Kentucky Center for Mathematics External Evaluation 2015

Establishment of a School Database This task includes the collection of longitudinal data (from 2009 to 2014) on school characteristics (e.g., school size, school gender composition, school socioeconomic composition, and school racial ethnic composition) and school state test results online for schools in the Kentucky Center for Mathematics (KCM} Professional Learning Experiences (PLEs) database. All data collection will be conducted online without interrupting normal instruction of any school (i.e., research of school or district websites for data on school characteristics and school state test results). This database will provide one part of the foundation for data analysis to be discussed soon (see the last task). Note that this task requires substantial time commitment. Forms for school visits are already being filled out by RCs and KCM staff members. These data will also form part of the school database when they are available. Deliverable: A csv database of schools, their KCM participation by program and number of participants, the school demographic data and the results of school visits conducted by KCM staff or RCs. Development of an Online Survey of PlEs Teachers This online survey will track teachers who have participated in the KCM PLEs since the renewal of KCM. It will measure participation and leadership (influence) of teachers who have participated in KCM PLEs as well as administrative support that they have received for pursuing participation and practicing leadership (influence). Data from this survey will provide the other part ofthe foundation for data analysis to be discussed next. Deliverable: The csv file from "Establishment of A School Database" appended with the results of this online survey Examination of What Schools Promote Greater Academic Improvement through PLEs Do all KCM schools (schools in the KCM PLEs database) benefit equally from PLEs (in terms of academic improvement of their students)? What kind of schools benefit more from PLEs? Questions like these have great policy implications. With data from the school database and the teacher sur.tey {see above} and the school visits, we can effectively address these (and many other) critical and exciting issues. Dr. Xin Ma has done very similar work for a federal research grant in Michigan. He can supervise a Research Assistant (RA) to obtain above information without bothering a single school and then perform advanced longitudinal data analysis (e.g., growth model analysis) to address critical issues related to PLEs. Deliverable: Models associating variables in the database from part 2 with solid or exceptional growth.