CAA for Science Administration Research FilesThese research files contain results from the 2017-18 year two pilot of the California Alternate Assessment (CAA) for Science. The data is intended for use by educators or researchers to perform analyses and preparation of customized reports.
Preliminary indicators offer a general indication of student content knowledge. They include a percent of items answered correctly and an indicator category. Preliminary indicators provide a broad and early indication about a local educational agency’s (LEA’s) implementation of the alternate assessment science standards. They should be used in conjunction with other information available at the LEA, as preliminary indicators are not precise enough to stand on their own. It is not recommended that preliminary indicators be used for any high stake purposes. More information about the indicators can be found in our Preliminary Indicator Communication Toolkit.
Downloading CAA for Science Research Files
Use of these research files requires some expertise in the handling of data and advanced data management skills. Many of the district and county research files are very large (up to 130MB) and maybe too large for spreadsheet applications. Database applications such as MS Access, SAS, or SPSS are required to manage these files. The file size is indicated in parentheses and is shown only when the size is greater than one megabyte.
File Layouts for the 2017–18 CAA for Science, Year Two Pilot Administration
Entities (ZIP)– This table is comprised of the state, all counties, districts, and schools in California. Because there are both school-level and district summary records as well as county and state summary records, it is critical that in any analysis, a “Type ID” record type be selected. This will help avoid the double or triple-counting that will occur when a school count is also counted in the associated district record.
Access Data Shell (ZIP) – A database “shell” is another alternative provided at this site. Once downloaded to the target computer, this application provides a powerful school, district, CDS, and ZIP code search capability as well as a formatted report containing all the data for the selected entity. This MS Access 2007 shell contains all entity data and is designed to import any of the selected state, county, or district comma delimited files. In order to use the shell, MS Access 2007 must already be installed on your computer.
Getting Accurate Results from the Research Files
Achieving accurate results when working with these research files requires an understanding of the structure and content of the two primary tables: the entities table and the test data table. The research files have many rows for each entity. There are records for each combination of grades, tests, and student groups. This means that there are hundreds to thousands of records for each entity, with an average of approximately 900 records. In order to correctly work with the data, you must use constraints to limit the data you are reporting. These constraints are discussed below.
Test Data Table
This table is comprised of the school, district, county, and state aggregate science test taken counts and preliminary indicators (i.e., percent correct and indicator category). To accurately analyze and report from these research files, the appropriate constraints must be applied to the following elements:
- CDS code – The research files contain summary district and county records. A district summary record will have a “school” code of “0000000.” When working with the file, be sure to include the county, district, and school codes. Failure to include all three data codes will result in double-counting in any summary calculations.
- Test type – Identifying the desired test (science) will help to provide clear query results.
- Subgroup ID – Each student will be included in both the “All Students” student group aggregation and each of the appropriate student group aggregations. Consequently, an individual student group must be selected to avoid duplicate counts. For Subgroup ID code, refer to the CAA for Science Demographic File Layout.
Providing accurate and meaningful reports from the research files generally requires the “linking” of the Entities and Test Data tables. Additional efforts might include linking to the “lookup” tables. Working with these tables requires an understanding of “relational” data tables and their manipulation.