Hi, I'm Patti (she/her)
I'm an assistant professor at Michigan State University working in the Computational Education Research Lab (CERL). I teach introductory computational science courses, and I study students' affective experiences using qualitative research methods. Specifically, I'm interested in building ways to support self-efficacy development in introductory computation-integrated courses.
CV

Research
Computational self-efficacy
I'm currently researching how students experience CMSE 201: Introduction to Computational Modeling and Data Analysis. I'm using their perceptions of the course and of their own experiences to characterize self-efficacy in this context. Recent poster presented at ITiCSE '22.
Affective experiences in computation-integrated physics
I helped plan and facilitate the ICSAM workshop for high school physics teachers to integrate computation into their classrooms. As part of this project, I conducted a study on how students in these classrooms experienced the computational activities, and how different affective constructs lent insight into the challenges that students faced with doing computation. Recent poster presented at AERA '22. Paper published in PRPER.
Learning assistants as pedagogical and curricular partners
I conducted a case study on how undergraduate learning assistants (LAs) influenced the pedagogy and curriculum in an introductory physics course. The LAs comprised a community of practice which directed the course in certain ways. I used the students-as-partners framework to show how the expertise of LAs can be infused into a course sustainably. Paper published in PRPER.
Teaching
Computation and Data Science
I taught CMSE 201: Introduction to Computational Modeling and Data Analysis, and STT/CMSE 180: Introduction to Data Science. In both courses, I employed active learning through in-class group work. In 201, students learned Python and created computational solutions to real world problems (like modeling a forest fire, shown). In 180, students learned R and used data sets to explore new statistical ideas.
Physics
I was a teaching assistant for four semesters of PHY 184: Electricity & Magnetism Projects and Practices in Physics. I facilitated in-class group work on complex physics problems, including some GlowScript-based computational activities (like the EM-field from an oscillating charged particle, shown). I also planned and ran pre-class preparation meetings for the undergraduate learning assistants, and wrote weekly individualized feedback for students.
Bailey Scholars Program
I taught in the Liberty Hyde Bailey Scholars Program community as a course convener, meaning co-instructor for Bailey courses (ANR 210, 310, and 410). Students in the program earn a minor in Leadership in Integrated Learning and participate in community activities together. My role as convener involved co-creating curriculum with the students by leading discussions and co-planning classes. I was mentored by Jeno Rivera and Dustin Petty.
Curriculum
Dynamic Energy Transfer Models
In collaboration with Marcus Kubsch, I developed a curricular tool for physics teachers to dynamically visualize the transfer of energy between physical systems. I created example visualizations, a template for teachers to use for customizable demos, and a website to host the DETM. We wrote a paper on the tool, published in The Physics Teacher.
Electricity & Magnetism Projects and Practices in Physics
I helped develop materials for PHY 184, the physics class described in my Teaching section. The team, led by Daryl McPadden and Paul Irving, developed weekly notes and video lectures, pre-/post-class homework sets, weekly in-class projects, and instructor solution guides. I wrote in-class projects, solution guides, and example problems to accompany the weekly notes.