The Evaluation of Mathematics and Science Partnership Program

A Quasi Experimental Design Study

Abdallah Bendada, MSP Director

Abdallah.bendada@dpi.wi.gov608-267-9270

• 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.

X Xz

SD

z

2

( )1

1xx

k X k Xr

k k

1 2

2 21 2( ) / 2

X Xd

SD SD

Statistical Formulas

Score Gain Differences between Program and Comparison Groups

-2

0

2

4

6

8

10

12

14

16

1 2 3 4

Groups

Sco

re G

ain

s

Program Teachers

Comparison StudentsComparison Teachers

Program Students

Program Teachers' Gains

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

0 20 40 60 80

Teacher

Z-S

core

Teacher: Score Distribution

0

0.1

0.2

0.3

0.4

0.5

-3 -2 -1 0 1 2 3 4

Score

Freq

uenc

y

ProgramComparison

Student Gains

-5

0

5

10

15

20

0 10 20 30 40 50 60 70 80

Student Teams

Raw

Sco

re G

ain

Program

Comparison

Z-Score True Gains

-2.00-1.50-1.00-0.500.000.501.001.502.002.503.00

-2.00 -1.00 0.00 1.00 2.00 3.00 4.00 5.00

Teacher Gain

Stu

den

t Gai

n

Students: Score Distribution

0.00

0.20

0.40

0.60

0.80

1.00

1.20

-2.00 -1.00 0.00 1.00 2.00 3.00

Score

Comparison

Program

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