Investigating the Transformative Impact of Generative AI on Academic Integrity Across Diverse Educational Domains
Ajay Dhruv, Sayantika Saha, Shivani Tyagi, Vijal Jain
Abstract
Academic integrity is essential in educational institutes to ensure equal and fair learning. However, the increasing use of generative artificial intelligence (AI) in education has generated concerns about its integrity. The use of artificial intelligence (AI) to complete assignments, projects, and evaluations has raised concerns about unfair benefits and the legitimacy of the work being submitted. This study highlights the need for rules and systems to protect academic integrity as AI expands in education. This study attempts to evaluate AI-generated solutions at high school, college, and graduate levels based on three important metrics: Fulfillment, Presentation, and Helpfulness. This study implements an experiment using the proposed framework, and the findings show that the used generative AI models exceeds human-like behavior. Through this study, it was observed that there is a risk of bias against those with real efforts.