校内研究方法项目 Causal Discovery and High-Dimensional Treatment Methods for Evaluating Online Learning Platforms: With Application to Lastinger Center Literacy Matrix Data 支持在线学习环境评估方法研究。
在实验室中，该项目将因果方法与大规模数字学习数据连接起来。应用场景为 Lastinger Center Literacy Matrix 数据，方法重点包括因果发现、高维处理和在线学习平台的可解释评估。
项目信息
- 资助来源： University of Florida HDOSE Strategic Reinvestment Fund
- 角色： 主持人
- Co-PI： Katherine J. Strickland
- 项目周期： 2026 年 7 月 1 日-2027 年 6 月 30 日
- 资助金额： $15,000
项目重点
- 发展和应用用于在线学习平台评估的因果发现方法。
- 研究教育数据中的高维处理方法。
- 以 Lastinger Center Literacy Matrix 数据作为方法发展的应用场景。
相关论文和工作论文
- Li, W., & Strickland, K. J. Designing longitudinal quasi-experimental studies using staggered DID: Estimator selection, software implementation, and sample size planning. Working paper.
- Li, W., Gao, X., Ren, S., & Dong, N. (2026). Heterogeneous treatment effects for impact evaluations. Manuscript under review.
- Strickland, K. J., Hill, J., & Li, W. Estimating heterogeneous treatment effects of the gifted and talented program using Bayesian additive regression trees. Working paper.
相关报告
- Li, W., & Strickland, K. J. (2026). Power analysis for difference-in-differences studies with staggered treatment adoption. Modern Modeling Methods Conference.
- Strickland, K. J., Hill, J., Lu, Y., & Li, W. (2026). Estimating heterogeneous effects of the gifted and talented program using Bayesian additive regression trees. Modern Modeling Methods Conference.
- Li, W., Strickland, K. J., Gao, X., & Huang, J. (2025). Designing longitudinal quasi-experimental studies using staggered difference-in-differences: Estimator selection, software implementation, and sample size planning. SREE Annual Meeting.