Using Data to Target Instruction

This workshop guides educators through leveraging student data to personalize instruction and improve learning outcomes across grade levels. Participants explore how to gather and interpret various data sources—including demographics, IEPs, test scores, and classroom performance—to make informed instructional decisions. The training emphasizes designing valid assessments, analyzing results for grouping and differentiation, and integrating formative, interim, and summative assessments. By the end, educators will understand how to implement a data-informed cycle to support targeted interventions and instructional planning.

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• Lack of clarity or structure around using data to inform instruction.
  
• Ineffective or invalid pre-assessments that don’t provide actionable information.
  
• Inconsistent or informal assessment practices that fail to track progress meaningfully.
• Challenges in addressing individual learning needs in a diverse classroom setting.

1. Constructing and Using Valid Assessments:
   Participants will learn how to create valid pre- and post-tests that align in structure, content, and conditions. Emphasis is placed on creating assessments that yield accurate baseline data and reflect true student growth across all grade levels, including early learners and pre-literate students.
   
   
2. Implementing a Continuous Data Cycle:
   Educators will understand how to engage in a cyclical process of collecting, analyzing, and responding to data. This includes evaluating progress through formative assessments and refining instructional strategies in real-time to meet student needs.
   
   
3. Using a Variety of Assessment Tools for Differentiated Instruction:
   Participants will explore formative tools (e.g., observations, student self-evaluations, conversations), interim assessments for decision-making, and summative assessments for evaluating overall growth. They will be equipped with strategies to tailor instruction and group students effectively based on their assessment data

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