A Data Framework

Each school will make the decision about who is to be involved, when, and in what ways.  Surely, the school improvement team (or whatever the leadership team is called) should be involved in the initial analysis of the data. But the process should be transparent and everyone in the school community, including families, should know about the process and have access to the data if they want it. 

1.    List Priority Goals

Ideally, the listing of priority goals is available in a public place and on handouts to the school community.  One way to list the goals is list them in a column on the left side of a legal sized page.  Across the top of the page, the specific categories that reflect the details of goal attainment for different groups of students can be arrayed. A page of each grade level would be necessary.  But there are other ways.

2.    Assemble Relevant Information for Each Goal

The information needed to examine the extent to which students have achieved priority goals depends, of course, on the specifics of the goals and the decisions made about how attainment of these goals will be measured during Step 3 of the KEYS-CSI process. Data developed to determine whether the school is meeting goals for “Annual Yearly Progress” are necessary but not likely sufficient; they deal with only part of the curriculum and the tests involved typically do not address the more ambitious goals of the
teachers in the school.

Data on student learning should be disaggregated by various sub-groups of students This, of course, is required by federal law but schools may wish to use other breakdowns depending on the makeup of the student body (federal definitions of ethnicity are very general, for example), goals of the school and ideas about the factors that influence student achievement. For possible ways to disaggregate student performance data, CLICK HERE. [link 4a]

Longitudinal data are important in order to see trends. Most studies show substantial variation in aggregate student scores from year to year.  “Value-added” data that trace individual student progress are optimal.
 
While we use the term “data” (as in data based decisions making), evidence about student performance may not be readily quantified.  For example, teachers may have identified writing samples as a source of evidence on student literacy and therefore want to example samples of student work. Such “qualitative” data should inform judgments about needed improvements.

3.    Enter Quantifiable Data on Worksheets

In part 2 (above) of this framework for analyzing student performance, a possible format for organizing data was suggested.  This part involves entering the relevant data in each box on the chart.  Of course, there is software available for doing this and school districts may have such processes in place.  Spreadsheet programs like Excel can be adapted to this purpose.