Teaching Portfolio

I deeply value the experiences that I have had teaching both undergraduate and PhD students. My teaching has had a special emphasis on research methods, statistics, and coding in R.

End-of-semester Student Evaluations:

“Sierra is such a kind and charismatic GSI, and she cares so much about her students' success! She made remote learning in a mainly asynchronous class enjoyable and engaging, and she was super helpful and responsive outside of class while answering questions over email. I found her feedback on drafts of paragraphs for each of the papers essential and valuable. Thank you so much, Sierra! Your dedication shines through.”

“She is organized, straight forwards, and adaptive. Open to feedback at any given time which and even encourages it and it makes all the difference in being able to learn. She is a great communicator and extremely knowledgeable. Goes above and beyond in teaching as she shares her insight on the course topics. Always willing to help is easily accessible. Sierra is an exemplary GSI. There is really nothing negative to say about the way she approaches her lessons and teaching style. Really a natural when it comes to teaching.”

“She’s really welcoming , and understanding which makes it easy to approach her or ask questions. Even if you don’t have a question for her, it’s just nice to see her especially with all the stuff that went on this semester. She made a very nice atmosphere that made things more bearable.”

“She was very accessible outside of class, always explained things from lectures during discussion, and had many fun interactive activities. She truly cared about how we were doing in the course.”

Research Methods, Statistics & Coding

  • PSYCH 205 ‧ Spring 2025

    Role: Graduate Student Instructor (GSI)

    Course description: Required course for all Psychology PhD students at Berkeley. Covers fundamental principles of statistical thinking including probability theory, distributions, modeling, parameter fitting, error estimation, statistical significance and cross-validation; as well as all statistical tests that are part of the generalized mixed effect models: n-way analysis of variance (ANOVA), multiple regression, analysis of covariance, logistic regression, between subjects, within subjects, mixed designs and designs with random factors. Introduces students to statistical programming using the computer language R.

    Instructor of record: Arman Catterson

    Institution: University of California, Berkeley

  • Webpage ‧ Summer 2023 & Summer 2024

    Role: Co-Instructor

    Course description: Four-session bootcamp for research assistants and post-baccalaureate students focusing on fundamental data skills in R with an emphasis on good data and coding practices. Sessions are interactive and hands-on, and include live demos, individual work, and group work.

    Institution: University of California, Berkeley

  • Webpage ‧ Fall 2023

    Role: Co-Instructor

    Course description: Semester-long course for first-year PhD and post-baccelaureate students by PhD students. Focuses on fundamental programming skills in R to prepare for research and data analysis in graduate school.

    Institution: University of California, Berkeley

  • PSYCH 101 ‧ Summer 2022

    Role: Graduate Student Instructor (GSI)

    Course description: Concentrates on hypothesis formulation and testing, tests of significance, analysis of variance (one-way analysis), correlation, regression (multiple and logistic), and nonparametric statistics such as chi-square and Mann-Whitney U tests.

    Instructor of record: Amanda Perez

    Institution: University of California, Berkeley

  • PSY 293 ‧ Spring 2015 & Fall 2016

    Role: Distinguished Undergraduate Teaching Fellow

    Course description: Provides an introduction to analyzing, interpreting, and reporting results in psychological research. Prepares students to analyze data. Topics include descriptive and inferential statistics

    Instructor of record: Paul Flaspohler

    Institution: Miami University of Ohio

Psychology

  • PSYCH 134 ‧ Fall 2022

    Role: Graduate Student Instructor (GSI)

    Course description: Students learn about measurement of psychological, behavioral, and biological constructs; incidence and prevalence of psychological and medical disorders; introductions to endocrinology, immunology, and psychophysiology and how these systems are thought to relate psychology to health; as well as introductions to how science is working to understand psychology and health in the laboratory and across the population.

    Instructor of record: Aaron Fisher

    Institution: University of California, Berkeley

  • PSYCH 167AC ‧ Fall 2020

    Role: Graduate Student Instructor (GSI)

    Course description: Upper-level course in Psychology which reviews the major contributions of the literature on prejudice and stereotyping and provides students with a broad understanding of both classic and current issues in the field.

    Instructor of record: Rodolfo Mendoza-Denton

    Institution: University of California, Berkeley

  • PSYCHC162 ‧ Spring 2021

    Role: Graduate Student Instructor (GSI)

    Course description: Upper-level course cross-listed in Psychology and Letters & Science (L&S) which takes an interdisciplinary approach to the understanding of happiness.

    Instructor of record: Dacher Keltner

    Institution: University of California, Berkeley

  • PSYCH 1 ‧ Fall 2023

    Role: Graduate Student Instructor (GSI)

    Course description: Required course for the Psychology major which offers an introduction to the principal areas, problems, and concepts of psychology.

    Instructor of record: Christopher Gade

    Institution: University of California, Berkeley

Invited Lecturer

 

Grad School: Getting in, Surviving & Thriving
University of California, San Francisco
July 2021

Getting into Grad School
University of California, San Francisco
July 2020

Preparing for Research
University of California, San Francisco
July 2019