Do Professional Communities Improve K-16 Curricula Mastery and Augment Mathematics Achievement?
Co-Principal Investigators: Elizabeth Stearns and Roslyn Mickelson
Purpose: To date, there has not been a comprehensive national analysis of students' mathematics achievement between kindergarten and twelfth grade. Some researchers have assessed growth over the entire period of schooling, but these studies are local and are not nationally representative. To address this need, the researchers will examine mathematics achievement trajectories for students in elementary, middle, and high schools, and identify possible mechanisms that appear to enable students, particularly lower achieving students, to augment their achievement.
Project: The researchers will conduct secondary data analyses using the Early Childhood Longitudinal Study (ECLS-K), the National Education Longitudinal Study (NELS), and the Education Longitudinal Study (ELS). Analyzing these datasets simultaneously will allow the researchers to identify important components of mathematics achievement during elementary, middle, and high school. It will also help assess whether mathematics achievement growth predicts post-secondary educational outcomes.
Products: The expected products of this research include published reports on the relationship between mathematics curricula and school organizational structure on students' mathematics achievement trajectory and post-secondary school attainment. Peer reviewed publications will also be produced.
Setting: The current study will use data from the ECLS-K, NELS, and ELS.
Sample: The ECLS-K began in 1998 with a sample of kindergarten students. Subsequent follow-up surveys were conducted when most students were in grades 1, 3, 4, and 8. The National Education Longitudinal Study began in 1988 when students were in eighth grade. Students were surveyed four more times over a 12-year period as they progressed through high school and joined the workforce or went on to pursue postsecondary education. The ELS began in 2002 when students were in tenth grade. Students were sampled again in the twelfth grade and then again two years after high school. All three datasets (ECLS-K, NELS, and ELS) include nationally representative samples of students.
Research Design and Methods: The researchers will examine the relationship between mathematics curricula, instruction, and school organizational structure on students' mathematics achievement during elementary, middle, and high school. The researchers will also examine whether mathematics curricula, instruction, and school organizational structure moderates gaps in mathematics achievement trajectories by student race, socioeconomic status, and gender. In terms of mathematics curricula and instruction, the researchers will examine teachers' use of more traditionalist approaches to mathematics instruction as compared to more reform-oriented approaches, along with the amount of time teachers spend on any mathematics activity. In order to understand the ways in which school organizational structure is related to mathematics achievement, the researchers will examine the school professional community and its relationship to teacher satisfaction and turnover rates, teacher credentials, student culture, and opportunities to learn. The researchers will use three datasets, ECLS-K, NELS, and ELS to answer their research questions. Analyzing these datasets simultaneously will allow the researchers to identify important components of mathematics achievement during elementary, middle, and high school. It will also allow them to assess how mathematics achievement growth predicts post-secondary educational outcomes.
Control Condition: Due to the nature of the research design, there is no control condition.
Key Measures: The key independent variables of interest are mathematics curricula and school organization structure. The primary dependent variable in the analyses will be student-level item response theory scale scores in mathematics from each data set. In addition, using the ELS and NELS, the researchers will examine the prestige of the postsecondary institution attended by the student.
Data Analytic Strategy: Mathematics achievement will be analyzed using growth curve modeling to assess students' mathematics trajectories over time. Postsecondary outcomes, including college prestige, will be analyzed through ordinary least squares regression.
Publications from this project:
Moller, S., Mickelson, R., Stearns, E., Banerjee, N., and Bottia, M. (2013). Collective pedagogical teacher culture and mathematics achievement: Differences by race, ethnicity, and socioeconomic status. Sociology Of Education, 86 (2): 174–194.