Data-Driven Decision Making and the RTI Process

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Data-Driven Decision Making and the RTI Process

• Kathleen Maxwell
• Instructional Research Data Analysis
• Capital Region BOCES

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IDEA 2004 Changes Procedures for Evaluating a
Child Suspected of Having a Learning Disability

• An LEA shall not be required to take into
  consideration whether a child has a severe
  discrepancy between achievement and intellectual
  ability in oral expression, listening
  comprehension, written expression, basic reading
  skill, reading comprehension, mathematical
  calculation, or mathematical reasoning.
• An LEA may use a process that determines if the
  child responds to scientific, research-based
  intervention as a part of the evaluation
  procedures.

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Rationale for RTI

• an at-risk childs initial response to
  remedial intervention can be a reasonably good
  barometer of whether that child will be readily
  remediated or difficult to remediate, andthe
  profile developed from this and subsequent work
  with the child can aid as a first-cut
  diagnostic in determining whether his or her
  reading difficulties are caused primarily by
  experiential and instructional deficits or by
  cognitive deficits of biological origin.

(Vellutino, Scanlon, Small, Fanuele, 2003)
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RTI has three core concepts

• Application of scientific, research-based
  interventions in general education
• 2) Measurement of a students response to these
  interventions and
• 3) Use of the RTI data to inform instruction.

National Joint Committee on Learning
Disabilities, 2005
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How are Data Used in RTI?

• School staff conduct universal screening of
  academics behavior.
• Continuous progress monitoring of students
  performance occurs, pinpointing students
  specific difficulties.
• School staff use progress-monitoring data to
  determine interventions effectiveness and to
  make any modifications as needed.

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Potential Benefits of RTI

• Earlier identification of students by means of a
  problem-solving approach rather than by an
  ability-achievement discrepancy formula
• Reduction in the number of students referred for
  special ed. and related services
• Reduction in the over-identification of minority
  students
• Provision of more instructionally relevant data
  than traditional means of identification

NJCLD, 2005
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The RTI Process
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Scientific Method
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RTI/Problem-Solving Models
(Tilley, Reschly, Grimes, 1999)
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Data Sources in theThree-Tiered RTI Model

• (from NJCLD, 2005)

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• Tier 1 Preventive RTI
• Universal Screening
• Ongoing Progress Monitoring/CBA
• Differentiated Instruction Based on Assessment

(Gresham, 2005 NJCLD, 2005)
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• Tier 1 Preventive RTI
• Universal Screening
• Ongoing Progress Monitoring/CBA
• Differentiated Instruction Based on Assessment

• Tier 2 Reactive RTI
• CBA Who still needs additional assistance?
• Frequent Progress Monitoring
• Assessment of Intervention Implementation

(Gresham, 2005 NJCLD, 2005)
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Major Characteristics of a Curriculum-Based
Measurement Model

• Direct measurement observation of specific
  student skills and behavior
• Repeated measurement monitoring students
  anywhere from 3X/week to 3X/year.
• Time series analysis graphing the direct,
  repeated measurement data, recording
  instructional interventions on the graph,
  looking at the students response to instruction.

(Wedl, 2005)
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• Tier 1 Preventive RTI
• Universal Screening
• Ongoing Progress Monitoring/CBA
• Differentiated Instruction Based on Assessment

• Tier 2 Reactive RTI
• CBA Who still needs additional assistance?
• Frequent Progress Monitoring
• Assessment of Intervention Implementation

• Tier 3 SPED Eligibility RTI
• Evaluation using multiple measures
• Additional data, as needed

(Gresham, 2005 NJCLD, 2005)
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• Tier 1 Preventive RTI
• Universal Screening
• Ongoing Progress Monitoring/CBA
• Differentiated Instruction Based on Assessment

• Tier 2 Reactive RTI
• CBA Who still needs additional assistance?
• Frequent Progress Monitoring
• Assessment of Intervention Implementation

• Tier 3 SPED Eligibility RTI
• Evaluation using multiple measures
• Additional data, as needed

SPED Identification
(Gresham, 2005 NJCLD, 2005)
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Educators Must Develop New Skills to Use Data
Effectively

• General education teachers will need to compile
  relevant assessment data through continuous
  progress monitoring and respond appropriately to
  the findings.
• Special education and related services personnel
  need to help design, interpret, and assess data
  as well as suggest instructional approaches.

(NJCLD, 2005, p. 9)
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Questions to Consider

• Which measures are most appropriate to identify
  nonresponders at different points of reading
  development, and what criteria determine movement
  between tiers?
• Is achievement determined by classroom, local,
  state, or national norms, and/or by reaching
  benchmarks?
• How do you define expected achievement level, and
  what is acceptable progress?
• At what point will a student be deemed
  nonresponsive to intervention?
• How is the quality of the intervention monitored?