australian students saw no change. Most students expressed a willingness to use AI in their future careers and called for institutional guidance on AI use, especially if official licenses were provided.

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Publication Details

Journal
AJP Advances in Physiology Education
Published
2025-03-25
DOI
https://doi.org/10.1152/advan.00181.2024
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
Controls
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article

The use of AI large language models by university students for assignment preparation

David van Reyk, Brian Gregory George Oliver, Hui Chen
3 citations
AJP Advances in Physiology Education
Artificial Intelligence in Healthcare and Education
1.96
article

The use of AI large language models by university students for assignment preparation

David van Reyk, Brian Gregory George Oliver, Hui Chen
article en
3 citations

Abstract

Using an opportunity where students were explicitly permitted to use artificial intelligence (AI) applications to prepare an assignment, we compared the practices and beliefs of two distinct student cohorts: second-year science students at a large metropolitan university in Australia and students at a partner institution in the People's Republic of China (PRC). Data from an anonymous survey revealed that over 50% of students employed AI tools, primarily for idea generation and initial drafting, instead of using these tools as a source of text they would use in the assignments without editing or attribution. Reasons for use showed differences between native English speakers, their nonnative speaking classmates, and their classmates attending the PRC campus. Across the cohorts, there was a measured engagement with AI tools when preparing assignments. Notably, all cohorts declared a greater willingness to use such tools if institutional licenses were made available. Most students believed that they would use AI in their future professional roles and that their institutions should be providing guidance on the proper use of AI tools. At the Australian campus, sanctioning the use of AI in preparing the class assignment was not associated with any change in the average assignment marks from those gained by a cohort from the previous year where no sanction was in place. At the same time, there was a significant improvement in the average mark for the PRC students, which was associated with the same sanction.<b>NEW & NOTEWORTHY</b> We compared second-year science students at an Australian university and a partner institution in China on their use of AI tools for assignments. Over 50% used AI for idea generation and drafting. Notably, PRC students showed improved grades when AI was permitted, while Australian students saw no change. Most students expressed a willingness to use AI in their future careers and called for institutional guidance on AI use, especially if official licenses were provided.

AJP Advances in Physiology EducationVol. 49(2)
University of Technology Sydney (AU), Woolcock Institute of Medical Research (AU), Macquarie University (AU)
Quality Education
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
1.96
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