The University of Florida Lastinger Center for Learning has numerous forms of digital technology involved in our work to improve teaching, learning, and childcare. We design, develop, and administer online professional development courses for educators in early learning, literacy, and mathematics. The courses include hundreds of hours of video that introduce educators to research-based classroom practices, and they require teachers to demonstrate competency through the completion of performance and knowledge assessments. (e.g., Fairman, et al., 2020). Each year, over 50,000 teachers participate in our online courses. Due to the significant amount of data generated in our professional learning platform (as well as the learning platforms of our partners), we have built the infrastructure for a ‘Data Lagoon’ to make the data usable for educational researchers to explore how these learning technologies influence teaching and learning outcomes. To date, we have amassed over 1 TB of data and over 2 billion records from 8 different sources. Researchers and developers using our data and platforms are engaged in a variety of research projects, including: The development of an artificial intelligence model to lessen the labor involved in providing personalized and timely feedback to teachers participating in our professional development courses (Cavanaugh, et al., 2024) The development of an Large-Language Model (LLM) tutoring agent that supports middle school mathematics students (Song, et al., 2025) A systematic effort is underway to evaluate the impacts of these learning technologies on improving educator pedagogical content knowledge and student learning outcomes. The Center regularly collects data on the impact of the educator coursework in the form of pre- and post-knowledge tests. Effect sizes (Cohen’s d) indicate a large and positive impact on educator knowledge, regularly exceeding 1.0 and even 4.0 across the various areas of professional development coursework (e.g., Frank Porter Graham CDI, 2022). Due to the Lastinger Center’s role as an administrator of large-scale programs, we are in the process of finalizing data sharing agreements to aggregate the data necessary to conduct analyses of the impact of educator professional development programs on student achievement outcomes in literacy and mathematics. We aim to compare the performance of students within the classrooms of teachers who have participated in our coursework to a matched sample of students in the classrooms of teachers who did not participate. Initial findings from these analyses will be shared.

Cavanaugh, C., Humphrey, B., & Pullen, P. (2024). AI-automated assignment scoring to scale a professional development micro-credential program. International Journal on e-Learning, 23(3), 335-345. https://www.learntechlib.org/primary/p/225199/ Fairman, J.C., Smith, D.J., Pullen, P.C., & Lebel, S.J. (2020). The challenge of keeping teacher professional development relevant. Professional Development in Education, 49(2), 197-209. https://doi.org/10.1080/19415257.2020.1827010 Frank Porter Graham Child Development Institute. (2022). 2021-2022 Flamingo Literacy Matrix evaluation report. University of North Carolina-Chapel Hill. https://lastinger.center.ufl.edu/wp-content/uploads/2023/02/2021-22_FLM_Annual-Report-Final_Oct-2022.pdf Song, Y., Kim, J., Liu, Z., Li, C., & Xing, W. (2025). Students’ perceived roles, opportunities, and challenges of a generative AI-powered teachable agent: a case of middle school math class. Journal of Research on Technology in Education. https://doi.org/10.1080/15391523.2024.2447727