Navigating the Impact of AI in Engineering Education: Enhancing Learning Outcomes and Addressing Ethical and Assessment Challenges

Md Nazmus Sakib; Maurizio Manzo; Rattaya Chowdhury Yalamanchili

Download Paper | Permalink

Conference: 2025 ASEE -GSW Annual Conference
Location: Arlington, TX, Texas
Publication Date: March 9, 2025
Start Date: March 9, 2025
End Date: March 11, 2025
Page Count: 8
DOI: 10.18260/1-2--55069
Permanent URL: https://peer.asee.org/55069
Download Count: 60

Paper Authors

biography

Md Nazmus Sakib University of North Texas

visit author page

Md Nazmus Sakib is a PhD student in the Department of Mechanical and Energy Engineering at the University of North Texas. His research focuses on microlasers in the Photonics and Micro-Device Fabrication Lab. With two years of teaching assistant experience, Sakib is passionate about teaching and is interested in enhancing engineering education and learning experiences.

visit author page

biography

Maurizio Manzo University of North Texas orcid.org/0000-0002-6418-6225

visit author page

Dr. Maurizio Manzo is an Associate Professor in the Department of Mechanical Engineering at the University of North Texas (UNT). He earned his Ph.D. in 2015 from Southern Methodist University in Dallas, Texas, and holds both bachelor's and master's degrees in Aerospace Engineering from Italy. Dr. Manzo's research spans several areas within mechanical engineering, including experimental optics, photonics, sensing, and experimental fluid mechanics. He has authored over 45 peer-reviewed journal papers and conference proceedings, and he holds 3 US patents (1 utility and 2 provisional). Dr. Manzo has been successful in securing over $2.3 million in research funding from prestigious sources such as the National Science Foundation (NSF), the Department of Homeland Security (DHS), and the Texas Department of Transportation (TxDOT), among others.

visit author page

biography

Rattaya Chowdhury Yalamanchili University of North Texas

visit author page

Dr. Yalamanchili is a Clinical Associate Professor in the Department of Mechanical Engineering. He currently teaches courses in Mechanical engineering (Primarily Design and manufacturing) and in Engineering Management (Project Management, Entrepreneurship, Strategic Management, and Systems Engineering). He has over two decades of experience in Industry both at small startups and large corporations. He has a BTech in Chemical Engineering and an MS and PhD in Mechanical Engineering. He has several patents and publications to his credit.

visit author page

Download Paper | Permalink

Abstract

The infusion of artificial intelligence (AI) in engineering education is revolutionizing conventional methodologies. This paper discusses the impacts of these improvements from the students’ and instructors perspective by analyzing the effectiveness of AI tools in enhancing learning outcomes. Through analyzing qualitative data collected from students of different faculties, this study aims to provide an analysis of the strengths and weaknesses of implementing and incorporating AI in learning. However, it has also presented challenges in grading and assessing work fairly and ethically. AI’s growing influence in engineering education is a double-edged sword, revolutionizing methodologies while complicating certain aspects of pedagogy. From the students' perspective, AI tools enhance their learning experience by providing instant feedback, improving language skills, and bolstering problem-solving abilities. Many students now employ AI tools to assist with assignments, increasing engagement and confidence while personalizing their learning journey. Yet, these benefits bring challenges, particularly in evaluating the authenticity of students' independent work and critical thinking skills. It can be difficult to discern the student’s own contributions, especially as some students use AI to refine their own work, while others rely on it to produce entire assignments without further modification. Advanced-level students, more familiar with AI, leverage it in sophisticated ways, underscoring a correlation between academic maturity and AI usage. This nuanced landscape calls for reevaluation of grading methodologies to ensure both fair and accurate assessment. The integration of AI also raises ethical and logistical concerns, such as issues of plagiarism, data privacy, and access equity. Nearly half of students express ethical reservations about AI’s role in academic work, viewing it as potentially dishonest, while others see it as a valuable, ethical tool. Financial barriers posed by subscription fees for advanced AI features create inequities in student access, complicating the fair assessment of student work. Moreover, excessive AI usage could undermine the development of critical thinking and analytical skills, as students may bypass the deeper learning process. Navigating these multifaceted implications of AI requires educators to remain adaptable and refine assessment practices that embrace both innovation and integrity. To address grading challenges, in this work we develop rubrics that focus on process-oriented tasks, encourage reflections on AI use, and foster transparency. This synergy, which bridges student-centered learning with ethical AI integration, enriches the educational experience by aligning theory with practice and promoting responsible technology use. In this work, students' use of AI and their opinions are gathered to understand how AI impacts their learning experience, engagement, and perceptions regarding ethics and academic integrity. This approach provides insights into how AI tools influence students’ development of technical skills, critical thinking, and responsible technology use in engineering education.

