The Evaluation of Mathematics and Science Partnership Program A Quasi Experimental Design Study Abdallah Bendada, MSP Director

Mathematics and Science Partnerships Grant Evaluation Model: Quasi-experimental design Sampling Instruments Outcomes Conclusions Future Studies Program Design

Evaluation Model 1.Participants reaction (Surveys, logs, …) 2.Participants Learning (Assessment, tests,..) 3.Organization support for changes (administration ) 4.Participants use of new knowledge (Observation, performance) 5.Student learning outcomes (Assessment, tests, …) All = Gold 2 to 5 = Silver 2 and 5= Copper Anyone = Tin

What is the true impact of the Mathematics and Science Partnerships Grant on student achievement in Wisconsin? The use of quasi-experimental design to evaluate the MSP projects using pre- and post-test data for teachers and their students is the most appropriate method to: measure the impact of the projects measure the students’ gains measure the teacher content knowledge assess the effectiveness of the MSP in Wisconsin

Sampling Program group: 75 middle school mathematics teachers from high-need LEAs. pre-selected Only 69 teachers participated completed the program Comparison group: 75 middle school teachers from similar LEAs. Matched to the program group. Only 71 teachers completed the program Program group: 5 students from each participating teacher randomly assigned. (325) Comparison group: 5 students from each participating teacher randomly assigned. (325)

Instruments 1- Teachers The Test of Mathematics Knowledge for Teaching School Mathematics also known as Learning Mathematics for Teaching (LMT) developed by Deborah Ball and Hyman Bass at the University of Michigan as an NSF project, were used to assess the teacher in both the pre- and post-test. 2- Students The Measures of Academic Progress (MAP) developed by the Northwest Evaluation Association (NWEA) in mathematics has been used to assess student achievement. More than 138 school districts in Wisconsin use MAPs in mathematics and reading to monitor the progress of student achievement.

Statistical Formulas

Program Teachers Comparison StudentsComparison Teachers Program Students

Conclusions Positive Impact in mathematics, Program teacher gained more content knowledge, The program impact is on teachers with lower content knowledge, Program students achieved higher, The program impact is on students with lower content knowledge, Effective evaluation designs are necessary for impact programs, and Variables such as the socioeconomic group, ethnic group, and disability should be factored in the evaluation design