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Iris Zhou -Researcher, Mandarin Programs

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"I’m Iris, a third-year student at the University of Washington majoring in Education Studies: Wellness and Social Emotional Learning with a minor in Data Science. I am from China where I spent most of my life learning in a Chinese environment before studying in the United States. As an international student and English language learner, I understand the challenges that multilingual students face when adapting to new languages, cultures, and educational systems. Although I am not directly studying Multilingual Education, I am interested in combining Education Studies and Data Science to better understand the data behind multilingual learning programs. My goal is to use data-informed approaches to help multilingual learners thrive by creating positive, supportive, and effective learning environments and learning strategies. I believe every student brings valuable perspectives and strengths to the classroom, and I am excited to contribute to educational communities that celebrate diversity and support all learners."

Professional Education Experience

Sep-Dec 2025

Seattle Union Gospel Mission, Children and Youth Volunteer

-Facilitated math and reading activities through guided learning resulted in increased confidence in math and
reading skills.
-Organized activities including reading, drawing, and sports
-Maintained a positive and safe environment for children

Mar-Aug 2024

Online English Teaching Program

-Taught basic English to elementary students in Tanzania through online sessions, improving their speaking skills and
building confidence in using English for communication.
-Communicated with students from different backgrounds.
-Applied a variety of teaching strategies to enhance student understanding and cultivate a strong interest in English
learning.

Jan-Mar 2026

Course Project – Data Analysis @ University of Washington, Data Analyst 

-Analyzed global data on paid and unpaid work across different countries to identify cross-national patterns and
highlight disparities in unpaid labor distribution between different genders.
-Applied data analysis techniques to examine trends in unpaid work, uncovering key factors contributing to gender
inequality.
-Analyze the information behind data, such as the impact of unpaid work on people’s mental and physical health

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