TY - GEN
T1 - The Potential of AI in Electrical and Electronic Engineering Education
T2 - 11th IEEE International Conference on E-Learning in Industrial Electronics, ICELIE 2024
AU - Sun, Jiaqin
AU - Kwong, Chiew Foong
AU - Buticchi, Giampaolo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The rapid advancement of Artificial Intelligence (AI) technologies is transforming education, particularly in Electrical and Electronic Engineering (EEE). This paper explores the potential applications, benefits, and challenges of Generative AI (GenAI) and Large Language Models (LLMs) in EEE education. Key areas include personalized learning, intelligent tutoring systems, automated grading, and predictive analytics. While these technologies offer significant enhancements in teaching and learning, they also present challenges such as data privacy, bias, and the need for human interaction. By examining current implementations and providing recommendations, this paper aims to guide educators and researchers in effectively integrating AI to improve EEE education.
AB - The rapid advancement of Artificial Intelligence (AI) technologies is transforming education, particularly in Electrical and Electronic Engineering (EEE). This paper explores the potential applications, benefits, and challenges of Generative AI (GenAI) and Large Language Models (LLMs) in EEE education. Key areas include personalized learning, intelligent tutoring systems, automated grading, and predictive analytics. While these technologies offer significant enhancements in teaching and learning, they also present challenges such as data privacy, bias, and the need for human interaction. By examining current implementations and providing recommendations, this paper aims to guide educators and researchers in effectively integrating AI to improve EEE education.
UR - http://www.scopus.com/inward/record.url?scp=85216723579&partnerID=8YFLogxK
U2 - 10.1109/ICELIE62250.2024.10814858
DO - 10.1109/ICELIE62250.2024.10814858
M3 - Conference contribution
AN - SCOPUS:85216723579
T3 - 2024 IEEE 11th International Conference on E-Learning in Industrial Electronics, ICELIE 2024
BT - 2024 IEEE 11th International Conference on E-Learning in Industrial Electronics, ICELIE 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 November 2024 through 6 November 2024
ER -