# Is AI Changing the Rules of Academic Misconduct? An In-depth Look at Students' Perceptions of 'AI-giarism'

arXiv: https://arxiv.org/abs/2306.03358 · HTML: https://mlsanity.com/paper/2306.03358/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 63 references that are in the map.
- First posted on arXiv 6 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education](https://mlsanity.com/paper/2305.00290/) (2023)
- [A Comprehensive AI Policy Education Framework for University Teaching and Learning](https://mlsanity.com/paper/2305.00280/) (2023)
- [The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?](https://mlsanity.com/paper/2305.02878/) (2023)
- [The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education?](https://mlsanity.com/paper/2305.01185/) (2023)
- [Text-to-Image Generation: Perceptions and Realities](https://mlsanity.com/paper/2303.13530/) (2023)

## Built on by (most cited first, 4 of 4)

- [Approaches to Generative Artificial Intelligence, A Social Justice Perspective](https://mlsanity.com/paper/2309.12331/) (2023)
- [Using Curriculum Theory to Inform Approaches to Generative AI in Schools](https://mlsanity.com/paper/2309.13053/) (2023)
- [Generative AI Usage of University Students: Navigating Between Education and Business](https://mlsanity.com/paper/2602.16307/) (2026)
- [Can AI be a moral victim? The role of moral patiency and ownership perceptions in ethical judgments of using AI-generated content](https://mlsanity.com/paper/2604.26956/) (2026)

## Abstract (arXiv)

This pioneering study explores students' perceptions of AI-giarism, an emergent form of academic dishonesty involving AI and plagiarism, within the higher education context. A survey, undertaken by 393 undergraduate and postgraduate students from a variety of disciplines, investigated their perceptions of diverse AI-giarism scenarios. The findings portray a complex landscape of understanding, with clear disapproval for direct AI content generation, yet more ambivalent attitudes towards subtler uses of AI. The study introduces a novel instrument, as an initial conceptualization of AI-giarism, offering a significant tool for educators and policy-makers. This scale facilitates understanding and discussions around AI-related academic misconduct, aiding in pedagogical design and assessment in an era of AI integration. Moreover, it challenges traditional definitions of academic misconduct, emphasizing the need to adapt in response to evolving AI technology. Despite limitations, such as the rapidly changing nature of AI and the use of convenience sampling, the study provides pivotal insights for academia, policy-making, and the broader integration of AI technology in education.