Leite, Walter

Category: All Faculty, Artificial Intelligence, Assessment & Evaluation, Big Data, Causal Inference, Data Collection & Analysis, Educational Assessment & Measurement, Educational Data Mining, Emerging Technologies, Equity, Experimental and Quasi-Experimental Design and Analysis, Lastinger Center for Learning, Learning Analytics, Longitudinal Data Analysis, Machine Learning, Mathematical Modeling, Mathematics Education, Multilevel Model, Online Mentoring, Qualitative Research, Quantitative Research, Research / Program Evaluation, Research Design, Scale Development, School of Human Development & Organizational Studies in Education, Statistics / Applied Stats, Teacher Evaluation, Validity, Value-Added Measures of Teacher Evaluation

Professor,
Research and Evaluation Methodology Program,
School of Human Development and Organizational Studies in Education
Educational Psychology

College of Education
University of Florida
2-265I Norman Hall
PO Box 117049
Gainesville, FL 32611
Phone: 352-273-4302
Fax: 352-392-5929
walter.leite@coe.ufl.edu
http://education.ufl.edu/leite/

Research Biography

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.

Degrees

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

Key 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

Grants

Precision Education: The Virtual Learning Lab. U.S. Department of Education, Institute of Education Sciences, 7/1/2016 – 6/30/2022, $8,908,289.

Efficacy of Prime Online: Teacher Professional Development for Inclusive Elementary Mathematics Classrooms. U.S. Department of Education, Institute of Education Sciences, 8/15/2018 – 8/14/2022, $3,276,003.

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