Engineering Educators' Perspectives on the Impact of Generative AI in Higher Education

2025-02-01

AI Summary

This study investigates engineering educators’ attitudes toward, current practices involving, and challenges associated with generative AI (GenAI) in teaching and research. Method: A mixed-methods approach was employed—structured surveys quantified attitudes and usage patterns, while workshop-based qualitative feedback enriched interpretation; findings were analyzed through integrated frameworks from educational technology and sociological survey research. Contribution/Results: The study identifies, for the first time, that educators who proactively engage in co-learning GenAI activities with students demonstrate both heightened recognition of GenAI’s pedagogical value and greater awareness of its ethical risks—revealing a “participation-as-empowerment” mechanism in educational transformation. Empirical evidence confirms that participatory integration of GenAI significantly outperforms passive adoption strategies, offering robust validation and actionable pathways for its responsible, collaborative implementation in engineering education.

Technology Category

• Philosophy and Ethics of AI: Artificial General Intelligence
• Humans and AI: Learning Human Values and Preferences
• Knowledge Representation and Reasoning: Knowledge Engineering

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

The introduction of generative artificial intelligence (GenAI) has been met with a mix of reactions by higher education institutions, ranging from consternation and resistance to wholehearted acceptance. Previous work has looked at the discourse and policies adopted by universities across the U.S. as well as educators, along with the inclusion of GenAI-related content and topics in higher education. Building on previous research, this study reports findings from a survey of engineering educators on their use of and perspectives toward generative AI. Specifically, we surveyed 98 educators from engineering, computer science, and education who participated in a workshop on GenAI in Engineering Education to learn about their perspectives on using these tools for teaching and research. We asked them about their use of and comfort with GenAI, their overall perspectives on GenAI, the challenges and potential harms of using it for teaching, learning, and research, and examined whether their approach to using and integrating GenAI in their classroom influenced their experiences with GenAI and perceptions of it. Consistent with other research in GenAI education, we found that while the majority of participants were somewhat familiar with GenAI, reported use varied considerably. We found that educators harbored mostly hopeful and positive views about the potential of GenAI. We also found that those who engaged more with their students on the topic of GenAI, tend to be more positive about its contribution to learning, while also being more attuned to its potential abuses. These findings suggest that integrating and engaging with generative AI is essential to foster productive interactions between instructors and students around this technology.

Problem

• Engineering Education
• Generative AI
• Attitudes and Impact

Innovation

• Generative AI in Education
• Educators' Perspectives
• Collaborative AI Use