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Special Education teacher progress monitoring refresher training Dan Hyson HVED Data Management Coordinator January 21, 2013

Special Education teacher progress monitoring refresher training

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Special Education teacher progress monitoring refresher training. Dan Hyson HVED Data Management Coordinator January 21, 2013. Agenda. Review agenda What else were you hoping I would address when you heard I was presenting? - PowerPoint PPT Presentation

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Page 1: Special Education teacher progress monitoring refresher training

Special Education teacher progress monitoring refresher training

Dan Hyson

HVED Data Management Coordinator

January 21, 2013

Page 2: Special Education teacher progress monitoring refresher training

Agenda

1. Review agenda

2. What else were you hoping I would address when you heard I was presenting?

3. What is the place of progress monitoring (PM) data within a comprehensive assessment system?

4. How can Special Education (SpEd) teachers use technology tools to record and view PM data?

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

6. How can SpEd teachers use PM data to help determine whether students are eligible for SpEd and/or identify whether students are meeting SpEd goals?

Page 3: Special Education teacher progress monitoring refresher training

2. What else were you hoping I would address when you heard I was presenting?

Page 4: Special Education teacher progress monitoring refresher training

3. What is the place of progress monitoring within an assessment system?

Functions of assessment

Examples Purpose How often? With whom?

SUMMATIVE ASSESSMENT

MCA-II How did we do? (aka “autopsy”)

1x/year All students

FORMATIVE ASSESSMENT

1. Benchmark screening

NWEA MAP, AIMSweb

Are we meeting the needs of most students? Which are at-risk?

Up to 3x/year (Fall, Winter, Spring)

All students

2. Progress monitoring

AIMSweb

Chart Dog

How are students responding to interventions? Are they making growth?

1x/month (Strategic Monitoring); 1x/week-2 weeks (Progress Monitoring)

Students at-risk based on summative and benchmark screening assessments; Students receiving Special Ed

3. Diagnostic assessment

NWEA MAP, AIMSweb, other standardized assessments, common teacher-made assessments

What is getting in the way of some students making growth?

As needed General and Special Ed students not responding to intervention based on progress monitoring

Page 5: Special Education teacher progress monitoring refresher training

4. How can Special Education (SpEd) teachers use technology tools to record and

view progress monitoring (PM) data?

• In reading and math– AIMSweb– Chart Dog -

http://www.jimwrightonline.com/php/chartdog_2_0/chartdog.php

• For behavior– Chart Dog– AIMSweb Behavior

Page 6: Special Education teacher progress monitoring refresher training

Using AIMSweb R-CBM Oral Reading Fluency (ORF) measure to predict performance on MCA-II

Reading testR-CBM ORF is…• Nationally-normed,

standardized test of how many words student can read correctly in 1 minute

• Moderately correlated with MCA-II Reading test scores (correlation = .5 to .7)

• Easy to administer• Sensitive to change, even

when given as weekly progress monitoring tool

R-CBM ORF is NOT…• The only component of

reading we should be concerned about

• The only measure of reading you should administer, especially if students identified as at-risk based on ORF

Page 7: Special Education teacher progress monitoring refresher training

600

800

1000

1200

1400

1600

1800

2000

2200

0 50 100 150 200 250 300

ORF Grade 3 Spring

MC

A S

cale

Score

Gra

de 3

Read

ing

Happy Surprises

Happy, But No Surprise

Unhappy, But No

Surprise

Unhappy Surprises

1420

107

Multi-Year Correlation between MCA and ORF (N = 2135)

Page 8: Special Education teacher progress monitoring refresher training

Sample screening data from AIMSweb Behavior

Page 9: Special Education teacher progress monitoring refresher training

Sample Action Plans from AIMSweb Behavior

Page 10: Special Education teacher progress monitoring refresher training

Sample PM from AIMSweb Behavior

Page 11: Special Education teacher progress monitoring refresher training

Sample PM from AIMSweb Behavior

Page 12: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

Page 13: Special Education teacher progress monitoring refresher training

Start By Abandoning Old Goals

• Student will perform spelling skills at a high 3rd grade level.

• Student will alphabetize words by the second letter with 80% accuracy.

• Student will read words from the Dolch Word List with 80% accuracy.

• Student will master basic multiplication facts with 80% accuracy.

• Student will increase reading skills by progressing through the reading program with 90% accuracy as determined by teacher-made fluency and comprehension probes by October 2013.

• Student will be a better reader.

• Student will read aloud with 80% accuracy and 80% comprehension.

