In the tech world, the phrase “garbage in, garbage out,” is the idea that the quality of output is always determined by the quality of input (Market Business News, 2023). If data is entered incorrectly into a system, the output is unreliable. An example of “garbage” input would be an early childhood special education (ECSE) teacher entering the wrong placement code in a data system. This error in coding would produce incorrect data (“garbage” output) on federal indicator 6: Preschool Least Restrictive Environment, providing an insufficient overall report on preschool placements.
Using poor-quality data to make decisions about student performance or program progress can have a detrimental impact on the programs and children we serve. ECSE leaders manage varying types of data including three performance indicators, Child Find data, rosters, waitlists, and even VKRP and IEP progress data. To avoid errors in data collection and analysis, ECSE leaders are encouraged to assess their current data practices at the building and division levels to confirm the quality of their systems and practices. ECSE leaders can check the quality of their data by checking three points of reference: the individuals behind the data submission, the local processes that support data development, and the system output of the data collected (The Center for IDEA Early Childhood Data Systems, 2022).
For many special education systems, data comes from the initial entry made by teachers at Individualized Education Program (IEP) meetings. A division level ECSE leader may check the data, but final submission is often completed by a third individual. It is important for individuals at all levels of data collection and submission be knowledgeable about the data they are responsible for.
To make sure that all individuals at every level have the knowledge they need, leaders can ask:
- Who is responsible for entering and checking data?
- Are individuals trained on the data they are entering with annual refreshers?
- Is there a training plan in place for onboarding new staff?
- Has the person responsible for final submission been included in training?
- Who is responsible at the division level for analyzing the data after it has been collected and sharing it with those who matter?
For data to be of high quality, there should be an identified and consistent process in place for keeping data records up to date. For example, leaders can provide each teacher with a copy of Virginia’s Indicator 6 Decision Tree to support the process of placement identification at IEP meetings.
Leaders can further improve their processes by asking:
- Are there written procedures for how data is entered and monitored?
- Is there a process in place for monitoring data timelines and checking that data is correct before submission?
- Is there a process in place for checking that consistent steps are being followed to collect and report data?
- Has a learning plan been documented to ensure quality data collection with division-level turnover?
- Is there a system in place for updating new students who enroll into the program after the school year starts to avoid missing students in state reports?
A computer data system is only as good as the manual checks and balances in place to support the system. In some school divisions, data is entered into a special education database but reported from a different student information system. In this case, ECSE leaders must check to make sure that the data flows correctly from one system to the other. Division leaders are ultimately responsible for the data regardless of the data systems used to hold the data.
Leaders can answer these questions to check the quality of their data systems:
- Have you mapped the alignment of data to know that the data in your system is correct?
- If your data flows through multiple systems, have you checked the flow to make sure what goes into one system correctly transfers out to the new system?
- For the data manually entered in Virginia’s Single Sign-On Web Systems (SSWS), has someone double checked the entries to make sure the data was entered correctly?
- Is there a system of automated checks as well as manual checks to confirm data flow?
In a position where things can sometimes feel unmanageable, ECSE leaders can control data management for their respective role by ensuring that they have reviewed the systems, processes, and people that have the greatest impact on influencing their data. By improving these three areas, leaders can be confident in knowing they have committed to improving data quality and set the example for their division in data governance.
References and additional resources:
Early Childhood Technical Assistance Center. (2023). Data quality. https://ectacenter.org/eco/pages/quality_assurance.asp
Market Business News. (2023). What is GIGO (garbage in, garbage out)?https://marketbusinessnews.com/financial-glossary/gigo-garbage-in-garbage-out/
The Center for IDEA Early Childhood Data Systems. (2022). Data governance toolkit. https://dasycenter.org/data-governance-toolkit/
Virginia Department of Education. (2022). Data collection and reporting. https://www.doe.virginia.gov/teaching-learning-assessment/early-childhood-care-education/children-with-disabilities/data-collection-and-reporting
Virginia Department of Education. (2022). Special education child count. https://www.doe.virginia.gov/programs-services/special-education/reports-plans-statistics/special-education-child-count