Accuracy, reliability, and regulatory concerns in the use of AI tools in education and research

AI tools offer significant pedagogical and research benefits such as personalized learning, better student engagement, and support for teachers in classroom management. These tools also help researchers generate ideas, structure content, manage data, and maintain ethical standards. However, using AI raises questions about accuracy, reliability, and legal responsibility. This research explores the legal and practical implications of using AI tools in education and research. This study examines existing laws, regulations, and guidelines that govern AI use and identifies who is accountable for verifying AI-generated information. This paper is structured as a dual-component study. A quantitative empirical survey (n = 201 participants from 25 countries, with highly uneven geographic distribution and a predominantly student composition) was conducted, with most respondents being students engaged in degree programs. A regulatory analysis constitutes the policy-analytical component, examining existing legal frameworks and proposing normative governance recommendations. All findings reflect self-reported perceptions and behaviors. The findings show that nearly half of the participants use AI for part of their research, while one in five are unaware of any policies. This is a critical gap between institutional policy development and practice. The study's principal contribution is interdisciplinary adaptive legal frameworks that encourage innovation. It integrates empirical educational research, comparative legal analysis, and AI governance research within a single analytical framework. The findings further offer a methodologically grounded foundation for institutional policy development at the intersection of these three fields.

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