How do students perceive and accept generative AI tools in education?

With AI rapidly reshaping education, understanding students' attitudes is crucial for effective implementation. The study utilized a three-stage process to develop and validate the Generative AI Attitude Scale.

Generative artificial intelligence or GenAI, is rapidly transforming educational environments, offering students new ways to learn, collaborate, and create content. However, as these tools are seeing widespread adoption, there is a growing need to assess how students perceive their effectiveness, usability, and ethical implications.

A recent study titled "Development and Validation of Generative Artificial Intelligence Attitude Scale for Students", published in Frontiers in Computer Science (2025), introduces a new measurement tool to assess university students' attitudes toward generative AI. Conducted by researchers from the University of Foggia and Bartin University, the study addresses the growing role of AI-driven technologies in education by creating a validated scale that examines students’ perspectives on AI integration. The researchers aimed to bridge the gap in understanding how students perceive generative AI tools like ChatGPT, focusing on both positive and negative attitudes.

Assessing students' perceptions of generative AI

With AI rapidly reshaping education, understanding students' attitudes is crucial for effective implementation. The study utilized a three-stage process to develop and validate the Generative AI Attitude Scale. Data was gathered from 664 university students across various faculties during the 2022–2023 academic year. Researchers conducted expert evaluations for face and content validity, followed by exploratory factor analysis (EFA) on 400 students and confirmatory factor analysis (CFA) on another 264 participants.

The final version of the scale consisted of 13 items categorized into two key dimensions: positive attitudes and negative attitudes toward generative AI. Positive attitudes covered areas such as learning enhancement, creative empowerment, and technology appreciation. Negative attitudes focused on concerns related to reliance on AI, ethical considerations, and the impact on cognitive skills. The scale demonstrated high reliability, with a Cronbach’s alpha of 0.84 and test-retest reliability of 0.90, confirming its effectiveness in differentiating student perspectives.

Balancing AI’s benefits and risks in education

The findings highlight a dual perspective among students regarding generative AI. Many participants acknowledged the benefits of AI in improving learning efficiency, supporting problem-solving, and fostering creativity. The technology was seen as a valuable educational tool that enhances engagement and provides personalized learning experiences. However, concerns also emerged about AI potentially hindering originality, critical thinking, and academic integrity. Some students feared that excessive reliance on AI could diminish their independent problem-solving abilities and lead to ethical challenges such as plagiarism.

The study underscores the importance of responsible AI integration in education. While generative AI has the potential to transform learning by making it more accessible and efficient, educators must also address students' concerns. Ensuring that AI tools are used ethically and complement human learning rather than replace traditional cognitive skills is essential for sustainable adoption. The Generative AI Attitude Scale serves as a foundational tool for further research, enabling universities and policymakers to assess and refine AI-driven educational strategies.

Future implications for generative AI in education

The study provides valuable insights into AI's role in shaping the future of education. The validated Generative AI Attitude Scale offers a standardized method to measure student perceptions, helping institutions develop informed policies and training programs. By understanding students’ attitudes, educators can fine-tune AI adoption strategies, ensuring that technology enhances learning rather than creating unintended challenges.

The findings emphasize that AI’s success in education depends on balanced integration, where technology supports but does not replace traditional learning methods. Future research could explore long-term trends in AI acceptance among students and the effectiveness of AI-assisted education in improving academic outcomes. This research contributes significantly to the growing conversation on how AI and human intelligence can coexist harmoniously in learning environments.