Data-Based Decision-Making

Data-Based Decision-Making

Data-based decision-making is a cornerstone of an MTSS model. To support MTSS's fluid process, reliable and valid sources of screening, diagnostic, progress monitoring, and outcome data are utilized to inform instruction and intervention relative to the academic, social-emotional and behavioral needs of students. Data-based decision-making occurs within a dynamic, problem-solving process. Practitioners examine learning rate (growth) over time and design and deliver instruction to meet changing student needs within and across all levels of the system.

Assessment allows us to identify students as early as possible who are at-risk or who may already be experiencing difficulties and need supplemental instruction and intervention, as well as those students who need enrichment. Assessment allows us to monitor students' progress during the year to determine whether students are making adequate growth toward proficiency and generalization of critical skills and to identify students who may be falling behind. Assessment informs instructional design and delivery in order to meet the most critical needs of groups or individual students. Finally, assessment helps us determine whether the instruction and intervention will enable all students to learn a year’s worth of content in an instructional year or if for students who are behind, there will be both annual and catch-up (gap is closing) growth (within a reasonable period of time).


Data-Based Decision-Making Team Discussion Items

  1. Describe how systems or tools assist educators with user-friendly access to student and classroom performance data and interpretative reports.

  2. Describe the extent to which the design of the building schedule (from year to year) supports opportunities for ongoing “data examination.”

  3. Attach sample meeting notes (with student names redacted) that verify the establishment of grade level goal setting, identification of core instructional strategies matched to student needs/goals, how grade level goal attainment is monitored, and indicators of met goals.

  4. Based upon the disaggregated performance of diverse learners including students with disabilities, English Learners, and/or students who are economically disadvantaged, describe changes that have led to improved core and supplemental instruction and have accelerated the growth of diverse learners.

  5. Identify the progress monitoring measures you use and how often.

  6. Describe the process for monitoring the alignment and effectiveness of instructional strategy implementation across the tiers.

  7. Indicate what would happen if a student’s performance continued to fall below grade level expectations after one round of supplemental instruction/intervention (i.e., 7-10 weeks recommended to assess trend in response)

  8. Identify specific recommendations that have enhanced the efficiency and effectiveness of the data-teaming and instructional matching process and their contributions within it.

  9. Identify assessment measures that you use to inform “root cause” and the design and implementation of instruction/intervention.

  10. Review professional development that has served to advance skills across all educators relative to the areas of data-analysis and instructional matching in each tier.



MTSS: Enhancing Team-Based Decision-Making Within Effective Tiered Systems

RtI/MTSS Part II: Data-Based Decision Making & Instruction/Intervention Implementation

Integrating Tiered Data-based Decision Making to Address Essential Questions in an RtI Process - Overview of Tiered Data-Based Decision-Making

Data-Based Problem Solving and Decision-Making



RTI for English Language Learners: Appropriately Using Screening and Progress-Monitoring Tools to Improve Instructional Outcomes

Implementing RTI with English Language Learners (ELLs)

RTI in Linguistically Diverse Schools: How to Address Challenges

Tools to Support Intensive Intervention Data Meetings

Example Diagnostic Tools

RTI Action Network Checklist and Forms

Practice Profile for the Essential Components of a Multi-Tiered System of Support (MTSS) Data-Based Problem-Solving and Decision-Making

DBI Implementation Rubric and Interview