GIFTS: Integrating Generative AI into First-Year Engineering Education: From Knowledge Acquisition and Arduino Projects to Defining Accessibility Problems and Solutions

Anna Leyf Peirce Starling; Esther Tian

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Conference: 2025 ASEE Annual Conference & Exposition
Location: Montreal, Quebec, Canada
Publication Date: June 22, 2025
Start Date: June 22, 2025
End Date: August 15, 2025
Conference Session: First-Year Programs Division (FPD) GIFTS Session 1: Human-Centered and Project-Based Innovation in First-Year Engineering Design
Tagged Division: First-Year Programs Division (FPD)
Page Count: 9
DOI: 10.18260/1-2--56653
Permanent URL: https://peer.asee.org/56653
Download Count: 7

Paper Authors

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Anna Leyf Peirce Starling University of Virginia orcid.org/0009-0000-8944-0675

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Anna Leyf Peirce Starling (Leyf Starling) is a founding faculty member and current Director of the First Year Engineering Center at the University of Virginia. She is currently developing curriculum and teaching the Foundations of Engineering 1 and 2 courses as well as advising 1st year engineering students.
Starling earned a BS in Mechanical Engineering (UVA ‘03); enhanced that with a MAT in Special Education-General Curriculum (University of North Carolina- Charlotte ‘07); and she has taught math, science, engineering, and robotics for over 20 years in both public and private middle schools, high schools, and universities. Her goal and passion is to make engineering accessible at all levels and across disciplines.
Starling has led professional development trainings on integrating engineering in the K-12 classroom, spent over 10 years consulting for the NSF funded Research Experience for Teachers program at Michigan State University, was editor and contributor to NSF-funded TeachEngineering.org, has presented at ASEE and NIH conferences on promising practices for making engineering accessible, has collaborated closely with the DO-IT Center at the University of Washington, was the founder and director of the Summer Engineering Experience for Students with Visual Impairments and Blindness, and co-founded and co-coached FIRST Robotics Competition Team DARC SIDE.
Currently, her focus is on developing and implementing ways to best support 1st year students and transfer students coming into the field of engineering. She is working to advance the field of engineering education through accessibility while also researching, developing, and integrating practices to support students' growth in teamwork, leadership, communication, and meaningful engagement in the community. Through this effort, she also works to advance ways to integrate emerging technologies as productive tools to support student learning and assessment.

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Esther Tian University of Virginia

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Esther Tian is an Associate Professor of Engineering in the School of Engineering and Applied Science at the University of Virginia. She received her Ph.D. in Mechanical Engineering from the University of Virginia. Her research interests include bio-inspired robotics and engineering design education.

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Abstract

The objective of this Great Ideas for Teaching Students (GIFTS) paper is to present two approaches to employing Generative AI (GenAI) in the engineering design process with first-year engineering students at [REDACTED] school. These activities aim to build understanding of and analytical approaches to using GenAI tools such as Copilot and ChatGPT. This is motivated by the drive to leverage this evolving technology in ways that help students. As this technology evolves, it is increasingly apparent that we need to develop and share more promising practices for faculty and students to navigate various applications and limitations of Gen AI tools. This GIFTS paper will delve into using GenAI as a tool both for acquiring new knowledge and for ideation in two unique settings while scaffolding opportunities for students to grow in their proficiency for using these tools. In each activity, students integrate technical skills with social and ethical thinking as they explore and evaluate how GenAI can enhance or hinder their engineering design process. In order to make this a meaningful and applicable discussion, these topics are woven into two team-based design challenges.

The first activity introduces GenAI as a tool for acquiring knowledge in the research phase of the engineering design process. In this challenge, student teams apply their knowledge and creativity to engineer a parade float that meets certain design requirements and constraints. One of these requirements includes students being able to CAD and 3D print novel parts to enhance the creativity of the float. Additionally, students learn to use the Arduino platform as a basis for their design. During this challenge, students begin by researching basic Arduino components and independently creating simple code, which helps them gain a foundational understanding of programming and electronics. They are not allowed to use a GenAI tool during this part, and they must be able to produce a code to make the part work. Following this, students are introduced to the powerful capabilities of GenAI tools, such as Copilot, to quickly produce code and explanations for Arduino applications. Additionally, students learn the value of developing “good” prompts to produce the most helpful answers. The embedded discussion and reflection questions prompt students to analyze the benefits and drawbacks of using GenAI tools in this challenge in this part of the engineering design process.

