Teaching philosophy

As a teacher-scholar, my teaching development has been intertwined with my development as a researcher. In particular, I have learned about the ways in which effective research and teaching do not come from “eureka” moments of intellectual brilliance, but, instead, depend on thoughtful planning and structures that support success from the bottom up. Just as rigorous study design and statistical analysis are necessary to answer a research question, positive early experiences and supportive course structures are necessary for students to enter a discipline and thrive within it. I focus on designing and teaching classes where I can inspire new students to study psychology and scientific computing. In those classes, I implement accessible course policies to sustain student success throughout the semester. Finally, I maintain comprehensive course materials to standardize my pedagogy and share those materials to support my peers’ teaching.

I strive to nurture novice scientists’ critical thinking skills. Intro-level instructors have the privilege and responsibility of serving as the welcome committee for students entering a new academic discipline. Psychology in particular can serve both as a gateway to further scientific study for students curious about human behavior, and as a core college science experience for students fulfilling breadth requirements. I am committed to balancing the needs of these two groups of students through intro psych classes that are rigorous yet accessible. For example, I collaborated with Dr. Caroline Marvin in developing a new team-based introductory psychology course at Columbia University (“The Science of Psychology: Explorations & Applications”) taught for the first time in spring 2021. I helped select readings, develop lesson plans, and draft assignments, paying special attention to craft learning objectives and structure assignments in a way that was simultaneously appropriate for prospective psychology/neuroscience majors and for general-education students. For instance, I helped build units around applied “challenges” that grouped psychological concepts based on real-world significance. One unit combined concepts from perception and infant/child development, which are not commonly grouped together in introductory psychology courses or textbooks, in the context of masked in-person vs. remote learning strategies for COVID safety in schools (see Thieu et al., 2022, Journal of College Science Teaching for a summary and reflection of our work). I then taught the course as instructor of record in summer 2022, further refining the course to take advantage of summer course structure. During the class on perception, groups of students broke down the results and figures from papers on emotion recognition from face vs. body, and during the class on development, groups practiced writing a “grant” to extend findings from rodent research on infant-maternal attachment to humans. During the final class of the unit, groups used evidence from pre-class readings and in-class activities to propose a hypothetical elementary school’s COVID policy, arguing for masked in-person, remote, or hybrid learning. I leveraged the longer summer class meetings to allow students to engage more deeply with the material via the activities, all while I was able to assess their learning by observing their group work. By the end of the course, students reflected positively on the skills they acquired and stated plans to apply course content to their work in other majors.

Going beyond content, I build accessibility into my course policies to sustain student success. For example, psychology students entering quantitative courses may lack experience using scientific computing tools like R to analyze data, but they can build those skills given sufficient support. In this case, an accessible grading structure is one that will scaffold students’ learning by rewarding incremental progress and learning from feedback, without penalizing students for early mistakes. As a curriculum developer and instructor, I have designed assignment submission and grading policies that allow students flexibility in managing their own deadlines, without penalizing students who need more practice but ultimately achieve the same learning objectives. As instructor for Stats II in Psychology at Spelman College in spring 2024, I designed a two-stage system where each weekly problem set was eligible for full-credit revisions, with no late or resubmission penalty, if revised within one week of receiving the initial grade and feedback. I designed this structure to incentivize students to engage with my feedback and improve their work to meet learning objectives, without penalizing students for first-round mistakes. At the same time, the revision structure allowed me to grade more rigorously on the first pass and hold students to higher standards, knowing that they would have the opportunity to respond to my feedback for full credit. Finally, the time-limited nature of the problem set revisions encouraged students to stay on top of their work through the course, while protecting me as the instructor from a buildup of revision submissions at the end of the term. Over half of students completed at least one revision and raised their problem set grade, showing that students indeed made use of the system. In this way, I was able to leverage course logistics to support student learning, especially for a quantitative course where students might bring insecurity about their own abilities into the classroom.

Finally, in order to codify effective teaching practices and make them repeatable across terms and instructors, I create and refine detailed teaching materials that persist and evolve after my involvement with a course. As a lab instructor for the Spelman College Women in STEM six-week intensive program for incoming first-years in summer 2023 and 2024, I developed and taught a project-based data science course. Students first completed a crash course in data cleaning and visualization techniques using R, and then each student conducted an independent data science analysis—designing their own research question, sourcing their own publicly available datasets, identifying and graphing patterns in their data, and presenting their results. I created all lesson plans and course materials natively in R and managed a course workspace in RStudio Cloud for students to complete exercises and conduct their analyses. The course’s R integration made it easy to format course materials for storage and sharing. For example, on my end, I published the syllabus, course schedule, and lecture notes online as a public website using GitHub and Netlify, both for student reference and to share with other instructors and interested parties. On students’ end, they were able to export their summer work and re-publish their projects in their own GitHub coding portfolios, bringing the technical integration full-circle. In this way, I applied my technical expertise not only to support student learning during a single course but also to create a persistent store for course materials on which my peers and I can build in the future.

In summary, I work to make the discipline I love interesting and accessible to students through courses on psychological concepts, statistics, and scientific computing. I design those classes not only to inspire students through content but to set them up for success through supportive course policies. In those courses, I support my own and my peers’ future teaching by creating, maintaining, and documenting teaching materials that save time, keep record of successful teaching strategies, and support future innovation.