Reshaping Engineering Technology Education: Fostering Critical Thinking through Open-Ended Problems in the Era of Generative AI

Meenakshi Narayan; Lokesh Kumar Saharan

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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: July 12, 2024
Conference Session: Panel: AI and Engineering Technology Education: What, Why, How?
Tagged Division: Engineering Technology Division (ETD)
Tagged Topic: Diversity
Permanent URL: https://peer.asee.org/47944

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Paper Authors

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Meenakshi Narayan Miami University

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Dr. Meenakshi Narayan is currently an assistant professor and the department coordinator for robotics engineering technology at Miami University, a position she has held since the fall of 2021. She earned her Ph.D. in Mechanical Engineering from the University of Texas at Dallas in December 2020. Dr. Narayan's doctoral research was centered on the development of robust predictive control models designed to enhance patient safety during robotic interventional procedures. Her research interests encompass a wide range of areas, including dynamics systems and control, teleoperation, haptics, data-driven models, signal processing, and artificial intelligence. She applies her expertise in these domains to address challenges in healthcare and industrial automation. At Miami University, Dr. Narayan instructs courses related to electrical engineering technology and is actively involved in the creation of innovative robotics courses for the Bachelor of Technology in Robotics program. These efforts involve collaboration with industry partners and are backed by support from university endowments and funding from the Ohio Department of Higher Education. Her overarching goal is to modernize and invigorate the engineering technology curriculum to prepare students for the demands of the future workforce, aligning with the evolving needs of the industry.

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Lokesh Kumar Saharan Gannon University orcid.org/0000-0001-9032-4137

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Dr. Lokesh Saharan is currently serving as an Assistant Professor of Mechanical Engineering within the Department of Mechanical Engineering at the College of Engineering and Business at Gannon University. He obtained his Ph.D. from the University of Texas at Dallas in December 2017. Dr. Saharan's research interests encompass various fields, including engineering education, rehabilitation robotics, smart materials, soft robotics, and additive manufacturing. His academic contributions include multiple research articles published in peer-reviewed journals and conferences, as well as a book chapter. In addition to his research work, he has actively participated as a reviewer for various peer-reviewed conferences and journals.
Before joining Gannon University, Dr. Saharan held the position of Assistant Professor and Department Coordinator for Mechanical Engineering at the University of Texas Permian Basin. During this time, he established and managed the Advanced Manufacturing Center, which received substantial funding of $1.1 million from the Odessa Development Corporation. He also served as a co-principal Investigator for a Department of Education EM-Step grant valued at $750,000.
Further enriching his academic journey, Dr. Saharan contributed as an Assistant Teaching Professor at Penn State Behrend during the academic year 2019-20. Here, he played a pivotal role in developing new courses for the biomedical minor within the Mechanical Engineering department. Prior to his tenure in the United States, Dr. Saharan held the position of Assistant Professor (Instruction) in the Mechanical Engineering department at the National Institute of Technology Kurukshetra in India.
Throughout his academic and research career, Dr. Saharan has made significant contributions in both teaching and research roles, spanning multiple countries and institutions.

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Abstract

Academic integrity breaches and plagiarism existed long before the rise of generative artificial intelligence (AI). Students had already turned to paid online tutoring platforms like Chegg and CourseHero to obtain assistance with homework assignments, take-home exams, and course projects. However, the emergence of large language models like ChatGPT offers a novel approach to address these online tutoring services. It provides students with an opportunity to seek legitimate help while reshaping how we construct assignment questions and projects. Consider a real-world scenario where problems often lack the information and consistent methodologies taught in courses, making it insufficient to offer technological solutions. This study focuses on the digital signal processing course within electrical and robotics engineering programs. This course predominantly involves assignments that require coding and can easily be prone to plagiarism through generative AI platforms. For instance, tasks like designing a low-pass filter with specified desired frequency and signal parameters can be tackled using textbook-based methods that generative AI can readily employ to generate solutions. In reality, however, these desired parameters are often unknown, necessitating the application of rigorous system identification techniques to determine the appropriate filter design. The author proposes introducing open-ended problems and projects in these courses. This approach aims to foster critical thinking among students and prepare them for the demands of the industrial and research sectors. This shift in the curriculum can serve as a progressive step in addressing academic integrity issues and revitalizing engineering technology education. In essence, the utilization of generative AI models like ChatGPT can serve as a force for positive change in the educational landscape. It enables students to receive genuine support while pushing educational institutions to adapt by emphasizing critical thinking and problem-solving skills. This transformation represents a significant stride in the ongoing effort to maintain academic integrity and meet the evolving needs of the engineering and technology sectors.

Citation
Format

Narayan, M., & Saharan, L. K. (2024, June), Reshaping Engineering Technology Education: Fostering Critical Thinking through Open-Ended Problems in the Era of Generative AI Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47944

TY - CPAPER
AB - Academic integrity breaches and plagiarism existed long before the rise of generative artificial intelligence (AI). Students had already turned to paid online tutoring platforms like Chegg and CourseHero to obtain assistance with homework assignments, take-home exams, and course projects. However, the emergence of large language models like ChatGPT offers a novel approach to address these online tutoring services. It provides students with an opportunity to seek legitimate help while reshaping how we construct assignment questions and projects. Consider a real-world scenario where problems often lack the information and consistent methodologies taught in courses, making it insufficient to offer technological solutions. This study focuses on the digital signal processing course within electrical and robotics engineering programs. This course predominantly involves assignments that require coding and can easily be prone to plagiarism through generative AI platforms. For instance, tasks like designing a low-pass filter with specified desired frequency and signal parameters can be tackled using textbook-based methods that generative AI can readily employ to generate solutions. In reality, however, these desired parameters are often unknown, necessitating the application of rigorous system identification techniques to determine the appropriate filter design.
The author proposes introducing open-ended problems and projects in these courses. This approach aims to foster critical thinking among students and prepare them for the demands of the industrial and research sectors. This shift in the curriculum can serve as a progressive step in addressing academic integrity issues and revitalizing engineering technology education. In essence, the utilization of generative AI models like ChatGPT can serve as a force for positive change in the educational landscape. It enables students to receive genuine support while pushing educational institutions to adapt by emphasizing critical thinking and problem-solving skills. This transformation represents a significant stride in the ongoing effort to maintain academic integrity and meet the evolving needs of the engineering and technology sectors.

AU - Meenakshi Narayan
AU - Lokesh Kumar Saharan
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Reshaping Engineering Technology Education: Fostering Critical Thinking through Open-Ended Problems in the Era of Generative AI
UR - https://peer.asee.org/47944
ER -