Measuring AI-giarism: A Validation Study and Dimensional Exploration of the Scale in Turkish
Abstract
The study's scope includes adapting and validating the AI-giarism scale, developed by Chan (2024), into Turkish and conducting analyses to assess its validity and reliability. The study examined the perceptions of 426 university students towards AI-assisted academic misconduct. Exploratory factor analysis (EFA) revealed a three-factor structure for the scale: 'Plagiaristic AI use', 'AI-augmented writing', and ‘No AI reliance', accounting for 59.7% of the total variance. Confirmatory analyses revealed that the three-factor structure provided a good fit to the data, with the scale items loading significantly onto their respective factors. The model fit indices were adequate. Reliability analyses showed that Cronbach's alpha values ranged between .63 and .91, with discrimination between factors achieved. Additionally, no significant difference in AI-giarism level was obtained according to gender. This instrument provides a valid and reliable means of measuring university students' perceptions towards the ethical use of AI in academia. The scale is a valid and reliable assessment tool, particularly for distinguishing students' attitudes towards the unethical, ethical and limited use of AI.
Keywords
Artificial intelligence, GenAI, plagiarism, aigiarism, scale adaptation
Ethical Statement
Ethics and Consent: Ethical approval for this study was obtained from A2025CAL (Hacettepe University, approval date: 6/08/2025 and permission of ethics document's number).
Thanks
The authors would like to thank all participants and collaborators who contributed to this study.
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