# Presentation: 851284

## Instructional Practices 

- Instructional Practices
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**Chicago  Meeting**
**Progress Report**
**April 20, 2007**

## Task Group Members

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**Task Group Members**

**Russell Gersten**
**Camilla Benbow **
**Douglas Clements **
**Bert Fristedt **
**Tom Loveless **
**Vern Williams **
**Joan Ferrini-Mundy, Ex Officio **
**Diane Jones, Ex Officio **

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*** ***
**Framing of the Methodology Used and **
**the First Three Research Topics**

## Studies Sorted into Four Categories	

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***Studies Sorted into Four Categories*****	**
**Tier 1: Experimental and Quasi-experimental Studies that Meet What Works Clearinghouse Standards (Evidence of Causal Claims)**
**Tier 2:  Quantitative Studies that are Correlational/ Descriptive**
**Tier 3:  Qualitative Research (including case studies, beat the odds schools) **
**Tier 4: Flawed Experimental or Quasi-experimental studies**

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**In analyzing Tier 1 Studies:**
**	****Studies Must Meet What Works Clearinghouse standards (with two caveats)**
**Subject matter experts (Wu, Fristedt & Williams) will review the mathematical quality of: **
**	***** The measures**
**	***** The content taught (when feasible)**
**2.    Context will be described and discussed**
** **

## Role of Tier 2 and Tier 3 Studies

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**Role of Tier 2 and Tier 3 Studies**
**Will Help Frame Research Questions and Issues**
**Assist in Interpreting Findings from Experimental Research**

## Student and Teacher Centered Instruction 

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**Student and Teacher Centered Instruction **
**Part I:**
**Research on Cooperative and **
**Peer Assisted Learning**

## Cooperative Learning

**Cooperative Learning**

## Cooperative Learning

**Cooperative Learning**

## Peer Assisted Learning

**Peer Assisted Learning**

## Other Cooperative Learning Strategies

**Other Cooperative Learning Strategies**

## Mixed Approaches

**Mixed Approaches**

## Instructional Practices 

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**A. Formative Assessment**
**Focus on studies that examine the following questions:**
**Does use of formative assessments in mathematics improve students’ growth in mathematics proficiency?**
**Are there tools or enhancements that help teachers use this type of data? If so, do they improve students’ growth in mathematics proficiency **

## Instructional Practices 

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**Data Sources **
**Ten experimental and quasi-experimental studies **
**Elementary grades **
**Outcomes include both procedural and problem solving/conceptual measures of reasonable reliability and criterion-related validity**
**Content validity is under review at current time**

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**C.  Type of Formative Assessments Studied**
- Sample from state standards
- Measures are brief and include a random selection of items from the years’ scope and sequence
- This approach is more reliable and valid than a sampling of only one week’s material
- This is the only body of research that has been studied experimentally
- Other approaches may have equal effect; they simply have not been studied systematically

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**D. Findings: Question 1**
- Yes, use of formative assessments by teachers (and often students) significantly enhances students’ growth in math proficiency.
- Result is statistically significant
- Average effect size is small and corresponds to about a nine percentile point growth, on average

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**E: Findings Question 2**
- 	Effect is almost doubled when the various enhancements 	are added.
- But, most of these studies include only special education students.
- Thus, it is unclear if the results will work as well for non-disabled students.
*Remember that almost 10% of the student population currently fits into the learning disabilities category.*

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**F.  What are the Enhancements?**
**1. Using formative assessment data as basis for peer tutoring activities.**
**2. Providing teachers with an analysis of areas of strength and weakness for individual students and areas of weakness for the class.**
**3. Providing teachers with specific instructional ideas and approaches to address the identified problem.**
**4. Teaching students to monitor their own progress and interpret the graphs of their progress.**

## /.....

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- “Real-World” Problem Solving

## Fundamental Question:

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- 	What is the impact of instructional approaches that feature the use of “real-world” problems on student learning and achievement?

## “Real-world” problems have been a feature (in various forms and with differing levels of emphasis) in US mathematics curriculum for a century

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- “Real-world” problems have been a feature (in various forms and with differing levels of emphasis) in US mathematics curriculum for a century
- Many current policy documents call for the use of “real-world” problems in mathematics instruction, and this is reflected in some instructional materials

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**Varied Meanings of “Real-World” Problems in the Literature, e.g.:**
- problems that will be meaningful, appealing, and motivating for students (from contexts that they know, from imaginary situations, from mathematics)
- authentic problems, similar to those in applications beyond school
- complex problems with multiple steps, integration of concepts
- “open-ended” problems

## 	There are many arguments, based in beliefs, experience, and research, both for and against the use of “real world” problems in mathematics instruction.

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- 	There are many arguments, based in beliefs, experience, and research, both for and against the use of “real world” problems in mathematics instruction.

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- Examining 12 studies thus far:
- 3 quasi-experimental studies that have examined the    impact of specific curricula, all with methodological problems
- 9 other studies that look at the impact of various types of instruction using “real-world” problems, and/or instructional strategies to help students solve real-world, again with methodological problems