Quantitative Consulting Services

Quantitative Consultants

Beilei Guo is a doctoral student in Teaching and Curriculum, with research interests in self-determination theory and motivation studies. After earning a master’s degree in TESOL from Durham University in the UK, she published her dissertation, which focuses on utilizing quantitative methods to explore learner autonomy in the English as a Foreign Language classroom. She enjoys helping students in designing surveys, sampling raw materials, visualizing data, selecting models, interpreting results and processing improvement. She has particular expertise in application of a wide variety of statistical techniques including regression, ANOVA, factor analysis, and cluster analysis. She also has experience in non-experimental design, omnibus datasets and meta-analysis.  
Daniela Luengo-Aravena is a PhD student in Educational Policy at the University of Rochester, Warner School of Education. Daniela holds a BA and MA in Economics from the University of Chile. She uses economic theories as a lens to analyze educational policy issues. Currently, she is interested in studying how the composition of a classroom, in terms of gender, ability, and socioeconomic status, impacts individual educational outcomes.   Ting Zhang
Jingwan Tang is currently a doctoral student in Human Development. She earned a master’s degree in Social Research Methods (Durham University) and a bachelor’s degree in Sociology (University of Sci. & Tech. Beijing). These experiences led her to the academic area of social inquiries as well as developed a solid base of methodological knowledge. She is proficient in using SPSS to explore the relationships among interested variables, such as principle component analysis and logistic regression analysis. Also, HLM is another computer program she prefers to use when analyzing longitudinal data. She has an excellent understanding of secondary data analysis and can work with the complex survey data of the national level including cleaning and management. Now, her research interest is primarily around collaborative learning, student identity, group cognition development, and mixed data analysis.   Fangzhi He
Caiqun Xu is a Ph.D. student in Educational Policy at Warner School. She conducts quantitative research on educational and labor outcomes of community college upward transfer students. Caiqun holds a BA and MA in Economics concentrating on Public Finance from Nanjing University of Finance and Economics of China. Prior to joining Warner, she worked as a quantitative research assistant at Center for Public Finance Research at NJUE. Her research interests include the economic returns to higher education, quantitative research methods, and the evaluation of educational policies and interventions.   Weijia Li