Structured Abstract
Setting
Four stable Head Start programs in the Boston, Massachusetts area that share a strong commitment to improving outcomes for young children have been selected to participate in this project.
Sample
All programs have student populations that are almost entirely (90-100 percent) low income and heavily (22-50 percent) English language learners (ELLs).
Intervention
The FLS program has two main components that will be given over a 6-month period: (a) 8 face-to-face instructional sessions that build teachers' pedagogical content knowledge in the physical and life sciences, and (b) one 1/2-hour mentoring sessions that will support teachers as they master science content and inquiry-based methods. The mentoring will include coaching, reflective documentation (videotaping teacher instruction), and collaborative inquiry (teacher study groups).
Research design and methods
The sample will consist of 1 cohort of 72 Head Start teachers. The teachers will be randomly assigned to intervention and control groups. Child data will also be collected on the preschool children in the classes of 42 of the teachers. Approximately 420 students will participate in the study stratified by whether or not they are ELLs and distributed between the intervention and control groups. The study will use a pre-post experimental design. Fidelity of implementation will be monitored. In-depth case studies of teachers and ELL students in five classrooms will be conducted in phase 2 to examine the effects of the intervention on student engagement and classroom participation. Classroom observations and teacher interviews will be included.
Control condition
The control group will get whatever professional development they would normally receive.
Key measures
Child and classroom data will be collected using a set of rigorous standardized measures. Because there are no existing assessments of science teaching and learning at the preschool level, the study will develop direct assessments for this purpose.
Data analytic strategy
Linear regression, hierarchical linear modeling (HLM), and qualitative measures will be employed.
People and institutions involved
IES program contact(s)
Products and publications
ERIC Citations: Find available citations in ERIC for this award here.
** This project was submitted to and funded under Teacher Quality: Mathematics and Science Education in FY 2005.
Related projects
Supplemental information
Co-Principal Investigator(s): Gropen, Jess
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
