Senior Education Researcher, SRI Education
Jared Boyce, PhD, is a senior education researcher specializing in using continuous quality improvement and improvement science to understand and improve instructional practices, educational leadership, and data use in schools. He has firsthand experience building researcher–practitioner partnerships that empower educators in collecting, interpreting, and acting on their own data through sustainable processes and improvement science. Boyce’s expertise includes Plan-Do-Study-Act (PDSA) rapid cycles of improvement, practical measurement, mixture modeling, analysis of large-scale state and national data sets, and evaluation methods.
Boyce received the 2016 Advanced Studies of National Databases Outstanding Dissertation Award from the American Educational Research Association and the 2016 Emerald/EFMD Outstanding Doctoral Research Award in Education and Leadership Strategy for his research on educational leadership.
Boyce earned his PhD in education leadership from Teachers College, Columbia University, and his BS in symbolic systems, MA in philosophy, and MA in education from Stanford University.
- First2 Network, NSF INCLUDES Alliance supporting rural first-generation STEM college students in West Virginia
- Networked Improvement Community for Students with Disabilities
- Initial Efficacy Study of Data Wise
- Exploring the Relationship Between Continuous Improvement Culture and Afterschool STEM Program Quality
- Postsecondary Teaching with Technology Collaborative
Different levels of leadership for learning: Investigating differences between teachers individually and collectively using multilevel factor analysis of the 2011–2012 Schools and Staffing Survey
Principal turnover: Are there different types of principals who move from or leave their schools? A latent class analysis of the 2007–2008 Schools and Staffing Survey and the 2008–2009 Principal Follow-Up Survey.
The application of multilevel models with latent variables to K-12 educational leadership and policy research: Multilevel factor analysis, growth models and structural equation models.