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Personalizing Learning: Empowering Students to Use Data to Drive Their Own Learning
Thursday, July 12, 2018 @ 1:00 pm - 2:00 pm EDT
Presented by Jeff Starr, Director of Personalized Learning, Relay Graduate School of Education
Sponsored by Nearpod
Effectively using student data to drive instruction can be a game changer for student learning. A blended learning approach can increase access to actionable data, and help teachers efficiently analyze data to inform planning and teaching that targets students’ evolving needs. Powered by the real time data from a blended approach, a culture of data-driven instruction, naturally leads to an orientation of data-driven learning; where students, empowered by access to their own data, begin to make informed decisions to drive their own achievement.
In this edWebinar, Jeff Starr, Director of Personalized Learning at Relay Graduate School of Education, discusses how to:
- Discover how a blended learning model can be used as a tool to support effective data-driven instruction
- Explore case studies where students use data to direct their own learning
- Learn practical strategies for beginning to engage students with making their own data-driven decisions
All K-12 teachers, librarians, and school and district administrators will benefit from watching this recorded edWebinar.
About the Presenter
Jeff Starr has 20 years of experience as a classroom teacher, a coach, an instructional designer, and a teacher educator. He was an early pioneer of blended learning in the classroom. He co-founded the Aspire Teacher Residency program in CA, and worked as Instructional Designer for Zearn Math, a comprehensive digital elementary math program. Jeff is currently the director of personalized learning at Relay Graduate School of Education where he merges his passions for practice-based teacher education and smart uses of technology, and leads an innovative teaching residency program aimed at developing teachers for new school models. He has an MA in computing and education from Teachers College, Columbia University.
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