Nathan Burroughs
Dr. Burroughs has a strong background in quantitative research, with extensive experience in statistics, research design, survey development, data collection, and data management. He also has strong communication skills, having produced reports aimed at a wide variety of audiences. Dr. Burroughs’ research is focused on mechanisms for alleviating social inequality. A major theme in his work is how public policies and institutions mediate background inequalities, with an emphasis on the role of teacher quality and curricular differentiation in STEM. He has employed a wide variety of methodological techniques to study these questions (e.g., multi-level modeling, randomized controlled trials, survey research, etc.), using both original data collection and large-scale secondary data sets. Dr. Burroughs routinely draws on methods and perspectives from a number of fields (education, policy evaluation, political science, history, economics, sociology, and analytic philosophy), with peer-reviewed publications in multiple academic fields. Prior to his work at PPA, Dr. Burroughs was part of educational research and evaluation centers affiliated with Indiana University and Michigan State University, where he participated in study design, data collection, project management, analysis, and reporting. He has also worked as a communications consultant and provided technical assistance as part of school reform efforts. Dr. Burroughs brings a synthetic approach to research and decades of experience working with stakeholders from diverse backgrounds. His approach combines the most rigorous feasible methods with a strong commitment to equity and collaboration.Dr. Burroughs has a strong background in quantitative research, with extensive experience in statistics, research design, survey development, data collection, and data management. He also has strong communication skills, having produced reports aimed at a wide variety of audiences. Dr. Burroughs’ research is focused on mechanisms for alleviating social inequality. A major theme in his work is how public policies and institutions mediate background inequalities, with an emphasis on the role of teacher quality and curricular differentiation in STEM. He has employed a wide variety of methodological techniques to study these questions (e.g., multi-level modeling, randomized controlled trials, survey research, etc.), using both original data collection and large-scale secondary data sets. Dr. Burroughs routinely draws on methods and perspectives from a number of fields (education, policy evaluation, political science, history, economics, sociology, and analytic philosophy), with peer-reviewed publications in multiple academic fields. Prior to his work at PPA, Dr. Burroughs was part of educational research and evaluation centers affiliated with Indiana University and Michigan State University, where he participated in study design, data collection, project management, analysis, and reporting. He has also worked as a communications consultant and provided technical assistance as part of school reform efforts. Dr. Burroughs brings a synthetic approach to research and decades of experience working with stakeholders from diverse backgrounds. His approach combines the most rigorous feasible methods with a strong commitment to equity and collaboration.
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About Nathan Burroughs
Dr. Burroughs has a strong background in quantitative research, with extensive experience in statistics, research design, survey development, data collection, and data management. He also has strong communication skills, having produced reports aimed at a wide variety of audiences. Dr. Burroughs’ research is focused on mechanisms for alleviating social inequality. A major theme in his work is how public policies and institutions mediate background inequalities, with an emphasis on the role of teacher quality and curricular differentiation in STEM. He has employed a wide variety of methodological techniques to study these questions (e.g., multi-level modeling, randomized controlled trials, survey research, etc.), using both original data collection and large-scale secondary data sets. Dr. Burroughs routinely draws on methods and perspectives from a number of fields (education, policy evaluation, political science, history, economics, sociology, and analytic philosophy), with peer-reviewed publications in multiple academic fields. Prior to his work at PPA, Dr. Burroughs was part of educational research and evaluation centers affiliated with Indiana University and Michigan State University, where he participated in study design, data collection, project management, analysis, and reporting. He has also worked as a communications consultant and provided technical assistance as part of school reform efforts. Dr. Burroughs brings a synthetic approach to research and decades of experience working with stakeholders from diverse backgrounds. His approach combines the most rigorous feasible methods with a strong commitment to equity and collaboration.
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Teaching for Excellence and Equity: Analyzing Teacher Characteristics, Behaviors and Student Outcomes with TIMSS
This open access book examines the interrelationship of national policy, teacher effectiveness, and student outcomes with a specific emphasis on educational equity. Using data from the IEA’s Trends in International Mathematics and Science Study (TIMSS) conducted between 1995 and 2015, it investigates grade four and grade eight data to assess trends in key teacher characteristics (experience, education, preparedness, and professional development) and teacher behaviors (instructional time and instructional content), and how these relate to student outcomes. Taking advantage of national curriculum data collected by TIMSS to assess changes in curricular strategy across countries and how these may be related to changes in teacher and student factors, the study focuses on the distributional impact of curriculum and instruction on students, paying particular attention to overall inequalities and variations in socioeconomic status at the student and country level, and how such factors have altered over time. Multiple methods, including regression and fixed effects analyses, and structural equation modelling, establish the evolution of these associations over time.
