Supported by the Institute of Education Sciences, we are conducting a five-day training on Bayesian Longitudinal Data Modeling in Education Sciences in the summer of 2025, 2026 and 2027 at the University of Virginia, UCLA, and Florida State University, respectively.
The purpose of this training program is to fill the existing gap in advanced Bayesian skills among education researchers, thereby advancing the field and enhancing educational outcomes for the next generation. Through a well-designed training plan, the program will introduce a range of Bayesian methods, including growth mixture models, high-dimensional variable selection, and techniques for handling non-normal and missing data. The training is committed to creating an inclusive and active learning environment that integrates statistics and programming, offering interactive sessions where participants can present their work and receive constructive feedback. The program plans to recruit a cohort of 30 participants each year. It features a 5-day in-person workshop, monthly follow-up meetings, and a platform for trainees to present their research. To ensure the training is closely aligned with the needs of the participants, the contents are fine-tuned based on an initial review of the trainees’ application materials. Overall, this program is designed to significantly boost the capacity of education researchers to effectively analyze longitudinal data using cutting-edge Bayesian methods, fostering a deeper understanding of educational processes and contributing to informed policymaking and practice.
