Personal Teaching Statement
I believe an engineering education should equip students with a practical, adaptable toolkit for solving real-world problems. My teaching approach has been shaped by years of tutoring, formal pedagogy training, and classroom experience, including leading undergraduate thermodynamics and launching the Tekprenticeship program with industry partners like Chevron. I aim to create inclusive, interactive learning environments where students build confidence and strengthen critical thinking through varied content formats, active learning strategies, and open-ended, authentic projects.
I’m committed to continually growing as an educator by using research-based methods, seeking regular feedback from students and colleagues, and staying engaged in professional development. My goal is to not only improve student outcomes but also contribute meaningfully to the advancement of engineering education.
You can see a version of my full teaching statement here.
I conducted preliminary research on the use of emerging AI tools to develop concept inventories aimed at quantitatively evaluating the effectiveness of novel instructional strategies. This work explored the potential of AI-assisted, automatic generation of concept inventories within the context of an undergraduate engineering thermodynamics course.
The core framework of this investigation is outlined to the right. While I continue to view traditional methods, such as Delphi studies coupled with iterative question development, as more robust and reliable, I recognize that LLM-assisted inventories offer a promising means to streamline and accelerate the development process, particularly in early-stages of concept inventory design.