About

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 use of VLE by students and teachers. While well-established VLE added thousands of new users, many new platforms are being developed by both researchers and commercial enterprises. School administrators and teachers regularly face the difficult task of choosing between competing VLE to serve their student 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. I have focused on model-based approaches to estimate effects of VLE using propensity score analysis, multilevel modeling, structural equation modeling, and finite mixture modeling. Over the past five years, I have focused application of the evaluation methods I study on identifying the effects of the Math Nation VLE of the Lastinger Center for Learning. This research resulted in publications in Computers & Education, Journal of Experimental Education, Journal of Research in Educational Effectiveness, Investigations in Mathematics Learning, Journal of Computer Assisted Learning, and Structural Equation Modeling. I am the director of the Virtual Learning Lab, which is a research collaboration to investigate ways that personalized learning technologies can improve teaching and learning.

Research Interests

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

Education

• 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

Professional Appointments

• 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

Selected Grants

Selected Publications

• Leite, W. L., Jing, X., Kuang, H., Kim, D., & Huggins-Manley, A. C. (2021). Multilevel mixture modeling with propensity score weights for quasi-experimental evaluation of virtual learning environments. Structural Equation Modeling. https://doi.org/10.1080/10705511.2021.1919895
• Mitten, C., Collier, Z. K., & Leite, W. L. (2021). Online resources for mathematics: Exploring the relationship between teacher use and student performance. Investigations in Mathematics Learning, 1-18. https://doi.org/10.1080/19477503.2021.1906041
• Collier Z. K., Leite, W. L., & Karpyn A. (2021). Neural networks to estimate generalized propensity scores for continuous treatment doses. Evaluation Review. https://doi.org/10.1177/0193841X21992199
• Leite, W. L., Shen, Z., Marcoulides, K. M., Fisk, C., & Harring, J. (2021). Using ant colony optimization for sensitivity analysis in structural equation modeling. Structural Equation Modeling. https://www.tandfonline.com/doi/full/10.1080/10705511.2021.1881786
• Kim, D., Lee, Yongseok, Leite, W. L., & Huggins-Manley, A. C. (2020). Exploring student and teacher usage patterns associated with student attrition in an open educational resource-supported online learning platform. Computers & Education, 156. https://doi.org/10.1016/j.compedu.2020.103961
• Leite, W. L., Cetin-Berber, D. D., Huggins-Manley, A. C., Collier, Z. K., & Beal, C. R. (2019). The relationship between Algebra Nation usage and high‐stakes test performance for struggling students. Journal of Computer Assisted Learning, 35, 569-581. https://doi.org/10.1111/jcal.12360

Selected Links

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