How to Mitigate the Dependencies of ChatGPT-4o in Engineering Education

Abstract

The rapid evolution of large multimodal models (LMMs) has significantly impacted modern teaching and learning, especially in computer engineering. While LMMs offer extensive opportunities for enhancing learning, they also risk undermining traditional teaching methods and fostering excessive reliance on automated solutions. To counter this, we have developed strategies within curriculum to reduce the dependencies on LMMs that represented by ChatGPT-4o. These include designing course topics that encourage hands-on problem-solving. The proposed strategies were demonstrated through an actual course implementation. Preliminary results show that the methods effectively enhance student engagement and understanding, balancing the benefits of technology with the preservation of traditional learning principles.