1. MOY Data Analysis Increasing Achievement and Growth Grant NW BOCES
February 6, 2014

2. Objectives for today
The RLC will understand DIBELS Next growth data (BOY to MOY) for the entire BOCES population of K-3 students with disabilities
Each literacy lead will understand how to do a similar evaluation of the data for their school/district
Literacy leads will utilize the data analysis methods presented in this webinar to help develop next steps for students with disabilities in their school/districts

3. Analysis of growth
Purpose: determine whether the instructional programming for a district, school, class, program and/or individual student has changed or maintained the trajectory of growth
DIBELS is a “stoplight” assessment – lets us know whether a student is at risk of “reading failure” based on research
Example of change – student has moved from yellow to red
Example of maintain – student has stayed at the same level of risk

4. Percentiles
A percentile or percentile rank in DIBELS is a description of how a student scored compared to a national sample of about 30,000 students
For DIBELS, percentiles were last published for the school year.
Amplify percentiles are local (i.e. compared only to your school)

5. Percentile rank example
If a kindergartener at the beginning of the year has a composite score of 10, they are in the 25th percentile. That means that 25% of kindergarteners in DIBELS sample group scored at or below where this student scored
DIBELS places their benchmark (green) score at or near the 40th percentile

6. Percentile growth
If a student is making typical growth, they will stay at the same percentile ranking
If a student is making less than typical growth, their percentile ranking will drop
If a student is making more than typical growth, their percentile ranking will increase
If a student’s percentile ranking changes enough, then their category of risk will change

8. Questions for our data
Are the changes we are implementing through the grant making a difference for students?
Which students are making adequate growth?
Which students need changes to their systems of support in order to make adequate growth?

9. Our Data - Process Created cohort group
Pulled BOY and MOY data from Amplify for cohort group
Analyzed change from BOY to MOY based on risk category
Analyzed change from BOY to MOY based on percentile ranking
Disaggregated by disability
I started by creating a “cohort group” of students who were on IEPs during BOY benchmarking (based on data pulled from IEP system) – this group includes any students who were exited between Sept. 30 and January 1.
Looking for growth among this group – sometimes this means that they students will have been exited due to their performance, so we want to be sure to include these students as a success.

10. Our Data - BOY At/Above Below Well Below Total BOY Total BOY %
Well Below
Total BOY
Total BOY %
Primary Disability
BOY
BOY %
01 I.D. or S.L.I.C. 1
50.00%
0.00% 2
100.00%
03 S.E.D. or Emotional
33.33%
16.67% 3 6
04 S.L.D. 4
8.51% 5
10.64% 38
80.85% 47
05 H.I. incl. Deafness or H.D.
66.67%
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
3.70% 16
59.26% 27
08 Speech/Language 21
27.27% 18
23.38%
49.35% 77
10 Multiple
11 D.D. or Preschooler
9.09%
13.64% 17
77.27% 22
13 A.S.D. or Autism
44.44%
22.22% 9
16 Other Health Impairment
75.00%
25.00%
Grand Total 46
22.66% 33
16.26%
124
61.08%
203

11. Our Data - MOY At/Above Below Well Below Total MOY Total MOY %
Below
Well Below
Total MOY
Total MOY %
Primary Disability
MOY
MOY %
01 I.D. or S.L.I.C. 1
33.33%
0.00% 2
66.67% 3
100.00%
03 S.E.D. or Emotional
60.00%
40.00% 5
04 S.L.D.
10.64% 37
78.72% 47
05 H.I. incl. Deafness or H.D.
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
11.11% 14
51.85% 27
08 Speech/Language 29
38.67% 18
24.00% 28
37.33% 75
10 Multiple
11 D.D. or Preschooler
23.81%
14.29% 13
61.90% 21
13 A.S.D. or Autism 4
44.44% 9
16 Other Health Impairment
50.00%
Grand Total 59
29.80% 36
18.18%
103
52.02%
198

12. Benchmark Strategic Intensive Our Data – BOY to MOY BOY: 22.66% (n=46)

13. The vast majority (71%) of kids stayed in the same risk level on DIBELS.
21% showed a decrease in risk (good!)
8% showed an increase in risk (bad!)
Which of these groups do we need to look at on an individual basis and make changes to their systems of support?

14. Of the strategic and intensive students who stayed in the same range from BOY to MOY, here are their changes in percentile:
36% increased percentile ranking (significant is more than 10 percentile points) – good!
36% stayed the same – ok, but not good enough to catch up!
28% decreased (bad!)
Which of these groups do we need to examine on an individual basis to make changes to their systems of support?

15. This chart shows the students who were at or above benchmark at both BOY and MOY. The same information about change in percentiles applies to them, although it’s probably ok if they stay at the same percentile because they are making typical growth.
Which students do we need to look at on an individual basis here? Which would you add to a “watch” list to make sure that they stay at or above benchmark?

16. The majority of the students in our cohort group are either identified as having SLD (n=47)or a Speech/Language disability (n=75). The SLD category is a particularly difficult one with regard to reading achievement because their low achievement was likely why they were identified in the first place! If we can push these students’ growth, then we will unquestionably have been successful with our work. Again, the vast majority of students stayed at the same level of risk from BOY to MOY.

