Results for M2 participants show significant positive changes in content knowledge for teaching after participation in M2. Content knowledge was measured using the Learning Mathematics for Teaching assessment, which was administered prior to and after participant completion of M2. Positive effects were also found for self-reported instructional practice (e.g., emphasis on National Council of Teachers of Mathematics process standards), use of assessment, and preparedness and confidence related to teaching mathematics, as measured by a participant survey administered at three points in time-before, during, and after participation in M2.
Analysis of mathematics achievement data, collected for all middle-level students in the Lincoln Public Schools, suggests both positive and negative effects associated with teacher M2 participation, which vary according to grade level. For the 2006-2007 school year, for example, significant positive effects were found for the mathematics procedures measure on the Metropolitan Achievement Test and the total math measure on the district criterion referenced test (CRT) for students in Grade 7. A significant positive effect was also found for Grade 8 student performance on the geometry and measurement measure of the district CRT. Significant negative effects were found for three measures from the district CRT for Grade 6 students: total math, computation, and numeration.
Results from the student achievement data analyses are considered preliminary, however. While the possibility of using hierarchical linear modeling (HLM) for these analyses was explored to allow for a more valid estimation of impact, the sample of classrooms and schools did not provide for adequate statistical power. A one-level regression model was therefore used for these analyses. Because this sort of analysis does not take into account the clustering of students within classrooms and schools, it can yield statistics with greater apparent precision and overstate statistical significance (Raudenbush & Bryk, 2002). Subsequent analyses will explore the possibility of aggregating student data across years for particular grades to increase the power associated with statistical tests.