Teaching Approach

I have developed and implemented a wide range of educational experiences for diverse purposes, audiences, and settings. Some key features of my teaching approach include:

Careful design. I select and integrate all elements of courses and lessons, including learning goals, content, and assessment tools, in alignment with students’ needs and backgrounds. Evidence-based, transparent teaching methods increase engagement and teaching effectiveness since learners understand why they are learning in a certain way.
Emphasis on value and applicability. My focus is on developing transversal and high-order competencies instead of memorization. I do this by including hands-on activities where students apply knowledge and create and evaluate products. Learners in both short workshops and full courses acquire readily applicable tools, mental models, and resources.
Learning by doing. Oral explanations rarely go beyond 7 to 10 minutes. Most of the time, learners engage in activities such as inquiry-guided exercises using new technologies (e.g., online data set explorers, simulation software), polls and games, think-pair-share exercises, journaling and writing activities, case studies, work galleries and workshops to provide and receive feedback, and many others.
Welcoming, safe environment. Workshop sessions and courses incorporate several strategies to foster a positive, empowering, and respectful environment. For example, I design explanations that demystify anxiety-provoking topics, such as programming languages and statistical concepts, by breaking them down into manageable chunks and providing a road map for success. Learners in my classes learn collaboratively and participate in their learning experience directly (in-class) or anonymously (by voicing their opinion in anonymous one-minute cards at the end of each session). Through these and other techniques, I aim to promote engagement, self-efficacy, and a sense of community.

What learners are saying

“Maria was the best teacher I have had at Duke. She cared so much for each student in the class.”

What learners are saying

“Maria did a great job of relaying a significant amount of detailed information in the short period of time that we had. The class activities and workshops also helped me revise and improve my research proposal at every stage. It was extremely helpful, and I learned a lot!”

What learners are saying

“[I found useful] the balance between demonstration and hands-on work. The explanations and cheatsheets! So many resources at our disposal to work with and everything provided and showed to us can be applied immediately.”

What learners are saying

“A great primer for using R, as well as mistakes that users make when manipulating data in R. The code is golden, as well as the resources that were embedded in the code.”

Most Recent Teaching Experience

2021 Training Program Co-Instructor: “Data Wrangling, Analysis, and Visualization with R” – University of North Carolina at Chapel Hill, Center for Health Equity Research
2021 Invited Workshop Instructor: “Introduction to Social Network Analysis using R” (in Spanish) – R-Ladies Puebla, Mexico
2020 Invited Workshop Instructor: “Introduction to Social Network Analysis using R” – R-Ladies St. Louis, Missouri
2019 – 2020 Mentor/Project Manager for Capstone Projects: Duke’s Master in Interdisciplinary Data Science
2019 Instructor of Record: Methods of Social Research, Duke Sociology
2019&= Lab Lecturer: “Intro to R for Social Network Analysis” and “From Raw Data to Network Objects: Data Cleaning for Social Network Analysis in R” – Duke Network Analysis Center, Social Networks and Health Workshops
2018 Lab Lecturer: “From Raw Data to Network Objects: Data Cleaning for Social Network Analysis in R” – Duke Network Analysis Center, Social Networks and Health Workshops
2018 Guest Lecturer: “Experiments in the Social Sciences” – Methods of Social Research
2018 Guest Lecturer: “Creating Surveys using Qualtrics” – FOCUS seminar on Affect Control Theory

Teaching Certificates & Continuous Development

RStudio Certified Instructor - Tidyverse

RStudio May 2021

Prepares instructors to apply modern evidence-based teaching practices to teach data literacy and skills using R and RStudio. Certified instructors must pass an exam on teaching methods for programming that includes a demonstration lesson. Additionaly, certified instructors must pass a live-coding exam that requires mastery of data importing, wrangling and transformation, visualization, and modeling using R and Rstudio.

Certificate of Accomplishment in Teaching Writing in the Disciplines

Duke University - Thompson Writing Program May 2020

This program prepares instructors to help learners develop their writing skills, a key goal of undergraduate education. The training included modules on teaching the writing process across and within disciplines, crafting effective writing assignments, providing effective feedback, and grading writing. To obtain the certificate, I completed a teaching portfolio with training reflections and samples of writing assignments designed and feedback provided.

Certificate in College Teaching

Duke University - The Graduate School May 2020

Pedagogical training program on best practices in teaching and learning, course design, effective use of instructional technology, and assessing learning outcomes. To obtain this certificate, I completed coursework, acquired teaching experience, participated in peer teaching observation and reflection (from and to other teachers), and produced a teaching portfolio.