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Data Analysis

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Using various data elements, measures, and sources to guide decision-making from a systemic perspective. Data analysis should be incorporated in all essential elements, methods, and tactics. Data should not only guide identification, institutional change, and intervention efforts but should be used as a tool to evaluate program effectiveness within these measures. 

Data analysis is a key component of:

Providing student support

  • Monitoring student progress
  • Evaluating impact of services and support
  • Making decisions about school changes and improvements
  • The school improvement cycle for Colorado schools and districts under Unified Improvement Planning or UIP.

Strategies to support the effectiveness of interventions include the collection and analysis of the same data both before (pre-test) and after (post-test) the intervention.  Using the same data year after year provides the opportunity to identify and communicate trends, gaps and areas for improvement.  


Common measures that Colorado schools are using include:

  • Early Warning Systems: Attendance, Behavior, and Course Completion
  • Graduation, Dropout and Completion Rates
  • Performance Indicators: Academic Achievement, Academic Growth, Growth Gaps
  • Benchmark assessments to measure performance indicators
  • Individual Career Academic Plan (ICAP) Completion
  • SAT Scores
  • Concurrent Enrollment
  • Work-based Learning Opportunities
  • Apprenticeships