During the second activity, students deepen their understanding of how to utilize and evaluate GenAI responses during the problem definition and ideation phases of the engineering design process. Initially, students develop their own problem statements aimed at describing an accessibility issue on campus without the aid of any GenAI tools. After instruction on how to create a sound problem definition and drafting their own statements, students use GenAI to generate alternative statements for comparison. Students critically evaluate the accuracy, logic and efficacy of GenAI-generated statements. They then use GenAI tools for solution ideation to their posed problem by prompting a GenAI tool to write a 5-paragraph solution that meets specific criteria. Students analyze the responses with a rubric designed to promote analytical thinking skills and evaluate the response using various metrics aimed at identifying legitimacy and coherency of arguments. In addition, students further reflect on the various roles GenAI may play in the engineering design process. Here, the focus shifts to problem definition and solution ideation instead of acquiring knowledge. Through this challenge, students build on their understanding of the complexities of employing GenAI tools in the engineering design process as they recognize various applications yield various ethical considerations.

This GIFTS paper will provide further details of practical implementations of these two activities, including a description of the classroom setting, a suggested timeline, how each activity is introduced to the students, and the guiding questions students explore. We will also discuss the merits of the assessment methods used at REDACTED university during this first year course. This approach aims to equip students with the skills to use GenAI thoughtfully and effectively within the engineering design framework, laying the foundation for responsible and informed use of AI in their future careers.

Citation
Format

Starling, A. L. P., & Tian, E. (2025, June), GIFTS: Integrating Generative AI into First-Year Engineering Education: From Knowledge Acquisition and Arduino Projects to Defining Accessibility Problems and Solutions Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . 10.18260/1-2--56653

TY - CPAPER
AB - The objective of this Great Ideas for Teaching Students (GIFTS) paper is to present two approaches to employing Generative AI (GenAI) in the engineering design process with first-year engineering students at [REDACTED] school. These activities aim to build understanding of and analytical approaches to using GenAI tools such as Copilot and ChatGPT. This is motivated by the drive to leverage this evolving technology in ways that help students. As this technology evolves, it is increasingly apparent that we need to develop and share more promising practices for faculty and students to navigate various applications and limitations of Gen AI tools. This GIFTS paper will delve into using GenAI as a tool both for acquiring new knowledge and for ideation in two unique settings while scaffolding opportunities for students to grow in their proficiency for using these tools. In each activity, students integrate technical skills with social and ethical thinking as they explore and evaluate how GenAI can enhance or hinder their engineering design process. In order to make this a meaningful and applicable discussion, these topics are woven into two team-based design challenges.

The first activity introduces GenAI as a tool for acquiring knowledge in the research phase of the engineering design process. In this challenge, student teams apply their knowledge and creativity to engineer a parade float that meets certain design requirements and constraints. One of these requirements includes students being able to CAD and 3D print novel parts to enhance the creativity of the float. Additionally, students learn to use the Arduino platform as a basis for their design. During this challenge, students begin by researching basic Arduino components and independently creating simple code, which helps them gain a foundational understanding of programming and electronics. They are not allowed to use a GenAI tool during this part, and they must be able to produce a code to make the part work. Following this, students are introduced to the powerful capabilities of GenAI tools, such as Copilot, to quickly produce code and explanations for Arduino applications. Additionally, students learn the value of developing “good” prompts to produce the most helpful answers. The embedded discussion and reflection questions prompt students to analyze the benefits and drawbacks of using GenAI tools in this challenge in this part of the engineering design process.

During the second activity, students deepen their understanding of how to utilize and evaluate GenAI responses during the problem definition and ideation phases of the engineering design process. Initially, students develop their own problem statements aimed at describing an accessibility issue on campus without the aid of any GenAI tools. After instruction on how to create a sound problem definition and drafting their own statements, students use GenAI to generate alternative statements for comparison. Students critically evaluate the accuracy, logic and efficacy of GenAI-generated statements. They then use GenAI tools for solution ideation to their posed problem by prompting a GenAI tool to write a 5-paragraph solution that meets specific criteria. Students analyze the responses with a rubric designed to promote analytical thinking skills and evaluate the response using various metrics aimed at identifying legitimacy and coherency of arguments. In addition, students further reflect on the various roles GenAI may play in the engineering design process. Here, the focus shifts to problem definition and solution ideation instead of acquiring knowledge. Through this challenge, students build on their understanding of the complexities of employing GenAI tools in the engineering design process as they recognize various applications yield various ethical considerations.

This GIFTS paper will provide further details of practical implementations of these two activities, including a description of the classroom setting, a suggested timeline, how each activity is introduced to the students, and the guiding questions students explore. We will also discuss the merits of the assessment methods used at REDACTED university during this first year course. This approach aims to equip students with the skills to use GenAI thoughtfully and effectively within the engineering design framework, laying the foundation for responsible and informed use of AI in their future careers.
AU - Anna Leyf Peirce Starling
AU - Esther Tian
CY - Montreal, Quebec, Canada
DA - 2025/06/22
PB - ASEE Conferences
TI - GIFTS: Integrating Generative AI into First-Year Engineering Education: From Knowledge Acquisition and Arduino Projects to Defining Accessibility Problems and Solutions
UR - https://peer.asee.org/56653
DO - 10.18260/1-2--56653
ER -