EDUCATIONAL RESEARCH FOR THE GOOD OF SOCIETY  

 EXPLORING PRE-SERVICE TEACHER EDUCATION:IMPACT OF HIGHER EDUCATION INSTITUTIONS ON PUPIL MATHEMATICS PERFORMANCE

Mary E. Yakimowski and Mary Truxaw

Presentation at the annual meeting for the

Northeastern Educational Research Association

Rocky Hill, Connecticut

October 2011

Office of Assessment

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A Great Education Begins with Great Teachers

Teachers for a New Era (TNE) - An initiative designed to improve teacher quality by

reforming outstanding teacher preparation programs

Design Principles 1. Emphasize to preservice teachers the

importance of demonstrating student achievement through evidence.

2. Fully integrate faculty from the liberal arts and sciences, enriching future teachers' general and subject matter knowledge.

3. Support will be extended to beginning teachers from their individual colleges and universities.

Focus on how the UConn Neag School of Education is examining K-12 performance

More specifically, we would like to examine the patterns of Connecticut’s grade 3-8 pupils of graduates of our Teaching Education Program as part of our Neag Assessment Plan through our Teachers for a New Era project

Literature Review

Teachers have been found to be critically important in students’ mathematical learning and performance (Ball, 2003; Ball, Lubienski & Mewborn, 2001; Fennema & Franke,1992; Shulman, 1987)

There are significant interests in examining growth achievement models (e.g., Barone, 2009)

High-quality teacher education programs take on an important role (Bransford, Darling-Hammond & LePage, 2005; Darling-Hammond, 2006)

Lack of empirical evidence connecting teacher education programs with student outcomes (Crowe, 2010; Grossman, 2008)

Purpose of This Study

Examine the impact of teacher education experiences at higher education levels on pupil performance in mathematics.

Differences on pupil performance in mathematics between UI group vs. Non-UI group

Sampling

5 public school districts in Connecticut

12,047 students from grades 3 through 8

InstrumentationThe fourth generation of Connecticut Mastery

Test (CMT-4) mathematics portion

Grades 3 through 8 in the spring at each year

5 domains and 25 corresponding strands in CMT-4 math test are tested:

Numerical and Proportional Reasoning Geometry and Measurement Working with Data: Probability and Statistics Algebraic Reasoning: patterns and functions Integrated Understanding

__________________________________________________________________________Numerical and Proportional [NP]1. Place Value2. Pictorial Representations of Numbers3. Equivalent Fractions, Decimals and Percents4. Order, Magnitude and Rounding of Numbers5. Models for Operations6. Basic Facts7. Computation with Whole Numbers and Decimals8. Computation with Fractions and Integers9. Solve Word Problems10. Numerical Estimation Strategies11. Estimating Solutions to Problems12. Ratios and Proportions13. Computation with PercentsGeometry and Measurement [GM]14. Time15. Approximating Measures16. Customary and Metric Measures17. Geometric Shapes and Properties18. Spatial RelationshipsWorking with Data: Probability and Statistics [DPS]19. Tables, Graphs and Charts20. Statistics and Data Analysis21. Probability24. Classification and Logical ReasoningAlgebraic Reasoning: Patterns and Functions [AR]22. Patterns23. Algebraic ConceptsIntegrated Understanding [IU] (May include content from one or more of the four domains) 25. Mathematical Applications__________________________________________________________________________

Specifically, our objectives are to: 1. Measure the impact of teacher

education experiences in higher education on pupil performance in mathematics.

2. Interpret the findings and provide recommendations for a modified model to evaluate teacher preparation programs in higher education institutions.

Overview of Results

Total (Raw) Score Domain Scores Strand Scores Proficiency Level Scores Vertical Scale Scores

Research Question Scores Type OtherOverall mathematics achievement for pupils educated by UI alumni? Is it any different from pupils of alumni from other institutions?

Overall raw score

Descriptive, t-test

1 year

Five mathematics domains scores for pupils educated by UI alumni? Is performance in the domains for these pupils any different from pupils of alumni from other institutions?

5 domain scores

Descriptive, t-test

1 year

25 mathematics strand scores of pupils of UI alumni? Is this performance any different from pupils of alumni from other institutions?

25 strands

Descriptive, t-test

1 year

Pattern in pupil proficiency status for those educated by UI alumni? Is the performance any different from pupils of alumni from other institutions?

Proficiency level

Proportion analysis

1 year

Overall pupil mathematics achievement for those educated by UI alumni after controlling for initial difference on earlier achievement? Is it any different from pupils of alumni from other institutions?

Vertical scale

ANCOVA Covariate:last year’s results

Overall score UI was 106 (SD = 22.8)Non-UI of 95.3 (SD = 26.8)

Domain 1 – Numerical / Proportional UI 53.3 Non-UI 46.4

similar results for each domain

Domain 1 - Strand Score Results

Domain 1 - Strand Score Results

CMT-4 Geometry and Measurement [GM] domain’s five strand scores for two teacher groups.

Domain 2 - Strand Score Results

Research Question Scores Results

1 What is the overall pupil mathematics achievement educated by UI alumni? Is it any different from alumni from other institutions?

Overall raw score

UI score (106.1) > Non-UI score (95.3); statistically significant

2 What are the five mathematics domains scores educated by UI alumni? Is the pupil performance any different from alumni from other institutions?

5 domain scores

UI Domain scores > Non-UI Domain scores; statistically significant; e.g., for Domain1, UI score (53.3) > Non-UI score (46.4); statistically significant

3 What are the 25 mathematics strand scores from UI alumni? Is the pupil performance any different from alumni from other institutions?

25 strands UI Strand scores > Non-UI Strand scores; statistically significant; e.g., for Strand 9, UI score (5.6) > Non-UI score (4.6); statistically significant

4 What is the pattern in pupil proficiency status by those educated by UI alumni? Is the pupil performance any different from alumni from other institutions?

Proficiency level

76% of UI and 60% of Non-UI in the Goal and Advanced categories; 9% of UI and 20% of Non-UI in the Below Basic and Basic categories

5 What is the overall pupil mathematics achievement educated by UI alumni after controlling for initial difference on earlier achievement? Is it any different from alumni from other institutions?

Vertical scale

UI score (536.7) > Non-UI score (525.6); statistically significant after controlling for initial difference on earlier achievement

Overview of Findings to Each Research Qs

Proficiency Level

Non-UI UI

Level % %Below Basic 9.1 4.2Basic 10.7 4.4Proficient 20.4 15.4Goal 32.6 36.2Advanced 27.2 39.8

Groups n Unadjusted 2007-2008

Unadjusted 2008-2009

Adjusted2008-2009

Non-UI 9072 513.0 541.3 542.6

UI 816 534.2 564.2 549.1

F p

Between-Subjects Effects Intercept 3914.3 0.001***

MAVS2007-2008 32283.6 0.001***

Teacher Group 36.6 0.001***

Vertical Scale Results

Discussion

Two groups Limitations Modified Impact of programs Future Research

As noted by Education Secretary Duncan … at an annual meeting of the American Association of College of Teacher Education in February of 2010 in Atlanta, saying,

“To put it in the simplest terms, we believe teacher-preparation programs should be focused on results.”

Aligned with charge, we do contend that we must continue to strive to build an evidence-based teacher preparation model, which is directly linked to pupil academic performance; however, it is simply one piece as a puzzle to really evaluate a teacher education program.

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 EXPLORING PRE-SERVICE TEACHER EDUCATION:IMPACT OF HIGHER EDUCATION INSTITUTIONS ON PUPIL MATHEMATICS PERFORMANCE

Mary Truxaw and Mary E. Yakimowski