This publication was completed under the guidance of Dr. Cameron Schmidt in the Dept. of Biology at East Carolina University. As a mathematics undergraduate, I built core NetLogo code for our agent-based models of sperm population dynamics.
When AI is associated with education, it often is a source of fear for academic integrity. This project explores the good that technology can bring to the classroom. We hope to continue evaluating new methods to bring further socioeconomic opportunity to rural communities.
I analyzed data for our survey on perceptions of AI in the classroom, identifying key trends and insights to inform educational practices. Additionally, our team developed and coded a VR training simulation model, creating an immersive experience to enhance learning and skill-building in virtual environments.
Our project, titled “Evaluating the Effectiveness of Virtual Reality and Augmented Reality on Electrical Construction Curriculum in Community Colleges,” will be out for review in Spring 2025. This project was generously funded by the ECU department of computer science and the ECU Student and Engagement Outreach Scholars Academy.
I’d like to extend a huge thank you to community partners at Pamlico Community College for participating in this study under the guidance of mentor Dr. Yilei Huang.
Thank you as well to the Brinkley-Lane Scholars Program and my teammates Kailee Grubbs, Dhwani Hada, Aliah Spencer, and Jamie Gerdts for making this project enjoyable and impactful.
The daily production of millions of male gametes (sperm) relies on the activity of a small spermatogonial stem cell population that produces committed progenitor spermatogonia that differentiate in response to retinoic acid. It is currently unclear how these mammalian spermatogonial fate decisions are regulated; however, they are critical for maintaining tissue homeostasis, as imbalances cause spermatogenesis defects that can lead to human testicular cancer or infertility.
As part of the Geyer lab at ECU's Brody School of Medicine, I participated in research regarding the LDHC gene in mice. During this summer project, I managed data for our mouse colony of over 100 individuals, keeping track of their ages and genotypes. Using polymerase chain reaction (PCR) and gel electrophoresis, I genotyped each mouse and determined which were suitable for our experiments. In particular, we were studying male mice with a knockout of the LDHC gene.
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