Yue Yin

Dr. Yue Yin is an associate professor in the Department of Educational Psychology. Before joining UIC in 2008, Dr. Yin was an Assistant Professor in the Department of Educational Psychology, University of Hawaii at Manoa. She obtained her PhD in Science Education and MA in Psychology at Stanford University. She also obtained her MA in Education and B.S. in Chemistry at Peking University.

Dr. Yin is particularly interested in classroom assessment and applied measurement. She has conducted research on performance assessment, concept mapping assessment, formative assessment and feedback, learning progression aligned formative assessments, technology-enhanced formative assessments, and assessments diagnosing misconceptions, and assessment improving and measuring computational thinking in makerspace. She also advanced the use of statistical methods in assessment research, for example, utilizing generalizability theory in studying concept mapping assessments, utilizing a rule-space model to analyze students' responses in statistical tests. The subject contents in her research have involved physics, chemistry, biology, mathematics, and statistics, ranging from K-12 to higher education. In her research, she used learning theory as a foundation, measurement and statistics as tools, to explore and examine ways of using assessments to improve students' learning. Her work has been published on journals such as Journal of Research in Science Teaching, Educational Assessment, Applied Measurement in Education, International Journal of Science Education, Journal of Research on Technology in Education, Psychological Methods, and Studies in Educational Evaluation. In addition to being a senior personnel and evaluator on multiple NSF projects, she has been co-PI on two funding awards from National Science Foundation to study the effective use of feedback in STEM classrooms, assessing computational thinking in makerspace, and one funding awards from Institute of Education Sciences to study the effectiveness of connected chemistry curriculum.

Yin has taught educational assessment, research methodology, educational measurement, and various statistics courses. Currently, she teaches Regression, ANOVA, Multivariate Analysis, Hierarchical Linear Modeling, and Educational Measurement. She has received two teaching recognition awards at UIC.

Yin, Y., Olson, J., Slovin, H., Olson, M., & Brandon, P. (2015). Comparing two versions of professional development for teachers using formative assessment in networked mathematics classrooms. Journal of Research on Technology in Education, 47(1), 41-70.

Yin, Y., Tomita, M. K., & Shavelson, R. J. (2014). Using formal embedded formative assessment aligned with learning progressions to promote conceptual change in science. International Journal of Science Education, 36(4), 531-552

Briggs, D. C., Ruiz-Primo, M. A., Furtak, E. M., Shepard, L. A., & Yin, Y. (2012). Meta-analytic methodology and inferences about the efficacy of formative assessment. Educational Measurement: Issues and Practice, 31(4), 13-17.

Pan, T., & Yin, Y. (2012). The relationship between mean square differences and standard error of measurement: Comment on Barchard (2012). Psychological Methods, 17(2), 309-311.

2005 - PhD, Stanford University, Science Education and Assessment
2003 - MA, Stanford University, Psychology
2000 - MA, Peking University, Education
1997 - BS, Peking University, Applied Chemistry

Yin is particularly interested in classroom assessment and applied measurement. She has conducted research on performance assessment, concept mapping assessment, formative assessment, concept inventory development and validation, and computational thinking assessment. The subject contents in her research have involved physics, chemistry, biology, mathematics, and statistics, ranging from K-12 to higher education. In her research, she used learning theory as a foundation, measurement and statistics as tools, to explore and examine ways of using assessments to improve students' learning.

Her teaching interests include measurement and applied statistics. At UIC she regularly teaches Analysis of Variance, Regression Analysis, Multivariate Analysis, and Educational Measurement.