Citation
Format

Sakib, M. N., & Manzo, M., & Yalamanchili, R. C. (2025, March), Navigating the Impact of AI in Engineering Education: Enhancing Learning Outcomes and Addressing Ethical and Assessment Challenges Paper presented at 2025 ASEE -GSW Annual Conference, Arlington, TX, Texas. 10.18260/1-2--55069

TY - CPAPER
AB - The infusion of artificial intelligence (AI) in engineering education is revolutionizing conventional methodologies. This paper discusses the impacts of these improvements from the students’ and instructors perspective by analyzing the effectiveness of AI tools in enhancing learning outcomes. Through analyzing qualitative data collected from students of different faculties, this study aims to provide an analysis of the strengths and weaknesses of implementing and incorporating AI in learning. However, it has also presented challenges in grading and assessing work fairly and ethically.
AI’s growing influence in engineering education is a double-edged sword, revolutionizing methodologies while complicating certain aspects of pedagogy. From the students&#39; perspective, AI tools enhance their learning experience by providing instant feedback, improving language skills, and bolstering problem-solving abilities. Many students now employ AI tools to assist with assignments, increasing engagement and confidence while personalizing their learning journey. Yet, these benefits bring challenges, particularly in evaluating the authenticity of students&#39; independent work and critical thinking skills. It can be difficult to discern the student’s own contributions, especially as some students use AI to refine their own work, while others rely on it to produce entire assignments without further modification. Advanced-level students, more familiar with AI, leverage it in sophisticated ways, underscoring a correlation between academic maturity and AI usage. This nuanced landscape calls for reevaluation of grading methodologies to ensure both fair and accurate assessment.
The integration of AI also raises ethical and logistical concerns, such as issues of plagiarism, data privacy, and access equity. Nearly half of students express ethical reservations about AI’s role in academic work, viewing it as potentially dishonest, while others see it as a valuable, ethical tool. Financial barriers posed by subscription fees for advanced AI features create inequities in student access, complicating the fair assessment of student work. Moreover, excessive AI usage could undermine the development of critical thinking and analytical skills, as students may bypass the deeper learning process.
Navigating these multifaceted implications of AI requires educators to remain adaptable and refine assessment practices that embrace both innovation and integrity. To address grading challenges, in this work we develop rubrics that focus on process-oriented tasks, encourage reflections on AI use, and foster transparency. This synergy, which bridges student-centered learning with ethical AI integration, enriches the educational experience by aligning theory with practice and promoting responsible technology use.
In this work, students&#39; use of AI and their opinions are gathered to understand how AI impacts their learning experience, engagement, and perceptions regarding ethics and academic integrity. This approach provides insights into how AI tools influence students’ development of technical skills, critical thinking, and responsible technology use in engineering education.

AU - Md Nazmus Sakib
AU - Maurizio Manzo
AU - Rattaya Chowdhury Yalamanchili
CY - Arlington, TX, Texas
DA - 2025/03/09
PB - ASEE Conferences
TI - Navigating the Impact of AI in Engineering Education: Enhancing Learning Outcomes and Addressing Ethical and Assessment Challenges
UR - https://peer.asee.org/55069
DO - 10.18260/1-2--55069
ER -