Data-Based Decision-Making

Data-based decision-making is the implementation of a proactive, systematic process of collecting, analyzing, and using forms of data such as screening, progress monitoring, and other methods to inform student needs and allocate resources at the individual, classroom, building, and system levels.

Essential Features

A written comprehensive assessment plan is in place and used for collecting various types of assessment data, including:  

  • Quality assessment tools and sources (such as diagnostic, functional, and outcome) that are inclusive of academic and non-academic data
  • Administration and data collection that is consistent, accurate and timely to ensure data quality
  • Staff roles and responsibilities regarding the administration, collection, interpretation, and use of data
  • Evaluating the extent to which assessments, interventions, and supports are implemented as intended

An integrated data system is in place and used to document and access student-level academic and non-academic data — represented visually or graphically — and support teams in using and analyzing data together (such as analyzing literacy data alongside attendance data) to inform decision-making. 

A written, iterative data-based decision-making process is in place and used for analyzing and using assessment data, including:

  • Using data-based decision rules for academic and non-academic areas that are consistent across buildings
  • Using an integrated data-based decision-making process to ensure that all decisions are objective and evidence-informed, and that they proactively address academic and non-academic needs at the individual, classroom, building, and system levels:
    • Who may need help? Where is help needed?
    • What kind of help is needed?
    • What instruction, supports, and resources will address the identified need?
    • Are the selected instructional materials, supports, and resources effectively meeting the need?
  • Evaluating the implementation of academic and non-academic high-quality instructional materials, evidence-based programs/practices, and research-based practices within the continuum of supports prior to concluding that a student is not responsive to instruction
  • Using academic and non-academic trend data to inform progress (including at system, building, grade, and student levels)

Conditions for Success

Shared Leadership

  • A comprehensive assessment plan is developed and provided that measures academic and non-academic outcomes.
  • Data-based decision rules are developed and provided for academic and non-academic areas and are consistent across buildings.
  • A written data-based decision-making process is developed and provided for analyzing and using assessment data in academic and non-academic areas.
  • An integrated data system is provided that allows users to document and access individual student-level academic and non-academic data that are represented visually or graphically.
  • Fidelity and progress monitoring data in academic and non-academic areas are analyzed in a timely manner and used to inform instructional supports based on need and the effectiveness of instruction.
Learn more about shared leadership in the context of Ohio's Integrated Multi-Tiered System of Supports.

Professional Capacity

  • All staff understand and apply the benefits of using academic and non-academic data to inform decisions regarding student needs.
  • All staff understand and apply data literacy and integrated data-based decision-making.
  • Staff are trained in and can articulate the benefits and limitations of the assessments being used.
  • Staff are trained in administering assessments, ensuring that procedures are followed as designed.
  • Staff are trained in the collection, interpretation, and use of assessment data.
Learn more about professional capacity in the context of Ohio's Integrated Multi-Tiered System of Supports.

Communication and Collaboration

  • Staff collaborate frequently.
  • Staff have bidirectional communication with leadership.
  • General education teachers, special education teachers, and specialized support staff share responsibility for student progress and outcomes in both academic and non-academic areas. 
  • Staff regularly share data that is meaningful, user-friendly, and accessible with families and caregivers.
  • Staff involve students as partners in decision-making in academic and non-academic areas.
  • Staff involve families and caregivers as partners in decision-making in academic and non-academic areas.
Learn more about communication and collaboration in the context of Ohio's Integrated Multi-Tiered System of Supports.

Resources

Last Modified: 8/22/2025 1:41:23 PM