- Conference Session
- Engineering Education Methods and Reflections
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
-
Jad El Harake, Vanderbilt University; gina yu, Vanderbilt University; Kaden Jorge Tro; Jonathan Ehrman, Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Tagged Topics
-
Diversity
- Tagged Divisions
-
Student Division (STDT)
perceived growth and development of the student. In the latter case, manualcoding of the responses revealed which specific skills were acquired by the student and identifiedby the mentor but not by the student response, leading to a positive score discrepancy, or theareas which mentors identified as having room for improvement, leading to a negative scorediscrepancy.When considering the thematic content of all responses rather than focusing on those whichpresented with score discrepancies, coding and tallying of responses was complemented with theaid of the LLM ChatGPT (OpenAI, CA, USA). The use of LLMs in content analysis has beenpreviously shown to have good agreement with human results [12], [13]. In this study, ChatGPTwas prompted to identify