Comparative Analysis of Human versus AI-Generated Codes Regarding the Challenges Faced by Students in Innovation Competitions and Programs
- Conference
- Location
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Farmingdale State College, NY, New York
- Publication Date
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October 25, 2024
- Start Date
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October 25, 2024
- End Date
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November 5, 2024
- Conference Session
- Tagged Topics
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Diversity and Professional Papers
- Page Count
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15
- DOI
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10.18260/1-2--49429
- Permanent URL
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https://peer.asee.org/49429
- Download Count
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26
Paper Authors
Abdullah Konak
Pennsylvania State University, Berks Campus
orcid.org/0000-0001-6250-7825
Dr. Abdullah Konak is a Distinguished Professor of Information Sciences and Technology at the Pennsylvania State University, Berks. Dr. Konak also teaches graduate courses in the Master of Science in Cybersecurity Analytics and Operations program at the College of Information Sciences and Technology, Penn State World Campus. Dr. Konak’s primary research interest focuses on modeling, analyzing, and optimizing complex systems using computational intelligence combined with probability, statistics, data sciences, and operations research. His research also involves active learning, entrepreneurship education, and the innovation mindset. Dr. Konak’s published numerous academic papers on a broad range of topics, including network design, system reliability, sustainability, cybersecurity, facilities design, green logistics, production management, and predictive analytics. He has been a principal investigator in sponsored projects from the National Science Foundation, the National Security Agency, the U.S. Department of Labor, and Venture Well.
Sadan Kulturel-Konak
Pennsylvania State University, Berks Campus
orcid.org/0000-0003-4685-4135
Sadan Kulturel‐Konak is a Professor of Management Information Systems and the Director of the Flemming Creativity, Entrepreneurship, and Economic Development (CEED) Center at Penn State Berks. Dr. Kulturel also has a courtesy appointment at Penn State Harold and Inge Marcus Department of Industrial and Manufacturing Engineering. She received her Ph.D. in Industrial and Systems Engineering from Auburn University. Dr. Kulturel’s research focuses on modeling and optimizing complex systems using hybrid approaches combining heuristic methods and exact techniques from probability and operations research. The primary application areas of her research include designing and redesigning facilities to provide significant economic benefits for US firms. Dr. Kulturel is also interested in evidence-based and data-driven pedagogical research regarding entrepreneurship/STEM fields. She served as the elected president of INFORMS-Women in OR/MS (WORMS), the elected chair of INFORMS- Facility Logistics Special Interest Group, and the elected chair of the ASEE Middle Atlantic Section. She is currently an academic member of the College Industry Council on Material Handling Education (CICMHE). She is an Associate Editor of the Engineering Applications of Artificial Intelligence (Elsevier). She has been a principal investigator in several sponsored projects from the National Science Foundation (NSF) and VentureWell. She is a member of INFORMS, IISE, and ASEE.
Abstract
In the dynamic field of educational technology, there is an increasing emphasis on incorporating artificial intelligence (AI) into educational settings. Through interviews with mentors and students, this study compares the effectiveness and reliability of AI-generated qualitative codes with human-generated codes in addressing student challenges during Innovation Competitions and Programs (ICPs), such as hackathons, ide competitions, and pitch competitions. While ICPs encourage creativity and innovation, participants often encounter significant challenges. The methodology involves analyzing qualitative responses to student challenges from students involved in the ICPs. Preliminary findings suggest that AI-generated codes offer improved efficiency and objectivity, while human evaluators provide crucial nuanced insights into student challenges. The results showed a high level of agreement between human and AI-generated overall themes that highlight student challenges during ICPs. However, a low agreement was found in mapping AI-generated codes to transcript files. Based on the identified codes and themes, several recommendations were made to make ICP more inclusive learning events for all students.
Konak, A., & Kulturel-Konak, S. (2024, October), Comparative Analysis of Human versus AI-Generated Codes Regarding the Challenges Faced by Students in Innovation Competitions and Programs Paper presented at 2024 Fall ASEE Mid-Atlantic Section Conference, Farmingdale State College, NY, New York. 10.18260/1-2--49429
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