TECHNICAL PRINCIPLES

Philosophical Principles Technical Principles

1. Each record (row of data) should contain information on the appropriate unit of analysis. Thus, student data sets should have records that include information on individual students, teacher data sets should have records that include information on an individual teacher or prospective teacher, school data sets should include information on individual schools, and preparation program data sets should have records that include information on teacher preparation programs.
2. Because comprehensive data at each level—student, teacher, school, and preparation program—must be drawn from a combination of other databases at the same level, a unique identifying number should be included in each data set. For example, all data sets that include information on students should include a unique identifying number for each student. 
3. Because most useful analyses require data from multiple levels, data sets at each level also should include another unique identifying number that can be linked to another level of data. For example, teacher data sets should include both a unique number that identifies the teacher and a unique number that identifies the school(s) that employ(s) the teacher. Click here to see a proposed set of linkages.
4. Because most useful analyses must examine data longitudinally, the unique identifying numbers should remain constant over time.
5. Because of the tracking requirements, the database should be longitudinal, so that records can be updated at least once annually. Updates would document changes that take place from one year to the next.
6. Data should be as complete and as accurate as possible. At each level, investments should be made to ensure accurate data submission through the review and “cleaning” of data. At the individual level, prospective teachers could be required to provide their data as a condition for being admitted to a teacher education program, being awarded a degree and/or a recommendation for licensure, being granted a license to teach, or being employed in a public school in the state. At the school level, schools/districts could be required to submit appropriate data to receive state and federal funding. At the preparation level, programs could be required to submit appropriate data in order to receive state accreditation.
7. To the extent possible allowable under existing legal statutes, survey data should be collected from teachers, administrators, and preparation program personnel. The database should contain standardized survey data that permit researchers to study why teachers follow various career paths and/or why their students are successful (or not) on a variety of learning measures.
8. The privacy and security of individual records in the database must be protected, and any release of records to researchers or members of the public should be without Social Security numbers or other personal identifiers.
9. The database should be designed to produce both standardized and customized indicators and reports for educational policymakers at all levels. For those who need the full detail of the database, it should be made available without personal identifiers.
10. Oversight of the database should be entrusted to a state entity that can enforce security safeguards, assert the authority needed to collect and edit data, add and revise reports as needed, maintain the system, and work effectively across K-12, community college, and university organizational boundaries.

Last updated: February 21, 2006