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

TL;DR

This paper proposes curriculum strategies to reduce dependency on ChatGPT-4o in engineering education, aiming to balance technological benefits with traditional learning principles, demonstrated through course implementation and preliminary positive results.

Contribution

It introduces novel curriculum strategies specifically designed to mitigate reliance on ChatGPT-4o in engineering education, supported by practical implementation.

Findings

Strategies effectively increased student engagement

Methods improved understanding and reduced dependency

Course implementation demonstrated practical feasibility

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.