Student Perceptions of Academic Misconduct in the Age of Generative AI

In the contemporary landscape of academia, the integration of artificial intelligence (AI) has significantly altered the dynamics of academic research and writing. This study delves into the perceptions of academic misconduct among university students in the age of AI. Through a structured online survey, participants will articulate their perspectives on various activities and their classification as academic misconduct, as well as the severity of such transgressions. By probing into students' beliefs and attitudes, the research seeks to uncover potential disparities in the understanding and interpretation of academic misconduct within higher education settings. The advent of AI technologies has revolutionized the academic environment, providing students with unparalleled access to information and writing assistance. However, this paradigm shift has also brought forth heightened concerns surrounding academic integrity, particularly with regards to plagiarism. Moreover, the widespread adoption of grammar-checking tools such as Grammarly adds further layers of complexity, as the outputs sometimes resemble those generated by AI, blurring the lines between original work and automated assistance. Utilizing quantitative research methods, this study employs an online survey platform to collect data on student perceptions of academic misconduct. The insights collected from this investigation aim to contribute to a nuanced understanding of the multifaceted nature of academic integrity in the era of AI. Ultimately, the findings seek to inform educational policies and practices, fostering a cohesive and informed approach to upholding academic standards across diverse higher education institutions.

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Publication Details

Journal
Proceedings of the ALISE Annual Conference
Published
2024-10-16
DOI
https://doi.org/10.21900/j.alise.2024.1753
Citations
1
Primary Topic
Academic integrity and plagiarism
Type
article
Field-Weighted Citation Impact
0.53
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article

Student Perceptions of Academic Misconduct in the Age of Generative AI

Brady Lund, Nishith Reddy Mannuru, Tae Hee Lee, Nikhila Arutla
1 citations
Proceedings of the ALISE Annual Conference
Academic integrity and plagiarism
0.53
article

Student Perceptions of Academic Misconduct in the Age of Generative AI

Brady Lund, Nishith Reddy Mannuru, Tae Hee Lee, Nikhila Arutla
article en
1 citations

Abstract

In the contemporary landscape of academia, the integration of artificial intelligence (AI) has significantly altered the dynamics of academic research and writing. This study delves into the perceptions of academic misconduct among university students in the age of AI. Through a structured online survey, participants will articulate their perspectives on various activities and their classification as academic misconduct, as well as the severity of such transgressions. By probing into students' beliefs and attitudes, the research seeks to uncover potential disparities in the understanding and interpretation of academic misconduct within higher education settings. The advent of AI technologies has revolutionized the academic environment, providing students with unparalleled access to information and writing assistance. However, this paradigm shift has also brought forth heightened concerns surrounding academic integrity, particularly with regards to plagiarism. Moreover, the widespread adoption of grammar-checking tools such as Grammarly adds further layers of complexity, as the outputs sometimes resemble those generated by AI, blurring the lines between original work and automated assistance. Utilizing quantitative research methods, this study employs an online survey platform to collect data on student perceptions of academic misconduct. The insights collected from this investigation aim to contribute to a nuanced understanding of the multifaceted nature of academic integrity in the era of AI. Ultimately, the findings seek to inform educational policies and practices, fostering a cohesive and informed approach to upholding academic standards across diverse higher education institutions.

Proceedings of the ALISE Annual Conference
University of North Texas (US)
Quality Education
Openalex Percentile: Top 26%
Academic integrity and plagiarism
0.53
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Student Perceptions of Academic Misconduct in the Age of Generative AI — Brady Lund, Nishith Reddy Mannuru, et al. · Proceedings of the ALISE Annual Conference (2024) | TGRS Research Map | TGRS