Meta-Analysis Database

Understanding MRL's Action Research Meta-Analysis Database

MRL's Meta-Analysis Database

See the Database: MRL's Action Research Meta-Analysis Database

Database Facts: MRL's Action Research Meta-Analysis Database currently contains 1036 studies involving 22 instructional strategies. (Read strategy descriptions here.) This data was collected from 509 teachers at 87 schools in 26 districts. It should be noted that 198 teachers indicated that they conducted studies involving more than one instructional strategy. Data for those teachers was listed in the database with each Strategy ID. The database was last updated April 4, 2011.

Understand the Database:

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Understanding Meta-Analysis

Translating research into practice is the hallmark of Marzano Research Laboratory (MRL). This research-based approach to improving education is the key to why MRL is on the cutting-edge of finding and applying strategies that work.

Before recommending a practice for an individual teacher, a school, or an entire district, MRL first examines the research literature as comprehensively as possible to identify specific studies on specific practices. The studies found in the research literature are then analyzed using a statistical technique referred to as meta-analysis.

Meta-analysis follows a straightforward process: (1.) finding relevant studies pertaining to a practice of interest (i.e., note taking); (2.) grouping findings based on common purposes and variables; and (3.) using the effect sizes of each study in a group to calculate an average effect size (ES) for the group. (For a more thorough explanation, see Dr. Marzano's book, Designing & Teaching Learning Goals &
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Next MRL translates the findings from the meta-analysis into easily used strategies for teachers and administrators. By definition, these strategies are "research-based" in that they are grounded in the research found in professional journals and reports.

MRL then seeks teachers and administrators to try these strategies in their classrooms, schools, or districts. Whenever possible, these "action research" studies involve experimental classes (those classes in which a particularly strategy is used) and control classes (those classes in which a particular strategy is not used). It is these experimental/control action research studies that make the strategies recommended by MRL "evidence-based." They have their own unique evidence attesting to their utility, not just the evidence from the research literature. These action research studies are subjected to meta-analysis to track their utility in a variety of situations.

In MRL's Action Research Meta-Analysis Database, you will find results collected from over 200 teachers who participated in MRL action research studies in their classrooms. You can find explanations for how to read the data at the top of this page.


The Role of Action Research

For the most part, each of these studies represents a "snapshot of time" in the classroom. Because each teacher develops his/her own style of teaching in the classroom based on his/her experiences and education, it would not be a fair comparison to analyze the results of one teacher with those of another. So, each teacher acts as his/her own control by administering the same pretest and posttest to two different groups of students.
Action Research in Action:

Read detailed action research reports by Marzano Research Laboratory.

See the research here.

One group, the control group, is taught without the use of the target instructional strategy. The other group, the treatment group, is taught with the use of the target instructional strategy. Find more detailed instructions regarding the requirements for participation in action research here.

Except where noted, the data presented in MRL's Action Research Meta-Analysis Database was analyzed using the general linear model. One independent variable (treatment/control condition) was analyzed as a fixed effect. In each case, the pretest was used as the covariate. In effect, a fixed effects analysis of covariance (ANCOVA) was executed for the dependent measure. The advantage of using an analysis of covariance with the pretest as the covariate is that it statistically adjusts for students' initial status on the measure in question. In other words, it is a way of controlling for students' differences in what they know about a topic prior to the beginning of instruction on the topic. When random assignment to groups is not feasible, the ANCOVA design (with pretest as covariate) is commonly used to address students' prior achievement relative to the dependent variable.

MRL provides this database of its action research studies so that others may use it in their quest to find useful strategies for their classrooms, schools, and districts. This database will be updated periodically as MRL gathers more studies to add to its growing body of work in support of its evidence-based recommendations.