Using Artificial Intelligence Case Studies in a Thermodynamics Course

Karen Supan

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: MECH - Technical Session 4: Innovation in Engineering Education Methods
Tagged Division: Mechanical Engineering Division (MECH)
Page Count: 14
DOI: 10.18260/1-2--48227
Permanent URL: https://peer.asee.org/48227
Download Count: 94

Paper Authors

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Karen Supan Norwich University

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Karen Supan is an Associate Professor of Mechanical Engineering and the Director of the David Crawford School of Engineering at Norwich University. She teaches courses in thermodynamics, fluid mechanics, and renewable energy. Dr. Supan has research interests in degradation kinetics of biomass materials, microgrid development for cold regions, and implementation of Artificial Intelligence in Engineering classrooms.

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Abstract

With the explosion of ChatGPT in the past year it seems that Artificial Intelligence is everywhere, but does the modern engineering student know that it can be used for more than writing a paper. The aim of this study was to build an Artificial Intelligence teaching module that could be implemented into existing Mechanical Engineering Curriculum. Rather than teach students how to build neural networks or large language models, the module focused on how Artificial Intelligence is utilized in Nuclear Power Plants. The module was then implemented into a Thermodynamics II course directly following a unit on vapor power plants. Seven case studies from Artificial Intelligence and Nuclear Energy Journals were selected and reviewed for use in the module. A Case Study Implementation Guide was developed by the instructor to assist the students with their navigation of difficult topics, but was also intended for use by other instructors wanting to implement it into a Thermal/Fluids course. To complete the Case Study Review, the students were placed into groups of 3-4 students and each presented with a different case study. To help the students tackle new topics they were given two worksheets to complete with their group: Case Study Worksheet and Independent Research Worksheet. The Case Study Worksheet asked them questions such as “define the problem”, “determine the criteria for a successful solution”, and “what Artificial Intelligence was used in this case study”. The Independent Research Worksheet helped the group identify what they needed to learn about the problem in the case study and develop a plan for acquiring that knowledge. The students were assessed in the following ways: pre- and post-test on content knowledge, group presentation, case study report, concept map, and teamwork assessment. The group presentation was a way to test their knowledge without having them use Artificial Intelligence to write a paper. The purpose of the case study report was to provide the student a way to summarize the process they used to learn about the case. By writing about the experience, they could reflect on their use of problem-solving and critical thinking skills. In the case study report, the students also reflected on how much their perception of Artificial Intelligence changed from the beginning of the module to the end of it. With the feedback from the students, this module will be revised and used as a model for integrating Artificial Intelligence into other Mechanical Engineering courses across the curriculum.

Citation
Format

Supan, K. (2024, June), Using Artificial Intelligence Case Studies in a Thermodynamics Course Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--48227

TY - CPAPER
AB - With the explosion of ChatGPT in the past year it seems that Artificial Intelligence is everywhere, but does the modern engineering student know that it can be used for more than writing a paper. The aim of this study was to build an Artificial Intelligence teaching module that could be implemented into existing Mechanical Engineering Curriculum. Rather than teach students how to build neural networks or large language models, the module focused on how Artificial Intelligence is utilized in Nuclear Power Plants. The module was then implemented into a Thermodynamics II course directly following a unit on vapor power plants. Seven case studies from Artificial Intelligence and Nuclear Energy Journals were selected and reviewed for use in the module. A Case Study Implementation Guide was developed by the instructor to assist the students with their navigation of difficult topics, but was also intended for use by other instructors wanting to implement it into a Thermal/Fluids course. To complete the Case Study Review, the students were placed into groups of 3-4 students and each presented with a different case study. To help the students tackle new topics they were given two worksheets to complete with their group: Case Study Worksheet and Independent Research Worksheet. The Case Study Worksheet asked them questions such as “define the problem”, “determine the criteria for a successful solution”, and “what Artificial Intelligence was used in this case study”. The Independent Research Worksheet helped the group identify what they needed to learn about the problem in the case study and develop a plan for acquiring that knowledge. The students were assessed in the following ways: pre- and post-test on content knowledge, group presentation, case study report, concept map, and teamwork assessment. The group presentation was a way to test their knowledge without having them use Artificial Intelligence to write a paper. The purpose of the case study report was to provide the student a way to summarize the process they used to learn about the case. By writing about the experience, they could reflect on their use of problem-solving and critical thinking skills. In the case study report, the students also reflected on how much their perception of Artificial Intelligence changed from the beginning of the module to the end of it. With the feedback from the students, this module will be revised and used as a model for integrating Artificial Intelligence into other Mechanical Engineering courses across the curriculum.
AU - Karen Supan
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Using Artificial Intelligence Case Studies in a Thermodynamics Course
UR - https://peer.asee.org/48227
DO - 10.18260/1-2--48227
ER -