17. Our Data - BOY At/Above Below Well Below Total BOY Total BOY %
Well Below
Total BOY
Total BOY %
Primary Disability
BOY
BOY %
01 I.D. or S.L.I.C. 1
50.00%
0.00% 2
100.00%
03 S.E.D. or Emotional
33.33%
16.67% 3 6
04 S.L.D. 4
8.51% 5
10.64% 38
80.85% 47
05 H.I. incl. Deafness or H.D.
66.67%
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
3.70% 16
59.26% 27
08 Speech/Language 21
27.27% 18
23.38%
49.35% 77
10 Multiple
11 D.D. or Preschooler
9.09%
13.64% 17
77.27% 22
13 A.S.D. or Autism
44.44%
22.22% 9
16 Other Health Impairment
75.00%
25.00%
Grand Total 46
22.66% 33
16.26%
124
61.08%
203

18. Our Data - MOY
At/Above
Below
Well Below
Total MOY
Total MOY %
Primary Disability
MOY
MOY %
01 I.D. or S.L.I.C. 1
33.33%
0.00% 2
66.67% 3
100.00%
03 S.E.D. or Emotional
60.00%
40.00% 5
04 S.L.D.
10.64% 37
78.72% 47
05 H.I. incl. Deafness or H.D.
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
11.11% 14
51.85% 27
08 Speech/Language 29
38.67% 18
24.00% 28
37.33% 75
10 Multiple
11 D.D. or Preschooler
23.81%
14.29% 13
61.90% 21
13 A.S.D. or Autism 4
44.44% 9
16 Other Health Impairment
50.00%
Grand Total 59
29.80% 36
18.18%
103
52.02%
198
If we go back to this data, we see that the VAST majority of these students are in the intensive range and didn’t move out of it from fall to winter.

19. If we look at the change in percentile for these students, the number of students per category is low (which means we should be careful with how we interpret this data, but the trends are still clear. Most students either stayed at the same percentile (ok – but not enough to catch up) *caveat: how many stayed at the 1st percentile?* or increased (really good!)
Which students do we need to look at more closely in order to improve their systems of support?

20. Our Data - BOY
At/Above
Below
Well Below
Total BOY
Total BOY %
Primary Disability
BOY
BOY %
01 I.D. or S.L.I.C. 1
50.00%
0.00% 2
100.00%
03 S.E.D. or Emotional
33.33%
16.67% 3 6
04 S.L.D. 4
8.51% 5
10.64% 38
80.85% 47
05 H.I. incl. Deafness or H.D.
66.67%
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
3.70% 16
59.26% 27
08 Speech/Language 21
27.27% 18
23.38%
49.35% 77
10 Multiple
11 D.D. or Preschooler
9.09%
13.64% 17
77.27% 22
13 A.S.D. or Autism
44.44%
22.22% 9
16 Other Health Impairment
75.00%
25.00%
Grand Total 46
22.66% 33
16.26%
124
61.08%
203
Our largest group of students (n=75) are identified as having a speech/language disability. We know that by 3rd grade (and beyond) many of these same students end up being relabeled as having an SLD. Because of the strong connections between speech, language, and reading, it is our hypothesis that if students who are identified with a speech/language disability early on receive the intervention they need, then they will exit special education rather than being relabeled as SLD. One of our measures of success in this grant is whether or not we see a reduction in this type of reclassification.

21. Our Data - MOY
At/Above
Below
Well Below
Total MOY
Total MOY %
Primary Disability
MOY
MOY %
01 I.D. or S.L.I.C. 1
33.33%
0.00% 2
66.67% 3
100.00%
03 S.E.D. or Emotional
60.00%
40.00% 5
04 S.L.D.
10.64% 37
78.72% 47
05 H.I. incl. Deafness or H.D.
06 V.I. incl. Blindness or V.D.
07 Physical 10
37.04%
11.11% 14
51.85% 27
08 Speech/Language 29
38.67% 18
24.00% 28
37.33% 75
10 Multiple
11 D.D. or Preschooler
23.81%
14.29% 13
61.90% 21
13 A.S.D. or Autism 4
44.44% 9
16 Other Health Impairment
50.00%
Grand Total 59
29.80% 36
18.18%
103
52.02%
198
For these students, the data looks a bit better than for the SLD students (good news!)

22. Again, the vast majority of students either had the same level of risk (ok, but not good enough) or a reduced level of risk (good!) from BOY to MOY. And again, which of these groups of students should have their systems of support re-evaluated?

23. Students with a speech/language disability who scored below grade level. This data is not quite as useful as in some other cases, because the number of students that we are looking at is so small. However, it is valuable to look at this information on a per-student basis to determine whether or not they made adequate progress to catch up.

24. Next Steps/Considerations
What does your school’s data tell you?
What are the big picture patterns?
Which students need to be looked at individually?
What other patterns could you look for in the data?
What does it mean when a student is not making typical growth? (hint: think about their core instruction!)
When a student is making accelerated growth, how can you replicate that success?
Possible patterns – interventions, other?

25. Reflect What did you learn about analyzing student data today?
What will be valuable to use with your staff?
What is the best presentation method so that staff understand and have buy-in to what you share with them?
How will you use what you learned today in your school/district?
What questions do you want to answer with your data?
What are you wondering about your data?