Co-sponsored by Education Week (EdWeek.org), this learning and engagement opportunity — co-hosted by the Rollins Center for Language and Literacy and moderated by its Director, Ryan Lee-James, Ph.D. — explored the implications of data demonstrating that fall 2021 classrooms will reflect the challenges of the preceding two years. A significant increase in the proportion of students who have not had a full year of Head Start, pre-K or kindergarten, for whom everyday attendance is not yet routine or habit, is expected. Data experts including Woody Paik of Curriculum Associates, Beth Tarasawa of NWEA and Hedy Chang of Attendance Works reviewed what has been surmised from the research and shared considerations and actions that teachers and schools may take to best support early learners and their families with the transition.
Following the data discussion, Lee-James engaged in conversation with four leading experts and entrepreneurs associated with promising interventions and supports for successful teaching and learning. Reflecting on the words of renowned child psychologist James Comer, “There can be no significant learning without significant relationship,” Renee Boynton-Jarrett, M.D., Sc.D., of Boston Medical Center’s Vital Village Network; Pamela Cantor, M.D., of Turnaround for Children; Deborah Leong, Ph.D., of Tools of the Mind; and Kathy Hirsh-Pasek, Ph.D., of Temple University and the Brookings Institution previewed their innovative and relationships-first strategies to support teachers, school leaders, school districts and, importantly, parents as they face the new reality of early learning this fall. Each of these thought and action leaders will be featured in a unique GLR Learning Tuesdays session in June and July. See below for dates and details about these follow-on sessions coming soon!
Alejandro Gibes de Gac of Springboard Collaborative provided closing comments about the importance of building intentional collaborations between parents and teachers, families and schools to best address the challenges implied by the data.