Skip to main content Skip to navigation

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

Project Overview

The document examines the varied perspectives of engineering educators regarding the role of generative AI, particularly tools like ChatGPT, in higher education. It reveals a spectrum of reactions, with many educators recognizing the transformative potential of generative AI in enhancing teaching and research methodologies. However, significant concerns arise around issues such as academic integrity, the risk of plagiarism, and the reliability of AI-generated content. The findings indicate that educators who actively engage with generative AI—through discussions and integration into their course syllabi—tend to possess a more optimistic outlook and are better equipped to tackle the associated challenges. This engagement not only fosters a more informed approach to utilizing AI tools but also aids in addressing the ethical and practical implications of their use in educational settings. Overall, while generative AI presents promising opportunities for innovation in education, careful consideration and proactive strategies are essential to mitigate potential drawbacks.

Key Applications

Generative AI tools for personalized learning and teaching

Context: Higher education, specifically targeting engineering and computing students, including educators and learners in engineering disciplines.

Implementation: Surveying educators on their use and perspectives towards generative AI tools and developing custom adaptive learning platforms that provide personalized educational materials based on student backgrounds. This includes incorporating discussions about these tools in the classroom.

Outcomes: Increased familiarity and positive perceptions of generative AI, enhanced personalized learning experiences, improved teaching methodologies, heightened student engagement, and improved curriculum design.

Challenges: Concerns about academic integrity, potential for plagiarism, questions regarding the accuracy and reliability of AI-generated content, ensuring the accuracy and relevance of AI-generated material, and addressing potential biases in AI algorithms.

Implementation Barriers

Perception barriers

Educators have mixed feelings about the legitimacy and potential of generative AI, with some viewing it as a threat to academic integrity. There are concerns about plagiarism and the misuse of AI tools by students, impacting the assessment of genuine student work.

Proposed Solutions: Promoting open discussions about generative AI in classrooms, implementing clear policies regarding the use of AI tools in educational settings, and providing institutional support for its ethical use.

Technical barriers

Concerns about the accuracy and reliability of generative AI outputs in educational contexts.

Proposed Solutions: Establishing guidelines and best practices for the use of generative AI to ensure quality and trustworthiness.

Ethical barriers

Worries about plagiarism and the misuse of AI tools by students, impacting the assessment of genuine student work.

Proposed Solutions: Implementing clear policies regarding the use of AI tools in educational settings to safeguard academic integrity.

Project Team

Umama Dewan

Researcher

Ashish Hingle

Researcher

Nora McDonald

Researcher

Aditya Johri

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Umama Dewan, Ashish Hingle, Nora McDonald, Aditya Johri

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18