The focus of school improvement strategies has shifted from reforming whole schools to improving the quality of instruction in individual classrooms.
- Educational data collection
- Educational instrument design
- Respondent incentives
Sheila Heaviside is an experienced director and technical advisor for large-scale education surveys.
She currently directs the first-ever national longitudinal study of middle grade students, which involves surveying more than 4,000 sixth- to eighth-grade students in 50 schools nationwide. For this effort, she leads the recruitment team for cognitive laboratory interviews and focus groups she also oversees the design of a tracking system for student, teacher, parent, and school administrator surveys, as well as observation instruments and administrative records.
Heaviside is the survey director for other notable educational studies, including a study of teacher residency programs for preparing teachers through a process like a medical residency. On this project, she directs teacher sample frame development, surveys, and all data collection efforts. She also directs the survey and data collection components of the evaluation of the Teacher Incentive Fund (TIF), a project for the U.S. Department of Education to examine the effectiveness of TIF grants, program models, and features.
Prior to joining Mathematica, Heaviside held survey and research positions at Westat, Inc., Research Triangle Institute, Moss Survey Research Center, and the U.S. Bureau of the Census. Author of many papers and presentations, Heaviside holds a master’s in sociology from Catholic University of America.
Impact Evaluation of Departmentalized Instruction in Elementary Schools
Study of Feedback for Teachers Based on Classroom Videos
This evaluation is examining whether video-based observations and feedback help novice and early career teachers enhance classroom practices and student achievement.
Study of Teaching Residency Programs
This study looked at characteristics of federally funded Teaching Residency Programs, including applicants and participants, by measuring program length, required coursework, characteristics of mentor teachers, selection criteria for participants, and retention rates.
Feasibility and Conduct of an Implementation and Impact Evaluation to Inform High Quality Data-Driven Instruction (DDI)
Mathematica is conducting an experimental impact evaluation of the effects of data-driven instruction (DDI) on student achievement. This involves the implementation of high quality DDI professional development and estimating its effects on student achievement.