• Student will make 1 year's gain in general reading from K-3.

• Students will read 1 story per week.

X

Page 14: Special Education teacher progress monitoring refresher training

Individualized Goal Setting Strategies

1. Determine the Present Level of Performance (PLOP) based on Survey-Level Assessment (SLA)

2. Know the Time Frame for the Goal (typically the “anniversary date”--1 year.

3. Determine the Level of Curriculum That Defines Success and Reduces the Gap

4. Define the Criterion for Acceptable Performance (CAP)

Page 15: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

• Using norms v. target scores v. growth rates to set goals– Local v. national norms

• Setting grade level v. instructional level v. goal level goals

Page 16: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

• If student near grade level, set goal at grade level and PM with grade level probes

Page 17: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

• If student far below grade level, set goal that is rigorous, yet reasonable– NOT at grade level BUT– NOT at instructional level either– At level that will significantly close gap to same

grade peers– PM in goal level material

• Can use Survey Level Assessment (SLA) to determine

Page 18: Special Education teacher progress monitoring refresher training

A SLA for Grade 6 Student to Write Individualized Goals

Present Level of Performance (PLOP)

Expected Level of Performance

Achievement Level of Average Students in Fall

PLOP in Grade 6

Median of Grade 6 Benchmark Scores

or

3 Individually Administered Grade 6 Passages

24 WRC

Page 19: Special Education teacher progress monitoring refresher training

A Survey Level Assessment to Write Individualized Goals

PLOP

Expected Level of Performance

Potential Goal (and PM) Material

Page 20: Special Education teacher progress monitoring refresher training

A Survey Level Assessment to Write Individualized Goals

Goal Material and CAP of 90 WRC

Page 21: Special Education teacher progress monitoring refresher training

WORDS = GRAPH OF EXPECTED RATE OF PROGRESS

AIM LINE Expected Rate of Progress to Significantly Reduce the Gap

Ginny will read aloud 95 WRC with 3 or fewer errors when given a randomly selected Grade 4 reading passage by June 1, 2013

Page 22: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

• “4 point decision rule”– Establish baseline– After establish baseline, collect at least 6

additional data points• If goal is to increase target skill or behavior

– 4 consecutive data points below student’s goal or aimline -> adjust intervention» May mean adding intervention, adding/changing

component of intervention, or even taking intervention away

– 4 consecutive data points above student’s goal or aimline -> adjust goal or adjust/discontinue support

Page 23: Special Education teacher progress monitoring refresher training

5. How can SpEd teachers use screening and PM data to set goals and monitor student progress toward those goals?

• If goal is to decrease target skill or behavior– 4 consecutive data points above student’s goal or

aimline -> adjust intervention» May mean adding intervention, adding/changing

component of intervention, or even taking intervention away

– 4 consecutive data points below student’s goal or aimline -> adjust goal or adjust/discontinue support

Page 24: Special Education teacher progress monitoring refresher training

Assessing Response to Intervention4 point decision rule

10

20

30

40

Dec.Scores

Feb.Scores

Jan.Scores

M archScores

AprilScores

MayScores

JuneScores

60

50

Ora

l R

ead

ing

Flu

ency

Aimline

Student Identified as Needing Intensive Support

Modify intervention

Modify intervention

Determine resources needed to sustain progress (Gen Ed, SPED, Title, EA assistance, etc.)

Individualized intervention initiated

(Florence & Potter)

Page 25: Special Education teacher progress monitoring refresher training

Cautions when using 4-point decision rule

• Experts suggest that need to collect at least 10 data points (maybe as many as 20) before making decision– Some even suggest collecting 3 data points each time

PM to minimize error• Careful not to pay too much attention to

individual data points since more likely to be affected by sources of error (e.g., student motivation, examiner differences, difficulty of particular passages)

• Critical to do regular refresher trainings and fidelity checks with examiners to ensure don’t drift from original training

Page 26: Special Education teacher progress monitoring refresher training

6. How can SpEd teachers use PM data to help determine whether students are eligible for SpEd and/or identify

whether students are meeting SpEd goals?

Special Education Eligibility Decisions

• If and when your district gets to point of using RtI SLD eligibility criteria – Need 12 data points over at least 7 weeks– Data must show student not responding to at least 2

research-based interventions• Inadequate growth rate

– Student’s achievement level must be below the national or state 5th percentile on most recent standardized measures related to referral concern

Page 27: Special Education teacher progress monitoring refresher training

Contact information

Dan Hyson

Hiawatha Valley Education District

507-452-1200, ext. 119

[email protected]