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Data Based Decision Making Using Progress Monitoring Data.

Date post: 05-Jan-2016
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Data Based Decision Making Using Progress Monitoring Data
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Page 1: Data Based Decision Making Using Progress Monitoring Data.

Data Based Decision Making

Using Progress Monitoring Data

Page 2: Data Based Decision Making Using Progress Monitoring Data.

Progress MonitoringIndividual or class-wide assessment used

to:

Demonstrate student/class rate of improvement in the curriculum & to identify students whose growth is inadequate

Aid teachers in determining when instructional modifications may be necessary

PM schedule may vary by student/class from weekly to monthly, based on perceived need

Page 3: Data Based Decision Making Using Progress Monitoring Data.

Why Is Progress Monitoring Important?

Research has demonstrated:

Students achieve more

Teacher decision making improves

Students tend to be more aware of their performance

(Fuchs, Deno, Mirkin, 1984; L.S. Fuchs, Fuchs, Hamlett, & Ferguson, 1992; Fuchs, Fuchs, Hamlett, & Stecker, 1991;

Stecker, Fuchs, & Fuchs, 2005)

Page 4: Data Based Decision Making Using Progress Monitoring Data.

Progress Monitoring Mantra

The more data points we have = the greater our ability to determine students rate of progress with confidence

The sooner we have them = the greater our ability to determine the potential need to change the reading intervention

Page 5: Data Based Decision Making Using Progress Monitoring Data.

Progress Monitoring Principles

1. Frequency of PM is related to severity of reading problem

2. Must balance what is ideal with what is feasible

3. The less frequently we assess, the higher quality our information should be

Page 6: Data Based Decision Making Using Progress Monitoring Data.

PM Best Practice Minimum of 6 data points

This is based on PM procedures where students are administered single passage

Accuracy of decisions about student’s rate of progress increases with each additional data point

Page 7: Data Based Decision Making Using Progress Monitoring Data.

Frequency # of Passages Quality; Timeliness

1 time per week 1 passage Defensible;Timely Decisions

Every 2 weeks 1 passage Moderately Defensible; Less Timely

Every 4 weeks 3 passages Moderately Defensible;

Much less timely

Decision-Making for At-Risk

Readers

Page 8: Data Based Decision Making Using Progress Monitoring Data.

Examining Student Response to Intervention

Page 9: Data Based Decision Making Using Progress Monitoring Data.

Definitions Goal: end of year expectation based on ROI

equal to or better than that of student performing at target

Aim Line: runs between beginning of year benchmark and and goal

Trend Line: indicates student’s actual progress based on weekly monitoring

Decision Rule: involves considering trendline in relation to aim line

Page 10: Data Based Decision Making Using Progress Monitoring Data.

Definitions F.I.T.T. principle (for adjusting

intervention) Frequency (of delivery)

Intensity (due to smaller group size)

Time (per session)

Type (of intervention)

Page 11: Data Based Decision Making Using Progress Monitoring Data.

Decision-Making RulesExamine the slope of the trend line in

relation to that of the aim line

Trend line is well above aim line, consider the following: Is student on track for benchmark; if so, consider

whether student should return to Tier one Student is responding well but not on track for

benchmark; consider continuing in current intervention

Trend line is at or somewhat above aim line: Consider intervention change by applying FITT

principle

Page 12: Data Based Decision Making Using Progress Monitoring Data.

Decision-Making Rules (cont’d)

Slope of trend line is less steep than that of aimline: Intervention change is needed (apply FITT

principle) Consider whether formal problem solving is

required (i.e. IDM)


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