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Undergraduate Students' Perspectives on Generative AI Ethics in Education

Strategic Insights

— 1 min read

Researchers at Texas Tech University conducted a study to investigate undergraduate students' agreement levels on five AI ethics principles in a classroom setting. The study used a mixed-method approach, involving 110 undergraduate students, to explore their perspectives on artificial intelligence (AI) ethics. The findings showed that students agreed most with the principle of "autonomy" and least with "justice." The study also identified 14 themes that explained the students' rationales for their choices.

Key Takeaways:

  • The study highlighted the importance of considering students' diversity and public interests when integrating AI ethics into the classroom.
  • The researchers found that gender and grade level could predict students' agreement levels on AI ethics principles.
  • The study's results can inform instructors to develop specific guidelines and facilitate attitudinal changes in applying AI ethics instructions.
  • The study emphasized the need to highlight public interests and consider students' diversity in the application of AI ethics.
  • The researchers identified 14 themes that explained students' rationales, including concerns about AI's impact on society and its limitations.
  • The study's findings can be applied to develop more effective AI ethics training programs for instructors and students.

Statistics:

  • 110 undergraduate students participated in the study (Texas Tech University, 2025)
  • Students agreed most with the principle of "autonomy" (Texas Tech University, 2025)
  • Students agreed least with the principle of "justice" (Texas Tech University, 2025)
  • 14 themes were identified to explain students' rationales (Texas Tech University, 2025)

Sources:

  • Texas Tech University. (2025). Undergraduate students' perspectives of generative AI ethics. International Journal of Educational Technology in Higher Education, 22(1), 1-22.
  • Yang, T., Cheon, J., Cho, M.-H., Huang, M., & Cusson, N. (2025). Undergraduate students' perspectives of generative AI ethics. International Journal of Educational Technology in Higher Education, 22(1), 1-22.
  • SpringerOpen. (n.d.). International Journal of Educational Technology in Higher Education. Retrieved from http://educationaltechnologyjournal.springeropen.com/

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