Data-Driven Decision Making

CTAC’s Data-Driven Decision Making Training Model builds the capacity at the school level to use multiple sources of data and specific analytical tools to develop plans and implement changes that address the root causes of academic underperformance. By leading school-based teams through a protocol to examine data, educators can focus on proactive steps to respond to findings for individual students.

Phase I: Establishing an Evidence-based Culture

We work collaboratively with district/school leaders to gather and organize perceptual data, early formative data, and vendor, state, and district provided summative/formative data into a Comprehensive Data Analysis (CDA) report. While the CDA is being compiled and analyzed, training for teacher teams begins with a focus on establishing an evidence-based culture and developing data literacy.

  • Comprehensive Data Analysis (CDA) is compiled, studied and analyzed and subsequently used to customize subsequent training.
  • Workshop: Data Literacy This training engages teacher teams in establishing working norms for the group with consideration for building group trust and collegiality. Teacher teams are guided through a series of activities to begin to build their understanding of a protocol for talking about student data, deepening knowledge in how to generate and examine reports to answer questions, and generate useful standards-aligned evidence of student learning beyond what standardized data provides.

Phase II: Building the Capacity for Data-Driven Action

Phase II kicks off with two training sessions focused on developing data literacy, data collection, data systems and instilling a continuous improvement cycle. These are supplemented with instructional rounds, virtual coaching, and data collection refinement.

  • Workshop: Measuring Learning Part 1 Teacher teams are guided through activities to develop their abilities to measure student learning on the identified standards, identify instructional priorities and establish specific learning goals/targets at the school, classroom, and student levels.
  • Workshop: Measuring Learning Part II Teacher teams learn how to us assessment data to determine evidence regarding student acquisition and/or mastery of a body of knowledge and apply this knowledge to learning in their own classroom.
  • Instructional Rounds provide the primary mechanism for monitoring implementation and determining how data-driven decision making is improving teaching and learning. The focus is on developing the capacity of school leaders and members of the instructional leadership team to monitor student learning measures in action in the classroom. School leaders and instructional leadership team members are guided through the process of collecting evidence of data-driven instruction during classroom observations and determining next steps for supporting teachers in deepening their knowledge and skills.
  • Virtual Coaching sessions support teacher teams in the acquisition of strategies for data-driven instruction.
  • Data Collection Refinement occurs as school leaders and teacher teams are guided through refining data collection practices and customizing reports from state and vendor provided assessments.

Phase III: Evaluating Results

In the final phase, an Evidence Summit allows teacher teams to review results, reflect upon their learning, and celebrate accomplishments from the first year-long cycle of data-driven decision making.

  • Evidence Summit provides an opportunity for school leaders and teacher teams to be guided through a process for evaluating results of long-term goals established earlier in the year and setting new priorities/goals for the upcoming school year establishing a cyclical process for continuous improvement.