Response-to-intervention multitiered support model with universal screening and progress monitoring as its assessment components¶

Theory · All theories
Evidence · 6 claims (6 for) · 1 study (1 associational), q3 · 0 of 1 report an effect size · 6 claims rest on one study

Description¶

The article describes the response-to-intervention (RTI) model as a multitiered framework for student support aimed at early identification of struggling students, typically with three tiers: Tier 3 is the most intense intervention for an estimated 5-10% of students, Tier 2 provides targeted less intensive intervention for 5-15%, and Tier 1 is core instruction for 80-90%. Within this model, "Universal screening identifies at-risk students in need of intervention, whereas progress monitoring tracks the learning progress of students who are already identified as at-risk for learning difficulty." The article uses this framework to motivate establishing technically sound screening benchmarks.

Design Implications¶

Context¶

Requirements¶

• A technically sound assessment system; the article states an RTI model cannot sustain itself if cut scores lack adequate classification accuracy

Constraints¶

• The article distinguishes universal screening cut scores from Read by Grade 3 cut scores, which are tied to state proficiency standards and correspond to much higher percentiles

Target Learners¶

• K-12 students in reading and mathematics, particularly those at risk of severe learning difficulties

Target Learning Objectives¶

• Early identification of students at risk for academic difficulty and appropriate tiered intervention placement

Claims¶

• Map Growth 30Th Percentile Screening Cut Scores [+M]
• Updated 2025 MAP Growth screening thresholds are set at the 35th percentile with adjustments for the Enhanced Item-Selection Algorithm [+W]
• MAP Growth state-test correlations exceed 0.8 for most Grade 3-8 concurrent indices, with mathematics correlations higher than reading [+W]
• Cross-validation in an independent Indiana sample was consistent with the primary-sample classification accuracy results [+W]
• Recommended MAP Growth screening cut scores yield sensitivity, specificity, and lower-bound AUC of at least 0.8 for most grades and terms [+W]
• Classification accuracy of the screening cut scores is lower for Grades K-2 than Grades 3-8, attributed to a 12-36 month lapse between MAP Growth and criterion measures [+W]

Related Theories¶

• Three-level RTI prevention model for identifying learning disabilities
• Three-tiered prevention model of behavioral supports

Examples¶

• Administer universal early literacy screening three times per year plus dyslexia-characteristics screening in K–2
• Progress Monitoring
• Curriculum Based Measurement
• Use early-session timing signals, interpreted relative to proficiency, to identify students needing adaptive support
• Ohio’s Dyslexia Guidebook
• Screen for and monitor children at risk of nonresponse to universal SWPBIS and target nonresponders for more intensive tiered interventions
• Assess accuracy and strategy use on one-half fraction items at the end of Grades 4 and 5 to identify students needing additional fraction support
• Use two-stage gated screening: an early reading screen followed by several weeks of progress monitoring before confirming at-risk status

Key Sources¶

• He, W., & Meyer, P. (2021). MAP Growth universal screening benchmarks: Establishing MAP Growth as an effective universal screener. NWEA. https://www.nwea.org