Predictors of the ethical use of generative artificial intelligence in higher education

A study conducted at the State University of Milagro investigated the ethical use of generative artificial intelligence (AI) in higher education. It aimed to identify factors associated with and structurally contributing to ethical AI use among students, given the challenges posed by AI adoption in areas such as authorship, transparency, content verification, privacy, and student responsibility.

Why it matters

The rapid integration of generative AI into educational environments necessitates understanding its ethical implications to ensure responsible adoption. Identifying factors influencing ethical use is crucial for developing governance frameworks and educational strategies that mitigate risks and foster beneficial AI integration across various sectors and institutions.

Key insights

• Generative AI is increasingly integrated into higher education, introducing both opportunities and ethical challenges.
• Key ethical challenges identified include issues of authorship, transparency in AI use, content verification, data privacy, and student responsibility.
• The study focused on identifying predictors and structural contributors to the ethical use of generative AI among students.
• A quantitative, cross-sectional, correlational, explanatory-predictive, and confirmatory study design was employed.
• The research involved 980 students selected via non-probability purposive sampling.
• Data collection was performed using a 44-item questionnaire.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1942426