Incorporating AI in Engineering Assignments  as a Reliable Self-Directed Learning Tool: A Pilot Implementation Overview

Gonca Altuger-Genc; Akin Tatoglu

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Conference: 2024 ASEE North East Section
Location: Fairfield, Connecticut
Publication Date: April 19, 2024
Start Date: April 19, 2024
End Date: April 20, 2024
Page Count: 9
DOI: 10.18260/1-2--45769
Permanent URL: https://peer.asee.org/45769
Download Count: 155

Paper Authors

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Gonca Altuger-Genc State University of New York, Farmingdale State College

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Dr. Gonca Altuger-Genc is an Associate Professor at State University of New York - Farmingdale State College in the Mechanical Engineering Technology Department.

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biography

Akin Tatoglu University of Hartford

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Akin Tatoglu is an Associate Professor of Mechanical Engineering at University of Hartford, CT. He currently leads Autonomous Mobile Robotics Research Lab. His research focuses on robotics, mechatronics and visual navigation.

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Abstract

An important characteristic of engineering education is its ability to evolve with the changes through time. Whether the changes are technological advancements, improvements in application methodologies or theoretical developments, engineering faculty, and engineering programs and curriculums update their teaching materials and course offerings to incorporate such changes so they can teach their students the most up-to-date approaches. One of the most recent developments, now slowly becoming a permanent component of daily life, is AI (Artificial Intelligence) and related tools. Students now have access to AI tools such as ChatGPT and, are able to utilize such tools as a part of their learning process in a useful or harmful way. One of the challenges of using an AI tool as part of learning is that students don’t understand why an AI generated answer may not always be reliable, or relevant or accurate. In this study, our approach is to incorporate AI based systems, such as ChatGPT and make it a part of the coursework and learning tool. Our study offers a multi-faceted multi-level approach: Level 1: Students will be given a pre-experience survey, where their familiarity and attitude towards AI based tools will be measured. Level 2: Students will be given an assignment where they will use ChatGPT as a part of their assignment. Level 3: Students will be provided with an evaluation rubric, and they will be asked to review the outcomes of the ChatGPT and evaluate the information on accuracy, relevancy and reliability as merits. Level 4: Students will be asked to re-write or update the assignment outcome they received from ChatGPT to achieve reliable, accurate and relevant outcome. Level 5: Students will be given a post-experience survey, where their familiarity and attitude change towards AI based tools will be measured. Authors will be incorporating this setting into different level engineering and engineering technology courses in two different (one private and one state), higher education institutions. As a part of the study, authors will share the development of the pre and post experience surveys, the pilot assignment that will is incorporated into courses, the evaluation rubric students will use, and preliminary results. This study aims to provide an overview of how a new technology is not something to be worried about or scared of, instead it can be an opportunity to encourage students to practice their critical thinking and decision-making skills, as well as can provide students an opportunity to practice self-directed learning. It is widely known and accepted; the process of learning never stops for engineers. And as engineering educators our goal is always to instill self-directed learning skills in our students, that way, after graduation, after the formal education ends, the learning never ends. And our students can continue to keep up with the changes and advancements in their field, while taking advantage of the new tools that may become available to them.

Citation
Format

Altuger-Genc, G., & Tatoglu, A. (2024, April), Incorporating AI in Engineering Assignments as a Reliable Self-Directed Learning Tool: A Pilot Implementation Overview Paper presented at 2024 ASEE North East Section, Fairfield, Connecticut. 10.18260/1-2--45769

TY - CPAPER
AB - An important characteristic of engineering education is its ability to evolve with the changes through time. Whether the changes are technological advancements, improvements in application methodologies or theoretical developments, engineering faculty, and engineering programs and curriculums update their teaching materials and course offerings to incorporate such changes so they can teach their students the most up-to-date approaches. One of the most recent developments, now slowly becoming a permanent component of daily life, is AI (Artificial Intelligence) and related tools. Students now have access to AI tools such as ChatGPT and, are able to utilize such tools as a part of their learning process in a useful or harmful way. One of the challenges of using an AI tool as part of learning is that students don’t understand why an AI generated answer may not always be reliable, or relevant or accurate.
In this study, our approach is to incorporate AI based systems, such as ChatGPT and make it a part of the coursework and learning tool. Our study offers a multi-faceted multi-level approach: Level 1: Students will be given a pre-experience survey, where their familiarity and attitude towards AI based tools will be measured. Level 2: Students will be given an assignment where they will use ChatGPT as a part of their assignment. Level 3: Students will be provided with an evaluation rubric, and they will be asked to review the outcomes of the ChatGPT and evaluate the information on accuracy, relevancy and reliability as merits. Level 4: Students will be asked to re-write or update the assignment outcome they received from ChatGPT to achieve reliable, accurate and relevant outcome. Level 5: Students will be given a post-experience survey, where their familiarity and attitude change towards AI based tools will be measured.
Authors will be incorporating this setting into different level engineering and engineering technology courses in two different (one private and one state), higher education institutions. As a part of the study, authors will share the development of the pre and post experience surveys, the pilot assignment that will is incorporated into courses, the evaluation rubric students will use, and preliminary results.
This study aims to provide an overview of how a new technology is not something to be worried about or scared of, instead it can be an opportunity to encourage students to practice their critical thinking and decision-making skills, as well as can provide students an opportunity to practice self-directed learning. It is widely known and accepted; the process of learning never stops for engineers. And as engineering educators our goal is always to instill self-directed learning skills in our students, that way, after graduation, after the formal education ends, the learning never ends. And our students can continue to keep up with the changes and advancements in their field, while taking advantage of the new tools that may become available to them.
AU - Gonca Altuger-Genc
AU - Akin Tatoglu
CY - Fairfield, Connecticut
DA - 2024/04/19
PB - ASEE Conferences
TI - Incorporating AI in Engineering Assignments as a Reliable Self-Directed Learning Tool: A Pilot Implementation Overview
UR - https://peer.asee.org/45769
DO - 10.18260/1-2--45769
ER -