Skip to main content

Reminder: All system self-assessments are due by April 30 for the Recognized Schools Program.

Strategic Use of Data

Educators collect data to measure learner (student) progress using formative, interim, and summative assessments. Similarly, it’s important to gather data around how the school and district systems are equitably serving families and communities.

Strategic use of data goes beyond gathering and compiling data; teams use it to action plan.

Using implementation data and outcome data

For a complete picture of the health of their systems, Wisconsin schools and districts must execute ongoing, reflective, and collaborative analysis using two general types of data:

  • implementation data (measures system effectiveness and efficiency)
  • student outcome data (measures the impact the system has on learner outcomes)

Educators systematically review implementation and outcome data with a growth mindset to plan next steps. As part of a continuous improvement process, they use data to create action plans and evaluate results. When needed, teams dig deeper and examine the root causes.

Implementation data measures which practices are in place with fidelity

Implementation research shows that schools and districts only realize improved student outcomes when evidence-based practices are fully implemented across the system with fidelity (used as intended). System self-assessment allows schools to gauge the extent to which practices are in place and if they are being delivered with fidelity.

Implementation data measures staff:

  • Knowledge,
  • attitudes,
  • beliefs, and
  • practices.

In other words, implementation data reveals the connection between adult behavior and learner outcomes.

System assessments used in Wisconsin

Here is an overview of system self-assessments in an equitable, multi-level system of supports. Teams use the assessment calendar to schedule when to perform their assessments.

Behavior self-assessments

Behavior assessments measure adult practices (not the students) for equitable, consistent, and effectiveness delivery of supports. The most common assessments to measure the implementation of behavior strategies are:

  • Tiered Fidelity Inventory (TFI) – measures all implementation levels (all tiers)
  • Benchmarks of Quality (BoQ) – measures the universal implementation level (tier 1)
Academic self-assessments

Academic assessments measure adult practices (not the students) for equitable, consistent, and effectiveness delivery of supports. The School-wide Implementation Review (SIR) is taken through a reading or mathematics system lens and measures all levels of implementation of academic support strategies.

Outcome data helps gauge how well supports work for learners and families

It’s important to use multiple forms of aggregated and disaggregated learner outcome data to:

  • Gauge the effectiveness of systems of supports for learners and families, and
  • identify who is benefiting from and whose needs are underserved by the system.

Examples of outcome data

Teams use data from several sources in addition to system self-assessments to gain additional insights into areas of focus, types, levels of analysis, and sources. Here are some examples:

  • Areas of focus (academic, behavioral, developmental, emotional, social, etc.)
  • Types (achievement, anecdotes and interviews, attendance, climate surveys, development, early warning system indicators, formative and interim assessments, observation, office discipline referrals, performance, etc.)
  • Levels of analysis (aggregated and disaggregated)
  • Sources (community, families, learners, and staff)

Universal screening helps schools proactively support learners

Universal screening processes and data help schools proactively match supports to needs.

Throughout the year, teams:

  • Use a universal screening process to review academic, behavioral, emotional, and social data for every learner,
  • review aggregated data to gauge whether the universal level of support is meeting the majority of learners’ needs,
  • review disaggregated data to identify areas of inequity, and
  • use a problem-solving process to make universal-level adjustments.

This process also helps identify learners who may benefit from support beyond the universal level. For example, some learners may need interventions to improve specific academic, behavioral, emotional, or social skills. Learners who exceeded academic benchmarks may need additional challenges to meet their learning needs.

Strategically using data to drive continuous improvement efforts

Continuous improvement is an ongoing effort to improve a framework or process.

It requires an organizational commitment to:

  • Adaptation,
  • continual learning,
  • growth, and
  • self-reflection.

School teams use a continuous improvement problem-solving process to inform decisions and achieve equity.

How do you know your system has strategic use of data in place?

Teams at all levels of support:

  • Use implementation data (staff knowledge, attitudes, beliefs, and practices) to:
    • Gauge the extent to which practices are in place and used as intended
    • Gauge the extent to which features of an equitable, multi-level system of supports are in place and implemented with fidelity
    • Guide action planning, professional development, and resource allocation
  • Use multiple forms of aggregated and disaggregated learner outcome data to:
    • Gauge the effectiveness of system of supports for learners and families
    • Identify who is benefiting from and whose needs are underserved by the system
  • Skillfully use problem-solving processes to inform data-based decisions and actions
  • Establish an environment of trust and transparency for data use
  • Use consistent, culturally competent processes focused on changing the system and adult practices, rather than fixing learners and families

Resources for this Key System Feature