ChatGPT in Engineering Education: Survey Data on AI Usage, Learning Impact, and Collaboration

Abstract:

This dataset presents survey responses from first-year engineering students on their use of ChatGPT and other AI tools in a project-based learning environment. Collected as part of a study on AI’s role in engineering education, the data captures key insights into how students utilize ChatGPT for coding assistance, conceptual understanding, and collaborative work. The dataset includes responses on frequency of AI usage, perceived benefits and challenges, ethical concerns, and the impact of AI on learning outcomes and problem-solving skills.

With AI increasingly integrated into education, this dataset provides valuable empirical evidence for researchers, educators, and policymakers interested in AI-assisted learning, STEM education, and academic integrity. It enables further analysis of student perceptions, responsible AI use, and the evolving role of generative AI in higher education.

By making this dataset publicly available, we aim to support future research on AI literacy, pedagogy, and best practices for integrating AI into engineering and science curricula.

.................................................................................................................................................................

Related Publication

This dataset supports the findings presented in the following peer-reviewed article:

ChatGPT in Engineering Education: A Breakthrough or a Challenge?
Davood Khodadad
Published: 7 May 2025 | Physics Education, Volume 60, Number 4
© 2025 The Author(s). Published by IOP Publishing Ltd
Citation: Davood Khodadad 2025 Phys. Educ. 60 045006
DOI: 10.1088/1361-6552/add073

If you use or reference this dataset, please consider citing the above publication.

.....................................................................................................................................................................

Description of the data and file structure

Title: ChatGPT in Engineering Education: Survey Data on AI Usage, Learning Impact, and Collaboration

Description of Data Collection:
This dataset was collected through a survey distributed via the Canvas learning platform following the completion of group projects in an introductory engineering course. The survey aimed to investigate how students engaged with ChatGPT and other AI tools in a project-based learning environment, particularly in relation to coding, report writing, idea generation, and collaboration.

The survey consisted of 15 questions:

• 12 multiple-choice questions to capture quantitative insights on AI usage patterns, frequency, and perceived benefits.
• 3 open-ended questions to collect qualitative perspectives on challenges, ethical concerns, and students' reflections on AI-assisted learning.

Key areas assessed in the survey include:

1. Students’ prior familiarity with AI tools before the course.
2. Frequency and purpose of ChatGPT usage (e.g., coding assistance, conceptual learning, collaboration).
3. Perceived benefits and limitations of using AI tools in an engineering learning environment.
4. Ethical considerations, including concerns about over-reliance and academic integrity.

The dataset provides valuable empirical insights into the evolving role of AI in STEM education and can support further research on AI-assisted learning, responsible AI usage, and best practices for integrating AI tools in engineering education.