Generative AI in Engineering Education: Insights from Students
Abstract (300 words maximum)
The rapid advancement of artificial intelligence (AI), particularly generative AI, is transforming engineering education and practice. This study explores engineering students' interactions with and attitudes toward generative AI, focusing on perceptions, usage patterns, benefits, challenges, and career impact. A 33-item survey was completed by 79 engineering students, providing insights into AI’s role in academic and professional development. Results indicate that while many students find AI beneficial for learning and creativity, its integration into coursework remains inconsistent. Forty-two percent of students reported that none of their professors assigned projects involving generative AI, while 32 percent had at least one professor who did. This suggests limited formal exposure to AI-driven assignments. Additionally, students primarily leverage generative AI for brainstorming and writing assistance, with text-based tools being the most used. Confidence in AI technology varies, with many students expressing neutral or slight confidence in their abilities. Ethical concerns persist, particularly regarding academic integrity. Students hold diverse opinions on whether AI use constitutes cheating. While some believe using AI tools for coursework is a legitimate aid, others view it as an unfair advantage or a violation of academic policies. Additionally, concerns about AI reliability, data privacy, and ethical considerations are widespread. Despite these challenges, most students believe AI will positively impact their careers, citing its role in enhancing adaptability, technical skills, and digital literacy. Students highlight the importance of structured learning resources, identifying webinars, workshops, and coursework as key aids in AI skill development. Social media has also emerged as an unconventional but influential learning tool. Addressing technical and ethical challenges in AI integration is essential in engineering education. By tailoring AI integration strategies and addressing students' specific needs and concerns, educational institutions can better align AI’s role with students' academic and professional goals, preparing them for a workforce increasingly shaped by artificial intelligence.
Academic department under which the project should be listed
SPCEET - Industrial and Systems Engineering
Primary Investigator (PI) Name
Awatef Ergai
Generative AI in Engineering Education: Insights from Students
The rapid advancement of artificial intelligence (AI), particularly generative AI, is transforming engineering education and practice. This study explores engineering students' interactions with and attitudes toward generative AI, focusing on perceptions, usage patterns, benefits, challenges, and career impact. A 33-item survey was completed by 79 engineering students, providing insights into AI’s role in academic and professional development. Results indicate that while many students find AI beneficial for learning and creativity, its integration into coursework remains inconsistent. Forty-two percent of students reported that none of their professors assigned projects involving generative AI, while 32 percent had at least one professor who did. This suggests limited formal exposure to AI-driven assignments. Additionally, students primarily leverage generative AI for brainstorming and writing assistance, with text-based tools being the most used. Confidence in AI technology varies, with many students expressing neutral or slight confidence in their abilities. Ethical concerns persist, particularly regarding academic integrity. Students hold diverse opinions on whether AI use constitutes cheating. While some believe using AI tools for coursework is a legitimate aid, others view it as an unfair advantage or a violation of academic policies. Additionally, concerns about AI reliability, data privacy, and ethical considerations are widespread. Despite these challenges, most students believe AI will positively impact their careers, citing its role in enhancing adaptability, technical skills, and digital literacy. Students highlight the importance of structured learning resources, identifying webinars, workshops, and coursework as key aids in AI skill development. Social media has also emerged as an unconventional but influential learning tool. Addressing technical and ethical challenges in AI integration is essential in engineering education. By tailoring AI integration strategies and addressing students' specific needs and concerns, educational institutions can better align AI’s role with students' academic and professional goals, preparing them for a workforce increasingly shaped by artificial intelligence.