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Data Science
Data Science
Data science training has a dual role in increasing retention of students in STEM; the training in analytical and critical thinking is crucial for advancing in a broad range of STEM careers, and the data literacy itself opens doors for the emerging and far-reaching field of data science. When I arrived at Florida International University, I independently designed and taught a multi-semester “Introduction to Data Science” workshop series aimed at teaching entry-level coding skills to the undergraduates in Campbell Lab. I continue teaching this content by co-leading the R working group in the EEB department at UCSC, which I have done since fall of 2020.
In this course I teach data management, analysis, and visualization in R using tidvyerse packages such as dplyr and ggplot2. Through hands-on coding and worksheets using a wide range of datasets, my aim is to provide students with the tools and confidence to succeed in a wide range of analytical fields.
All of my course material is publicly available in the linked GitHub repository.
Inclusive Teaching and Learning
Inclusive Teaching and Learning
To me, teaching and mentoring students is a uniquely rewarding and empowering experience. In an effort to make my teaching as effective and inclusive as possible, I recently completed the Pedagogy for Grads in EEB seminar course through UCSC. This course prepares graduate student Teaching Assistants (TAs) with the most effective teaching methods, centered around the concept of active learning.
Active learning is a method of learning where students are engaged by and participate actively in the learning process; this participation greatly boosts learning outcomes and retention of students when compared with traditional lecture-style teaching methods, resulting in a more inclusive and successful learning experience. By utilizing active learning techniques, I aim to make my students' classroom experiences - whether defined by learning data science in R or understanding foundational ecological concepts - as engaging, useful, and inclusive as possible. The active learning approaches I use are guided by the book Small Teaching by James M. Lang, an incredible manual of small, simple changes that can be made to any course.
Different courses that I have taught/TAed include:
Experimental Design and Data Analysis (UCSC, Winter 2023, Winter 2025)
Kelp Forest Ecology Field Quarter (UCSC, Fall 2021, Fall 2023, Fall 2024)
Applied Environmental Time Series Analysis (UCSC, Winter 2024)
Marine Ecology (UCSC, Winter 2021)
Introduction to Data Science using R (Self-designed, Spring 2020 @ FIU, Fall 2020-Present @ UCSC)
Principles of Ecology (Brown U., Spring 2018, Spring 2019)
Evolutionary Biology (Brown U., Fall 2018)
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