Exploring the Adherence to AI-Generated Writing Standards: Practice Levels among University Students

Abstract

Since writing was done with a quill, then with typewriters, and up to modern text processing programs, writing has always adhered to standards concerning the responsibilities and roles of the author, which cannot be abdicated. Given that adherence to writing standards may be a suitable way to regulate the use of generative artificial intelligence, this study explores the extent to which a sample of university students adhere to the standards of AI-generated writing. A total of 326 students majoring in the humanities participated in the study. The research was designed as a quantitative study, employing a descriptive-analytical approach to process the obtained results. A proposed list of standards for AI-generated writing suitable for undergraduate students was prepared and presented to experts. Based on the proposed standards list, data were collected using a graduated practice scale that illustrates the levels of student adherence to AI-generated writing standards. The scaled measure delved into student practices related to standards such as Input Guidance, Disciplined Dependability, Content Validation, Critical Analysis, Documentation, Review and Editing, and Responsibility. Students achieved beginner and intermediate ratings in their adherence to AI-generated writing standards, and they attained very low levels in the advanced practices of standard. This paper contributes to our understanding of how students apply AI-generated writing standards. The gap revealed by the current study's results prompts us to establish regulatory guidelines to enforce student adherence to AI-generated writing standards.