Caleb M. Trujillo

Assistant Professor of Data Visualization and Data Analytics

Caleb Trujillo

Ph.D. Biological Sciences, Purdue University.
B.A. Molecular, Cellular, and Developmental Biology, University of Colorado at Boulder.

Office: UW2-224
Email: calebtru@uw.edu
Phone: 425.352.3317

Intro

One of my favorite parts of my job is getting lost in data. We live in a data age, which brings up new questions, tools, and concerns for how to manage, share, and understand a rich sea of information. My goal is to help my students and colleagues usher in data-intensive research responsibly. My path to data visualization has been circuitous. I was trained in molecular biology, worked in developmental biology laboratories, and am now researching undergraduate STEM education. I use data visualization to conduct research in science education, empower students to work with data, and provide insights into how students learn.

Teaching

My role as an educator is to prepare students to tackle complex problems, identify critical issues, and collaborate toward creative solutions.
To do this in the classroom, I prioritize sketching models, constructing explanations, and arguing claims with evidence.

I align my lessons with education research to engage students in challenging and rewarding work when I teach.
To help students achieve, I guide them as partners. I use collaborative group work, large projects, frequent assessments, and activities to create a dynamic learning environment with minimal lecturing and support all my students’ success. I frequently partner with community organizations to find messy, overlooked data sets for students to work with.

Recent Courses Taught

BIS 140 Numbers in the News
BDATA 200 Introduction to Data Studies
BIS 232 Introduction to Data Visualization
BES 301 Scientific Methods and Practices
BIS 412 Advanced Data Visualization

Research and Scholarship

My research spans several key areas related to data visualization and STEM education:

Teaching STEM Practices: I research the teaching of scientific practices such as analysis, modeling, and explaining. I investigate activities and assessments that support these practices and their impact on different student groups.

Mechanistic and Systems Thinking: I study mechanistic and systems thinking to understand how people conceptualize the world and how this changes through time. This involves visualizing and testing these frameworks to determine their usefulness to students as they learn.

Mapping Scholarship: Using tools from information sciences, I analyze and synthesize disciplinary scholarship related to STEM education. By creating maps of published scholarship, I visualize relationships between impactful ideas and identify opportunities for future research.

Data Visualization in Education: My work includes using data visualization to conduct research in science education (assessment tools), empower students to work with data (undergraduate research experiences), and provide insights into how students learn (learning research). This involves developing innovative methods for visualizing qualitative and quantitative data.

Interdisciplinary Collaboration: I am co-PI for the NSF-funded MolecularCaseNet, engaging faculty nationwide in interdisciplinary collaborative projects that bridge biology, chemistry, molecular visualization, bioinformatics, and education. This includes developing molecular case studies. I serve as the education researcher to understand how faculty develop their teaching.

Selected Publications

  • Trujillo, C. M., & Long, T. M. (2018). Document co-citation analysis to enhance transdisciplinary research. Science Advances, 4(1), e1701130.
  • Trujillo, C. M., Anderson, T. R., & Pelaez, N. J. (2015). A model of how different biology experts explain molecular and cellular mechanisms. CBE—Life Sciences Education, 14(2), ar20.
  • Nguyen, H.N., Trujillo, C., Wee, K. Bowe, K. (2021). Interactive qualitative data visualization for educational assessment. IAIT2021: The 12th International Conference on Advances in Information Technology; Association for Computing Machinery (ACM) International Conference Proceedings.
  • Trujillo, C. M., Dutta, S. (2024). Molecular storytelling: A conceptual framework for teaching and learning with Molecular Case Studies. Frontiers in Education, 9, 1379515.