Date of Graduation


Document Type


Degree Name

Bachelor of Science in Biomedical Engineering

Degree Level



Biomedical Engineering


Elsaadany, Mostafa


In the field of biomedical engineering, needs identification and solution development are an important element of the design process. In our undergraduate curriculum, a course was designed to allow clinical observation and provide an opportunity for students to learn about engineering design and engage with clinicians via completing rotations in medical facilities near our campus. While this type of course is not unique, evaluating its efficacy is not simple. Given the broad range of institutional resources available- such as proximity to a medical school, or residency programs- reporting the quality of such courses within the context of such available resources is of broad interest to the engineering community. This study sought to measure the effectiveness of a junior-level clinical observations course designed for a major land-grant, public university without proximity to a medical school. In addition to evaluating the course as a whole, the study also sought to compare the experiences of historically marginalized groups to non-historically marginalized groups. We compared IP generation and pre- and post-class surveys were used to quantify students’ self-efficacy, motivations, and ability to make connections to real-world problems. The course was first evaluated as a whole. The data was then separated into different demographic groups to highlight any discrepancies within these student experiences. The total number of IP applications increased more than two-fold following the adoption of the course, and survey results indicated students’ collective improving understanding of the design process and increased confidence in engineering-related skills. When separated into demographic groups, data analysis revealed that historically marginalized groups are entering the course at a disadvantaged place. This study included a sample size of 75 undergraduate students. NVivo, a qualitative data analysis software, was used to analyze the open-response survey questions. NVivo requires an input of qualitative data that can be coded to produce a quantitative response, decreasing the chance of cherry-picking and researcher bias in data analysis. Such software allowed for the manual and automatic coding of themes identifiable in the data. Sentiment analysis was performed to analyze the frequency and tone of word usage. Ongoing work will continue to examine the long-term impacts of the course concerning the above metrics as well as student retention and graduate placement.


service-learning, real-world application, practical skills, clinical immersion