Analyzing Your Universal Screening Data

1. Analyzing Your Universal Screening Data Tom Jenkins, Ed.D. Educational Consultation Services, LLC Wilmington, NC

2. Building Your Infrastructure • Formative evaluation process • Informed by data • Highly involved school-based leadership team (SBLT) • School-based coach • Provide Technical Assistance • Interpretation and Use of Data • Facilitates regular data meetings for building and grade levels

3. Formative Evaluation Component of Infrastructure What we need: Screening system for identifying students at risk Diagnostic assessment tools for identifying specific needs of students identified by screening Systematic, explicit, research based instructional strategies – differentiated instruction Progress monitoring plan Evaluation of whether instruction is effective

4. Data For Each Tier - Where Do They Come From? Tier 1: Universal Screening, accountability assessments, grades, classroom assessments, referral patterns, discipline referrals Tier 2: Universal Screening - Group Level Diagnostics (maybe), systematic progress monitoring, formative assessment large-scale assessment data and classroom assessment Tier 3: Universal Screenings, Individual Diagnostics, intensive and systematic progress monitoring, formative assessment, other informal assessments

5. Data For Each Tier – Where Do They Come From? Results Monitoring Addl. Diagnostic Assessment Instruction Screen All Students Individualized Intensive Individual Diagnostic Intensive 1-5% weekly Small Group Intervention By skill Supplemental 5-10% Standard Protocol Behavior Academics 2 times/month Core Bench- Mark Assessment Annual Testing Monthly Screening None Continue With Core Instruction with differentiation Grades Classroom Assessments Yearly Assessments 80-90% Step 2 Step 3 Step 4 Step 1

6. Tier I - Core/Benchmark • Universal Screening • Academics: Screen all students, begin in kindergarten; 3 times per year with appropriate early literacy and math measures • More intense instruction and monitoring within classroom for students below cut scores • See worksheet

7. Cut Score Worksheet • Step One: Put all student scores on the university screening measure on a histogram type chart. • Step Two: Calculate typical Growth Rate of specific skills. Three formulas can be used here. • EOYBM – BOYBM / 36 weeks = GR • Or • EOYBM – MOYBM / 18 weeks = GR • Or • MOYBM – BOYBM / 18 weeks = GR • Step Three: Determine the Targeted Growth Rate for students. Two formulas can be used here depending on the desired amount of ambitiousness. GR * 1.5 = TGR • Or GR * 2.0 = TGR

8. Cut Score Worksheet • Step Four: Calculate the Growth Goal for the instructional period. • TGR * NWI (18 or 36) = GG • Step Five: Calculate the Cut Score for determination of level of instruction. Two formulas can be used here depending on the length of the instructional period used in step four. MOYBM – GG = CS • Or EOYBM – GG = CS • Step Six: Using the Cut Score place a line of demarcation on the histogram created in step one. Any students above the Cut Score should obtain the GG via Core instruction. Any students below the Cut Score may need Strategic instruction to obtain the TGR and GG. Students in need of Intensive instruction should be identified using progress monitoring data during Strategic instruction implementation. Progress monitoring within all three tiers allows for students movement between the tiers during the instructional period.

9. Cut Score Worksheet Activity • Knowing that your MOYBM is 40 and your BOYBM is 20 what would be the cut score using a accelerator of 1.5? • BOYBM = 20 • MOYBM = 40 • 18 weeks of instruction/intervention • Accelerator of 1.5

10. Universal Screening ResultsFidelity Check: Are you doing the right thing? • Assess success of instructional program • Percent of students at or above benchmarks • If necessary, examine curriculum, instruction, or both • Identify students below benchmarks • Interventions within general education classroom • Assess progress and consider need for more intensive interventions

11. Decision Rules: What is a “Good” Response to Intervention? Positive Response Gap is closing Can extrapolate point at which target student(s) will “come in range” of target--even if this is long range Level of “risk” lowers over time Questionable Response Rate at which gap is widening slows considerably, but gap is still widening Gap stops widening but closure does not occur Poor Response Gap continues to widen with no change in rate.

12. Positive Response to Intervention Expected Trajectory Performance Observed Trajectory Time

13. Decision Rules: Linking RtI to Intervention Decisions Positive Continue intervention with current goal Continue intervention with goal increased Fade intervention to determine if student(s) have acquired functional independence.

14. Decision Rules: What is a “Questionable” Response to Intervention? Positive Response Gap is closing Can extrapolate point at which target student(s) will “come in range” of target--even if this is long range Questionable Response Rate at which gap is widening slows considerably, but gap is still widening Gap stops widening but closure does not occur Level of “risk” remains the same over time Poor Response Gap continues to widen with no change in rate.

15. Questionable Response to Intervention Expected Trajectory Performance Observed Trajectory Time

16. Decision Rules: Linking RtI to Intervention Decisions Questionable Was intervention implemented as intended? If no - employ strategies to increase implementation integrity If yes - Increase intensity of current intervention for a short period of time and assess impact. If rate improves, continue. If rate does not improve, return to problem solving.

17. Decision Rules: What is a “Poor” Response to Intervention? Positive Response Gap is closing Can extrapolate point at which target student(s) will “come in range” of target--even if this is long range Questionable Response Rate at which gap is widening slows considerably, but gap is still widening Gap stops widening but closure does not occur Poor Response Gap continues to widen with no change in rate. Level of “risk” worsens over time

18. Poor Response to Intervention Expected Trajectory Performance Observed Trajectory Time

19. Decision Rules: Linking RtI to Intervention Decisions Poor Was intervention implemented as intended? If no - employ strategies in increase implementation integrity If yes - Is intervention aligned with the verified hypothesis? (Intervention Design) Are there other hypotheses to consider? (Problem Analysis) Was the problem identified correctly? (Problem Identification)

20. I, We, You • Analyze the universal screening data provided to determine who needs strategic intervention, intensive intervention, and follow-up diagnostic assessments? • Use all three methods. • Which ones correlate the most?

21. Questions? • Dr. Tom Jenkins, Director • Educational Consultation Services, LLC • Wilmington, NC • (910) 367-7209 • Fanofstel@aol.com