Peer Grading Bias in
Model-Based Systems Engineering Education
Joe Gregory
Dept of Systems and Industrial Engineering
Introduction
Peer grading, whether conducted individually or in groups, plays a crucial role in engineering education.
This TAR project intends to investigate the implementation of peer grading specifically in terms of grading SysML v1 models, as is done in the ‘Model-Based Systems Engineering’ course.
While both individual and group-based peer grading approaches have their merits, it is crucial to understand the potential impact of peer grading bias.
TAR Question
How does individual vs. group peer grading bias affect the assessment of
modeling artifacts in Model-Based Systems Engineering education?
Approach / Methods
What were your desired learning goals and outcomes for participants?
What instructional strategies or activities did you use?
What assessment techniques did you use?
How did you analyze your data?
Results
coming soon!
Discussion / Lessons Learned
coming soon!
About the Author
Dr. Joe Gregory is a postdoctoral research associate at the University of Arizona. His research interests include digital engineering, model-based systems engineering, and semantic web technologies. He is the co-chair of the Digital Engineering Information Exchange (DEIX) Taxonomy Working Group.