Unveiling Generative AI in Higher Education: Insights from Engineering Students and Professors
Abstract
The widespread use of Generative Artificial Intelligence (GenAI) tools in higher education, particularly among university students, has raised ethical concerns regarding unintentional plagiarism. Although these tools offer benefits such as time-saving and improved quality, with over 100 available applications, they may inadvertently include borrowed content, posing challenges to academic integrity. Ethical concerns arise within educational institutions, faculty, and integrity committees, complicating evaluations of originality. To address these concerns, universities must establish clear guidelines and educational programs for responsible use of GenAI applications. Educators need to remain current with the latest AI technologies, become proficient in their use, and utilize advanced techniques to teach students how to use them appropriately. This mixed-methods study examines undergraduate engineering students' understanding of GenAI, its usage and ethical implications. The findings demonstrate that ChatGPT is the most popular GenAI application among the students, but also highlight the professors' unfavorable attitudes towards GenAI. The study endeavors to improve understanding of perspectives on GenAI in higher education, facilitating responsible technology integration in classrooms and fostering students' ethical growth. The investigation provides valuable insights for professors, institutions, and research communities engaged in student development and educational advancement. This study also shows a panorama of strategies that could be implemented by teachers to incorporate GenAI in higher education.
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AI-generated content can be factually inaccurate, biased, or otherwise inappropriate.
“In addition, concerns have been raised about the authenticity and reliability of AI-generated context, as tools like Chat -GPT can produce information that is factually inaccurate, biased, or otherwise inappropriate [ 56, 65, 88, 92, 94, 99].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [94]
Institutions have shifted toward alternative assessment methods, such as oral exams (viva voce), real-world reflective tasks, scaffolded assignments, reflective journals, Bloom's Taxonomy higher-order thinking questions, and interactive problem-solving tasks, which require direct student engagement and cannot be easily outsourced to AI.
“To achieve this, institutions have shifted toward alternative assessment methods, such as oral exams (viva voce), real-world reflective tasks, scaffolded assignments, reflective journals, use of Bloom's Taxonomy higher-order thinking questions, and interactive problemsolving tasks, which require direct student engagement and cannot be easily outsourced to AI [ 56, 65, 67, 70, 73, 79, 89, 94, 97-99”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [94]
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The Role of Generative AI in Higher Education
NABHANI, F. A., HAMZAH, M. B., & Abuhassna, H. (2026) · doi:10.1002/9781394486120.ch7
- Authors
- Guillén-Yparrea, N., & Hernández-Rodríguez, F.
- Affiliations
- Tecnológico de Monterrey (MX)
- Venue
- 2024 IEEE Global Engineering Education Conference (EDUCON)
- Publisher
- IEEE
- Published
- 2024-05-08
- Pages
- 1-5
- OpenAlex
- W4400410371
- Cited by
- 43
- References
- 9
- Citations by year
- 2026: 17 · 2025: 23 · 2024: 3
- FWCI
- 16.37
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Global Engineering Education Conference (EDUCON) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, academic integrity, plagiarism, ChatGPT, engineering students, faculty attitudes, AI ethics in education, responsible AI use, AI in the classroom, undergraduate education, student perceptions of AI
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