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Resources:

Paradigm Shift to Data-Driven Decision Making

Top 10 uses of data in schools

Attributes of districts that make wise use of data

Making the case for data-driven decision making

Beginning the dialogue: A video-centered discussion

Considerations for data analysis

Types of data

Considerations for the data collected

Considerations for disaggregation of data

The inquiry cycle

Considerations for the data collected

  • Fit: How well does the data match the key issues or questions being investigated? No one in a school has time to collect and analyze data that is not important or won’t be used.
  • Utility: What is the purpose of the data being collected? The data must be useful to students, teachers, administrators, parents, and other stakeholders, and allows them to solve problems and make the changes needed.
  • Quality: How accurate is the data? The use of multiple sources of data must be used to compensate for biases in data and compensate for other imperfections in the data collected.
  • Validity: Does the data measure what they are intended to measure? All data collection methods should be put to the validity test.
  • Reliability: Are the instruments used in gathering data consistent? Assessments can pose problems if the results vary greatly depending on who scores them, or if the same assessment gives different results at different times.
  • Feasibility: How easy or difficult is it to gather the data? Schools must consider both the time and money needed when deciding what data to gather, as well as when and how to gather the data.

Education Commission of the States, Informing Practices and Improving Results with Data-Driven Decisions, August 2000

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