Walter Leite 

My current research program focuses on methods to evaluate the effects of student and teacher use of virtual learning environments (VLE). This area has strong current relevance given the tremendous expansion of the use of VLE by students and teachers. While well-established VLEs have hundreds of thousands of users, many new platforms are being developed by both researchers and commercial enterprises. School administrators and teachers regularly face the difficulty of choosing between competing VLEs to serve their students' needs, with scarce evidence of effectiveness for some of them. The methods I investigate estimate different types of causal effects of VLE, such as the average treatment effect (ATE), average treatment effect on the treated (ATT), and complier average causal effects (CACE), as well as treatment effect heterogeneity. These effects give a comprehensive view of the effectiveness of each VLE. My work in the Virtual Learning Lab focuses on causal inference using machine learning and log data from VLEs and intelligent tutoring systems. I have published extensively on model-based approaches to estimate the effects of VLEs on student achievement using propensity score analysis, multilevel modeling, structural equation modeling, and finite mixture modeling. My book Practical Propensity Score Methods Using R disseminates methodology to implement propensity score matching, weighting, and stratification for cross-sectional, longitudinal, and multilevel data. I have also created the podcast series Fairness and Equity in AI for Education which is available in all major podcasting platforms. I teach Structural Equation Modeling, Machine Learning for Causal Inference, Quasi-Experimental Design and Analysis in Education, and Survey Design and Analysis in Education. I am passionate about openness and reproducibility in research. Code for my projects is available in Open Science Framework. I have authored two R packages: SEMsens implements sensitivity analysis methods for structural equation modeling, and ShortForm selects items for short forms of psychometric scales optimizing on criteria selected by the researcher. I currently serve on the editorial boards of the journals Structural Equation Modeling, Multivariate Behavioral Research, and the Journal of Experimental Education. I have collaborated extensively with the Lastinger Center for Learning of the University of Florida on evaluations of educational products used by hundreds of thousands of students annually in Florida.

Assessment and Evaluation, Causal Inference, Data Collection and Analysis, Educational Assessment and Measurement, Emerging Technologies, Experimental and Quasi-Experimental Design and Analysis, Longitudinal Data Analysis, Mathematical Modeling, Mathematics Education, Multilevel Model, Online Mentoring, Qualitative Research, Quantitative Research, Research / Program Evaluation, Research Design, Statistics / Applied Stats, Teacher Evaluation, Value-Added Measures of Teacher Evaluation

• Ph.D. - Department of Educational Psychology, The University of Texas at Austin, 2005, Quantitative Methods
• M.A. - The University of Texas at Austin, 2003, Program Evaluation
• B.A. - Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil, 2000

• Professor, School of Human Development and Organizational Studies in Education, University of Florida, 2017-Present
• Associate Professor, Department of Educational Psychology, University of Florida, 2011-2017
• Assistant Professor, Department of Educational Psychology, University of Florida, 2005-2011

• http://education.ufl.edu/leite/
• http://virtuallearninglab.org/
• http://www.practicalpropensityscore.com