Yue Yin for WL School Board
Work in Education
I am a professor in the Department of Educational Psychology at the University of Illinois Chicago. My work involves teaching statistics classes, advising graduate students, and conducting research. I work remotely as I teach in our online Measurement, Evaluation, Statistics, and Assessment program.
Teaching
As a teacher, I love sharing my knowledge and expertise with students, applying educational theories in practice, watching students grow intellectually, and being inspired by them. I believe every student has the potential to learn and brings valuable experiences and perspectives to the classroom. I strive to engage all students in learning so they can reach their full potential.
Courses I Teach or Have Taught
2005-2008
University of Hawaii at Manoa
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Introduction to Educational Research
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Introductory Statistics
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Student Assessment
2008-Present
University of Illinois Chicago
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Advanced Analysis of Variance in Educational Research
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Educational Measurement
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Item Response Theory
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Hierarchical Linear Model
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Multivariate Analysis of Educational Data
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Multiple Regression in Educational Research
Teaching Awards
2022
University of Illinois Chicago
Teaching Excellence Award
2017
University of Illinois Chicago
Teaching Recognition Award
2012
University of Illinois Chicago
Teaching Recognition Award
Research
As a researcher, my work focuses on using assessment to support instruction and learning, particularly in Science, Technology, Engineering, and Mathematics (STEM). My colleagues, students, and I are currently working on several ongoing research projects: Supporting Instructional Decision-Making with Automatic Scoring, Measuring Instructional Practice, Measuring and Improving AI Literacy in K-12 Education, and Measuring and Improving Inclusive Teaching Strategies in Higher Education.
Below are the major funded research projects for which I have served as Principal Investigator (PI) or Co-PI in recent years.
Some Funded Research Projects
2021 ~ Present
Supporting Instructional Decision Making: The Potential of An Automatically Scored Three-dimensional Assessment System--Funded by National Science Foundation (NSF)
We support middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). Machine learning was used to score students' responses to open-ended assessments that integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
2019 ~ Present
Developing Organizational Capacity to Improve K-8 Mathematics Instruction and Learning--Funded by NSF
We provided systematic professional support and development to more than 100 CPS K-8 district administrators, school principals, teacher leaders, and nearly 400 teachers from four Chicago Public School districts so that teachers improved their math instruction and they can further help students improve their mathematical learning.
2017-2024
Improving Chemistry Learning with Connected Chemistry Curriculum--Funded by the Institute of Education
We explored how digital visualization tools can support student learning and teacher practice. Our team served schools by providing technology infused curriculum and instruction to more than 6000 high school students and the corresponding professional development to 29 teachers in Chicago area. Students could explore chemical reactions at both the microscopic and macromolecular levels in an interactive simulation. With the support of the curriculum, simulations, and instruction, students showed statistically significant improvements in their chemistry learning.
2015-2018
Improving Computational Thinking in Physics and Engineering Making Activities--Funded by NSF
Our team consists of researchers, public school teachers, high school students, and educators in informal settings. We developed curriculum activities to improve students' computational thinking, physics learning, and engineering learning in maker activities. We provided professional development to educators in both formal and informal settings and organized summer camps to high school students using our curriculum. All student participants were from Chicago public schools, more than 90% of the participants were in the free/reduced-price lunch program. They significantly improved their computational thinking skills and dispositions, and achievement tests.