2011-2012 data dialogues stan masters lenawee isd february 10, 2012
TRANSCRIPT
2011-2012 Data Dialogues
Stan MastersLenawee ISD
February 10, 2012
Data Driven Dialoguedi·a·logue or di·a·log n. Abbr. dial. 1. A conversation between two or more people. 2. An exchange of ideas or opinions: achieving constructive dialogue with all parties present. --di·a·logue v.
Deb Clancy, Washtenaw ISD, 2008
Ways of Talking
Normsof
Collaboration
Dialogue Discussion
Outcome:Deep
Understanding
Outcome:DecisionsThat Stick
Culture of Collaboration
Conversation
Deliberation
The Center for Adaptive Schools www.adaptiveschools.com
Listening Respectfully
Ear of the
Attentive
Listener
Rectitude of the Heart
Eye that is Unswerving
Third Grade Reading Readiness
New Cut Scores for ReadingGrade
3Grade
4Grade
5Grade
6Grade
7Grade
8MME
Advanced 364 478 565 653 760 853 1141
Proficient 324 419 521 619 721 818 1108
Partially Proficient
301 395 501 602 698 796 1081
9591
8084 85
78
52
8784 85 84
7982
63
78 78
61
75 7478
3537
3936 36
29 28
63 6466
64
56 5754
1714
2628
33
42
0
10
20
30
40
50
60
70
80
90
100
3rd 4th 5th 6th 7th 8th 11th 3rd 4th 5th 6th 7th 8th 11th 5th 8th 11th 6th 9th 11th
Math Reading Science Social Studies
Per
cen
t P
rofi
cien
tMEAP & MME 2010-11 Old & New Cut Scores
Michigan Old Michigan New
Using Local Data to Predict MEAP Success
• Review your local scores for your 2nd graders from 2010-2011
• Know that your target for Fall 2011 MEAP is 324
• Predict which students will pass using color-coding to indicate probability– Dark Green– Light Green– Yellow– Orange– Red
Elementary Principals Study 3rd Grade Reading Readiness
Last NameFirst
NameAIMSweb S-RCBM (90)
AIMSweb S-Maze (14)
Dolch % 100% of all 4 lists
DRA Independent Lev. (28)
Spelling Inven. %
70 12 100 14 86173 23 100 15 97212 30 100 17 10068 11 100 28 7373 9 100 28 87
How well do the existing local assessments predict success on the
Grade 3 Reading MEAP?
Predictions
Observations
Inferences
I predict . . .
I can count . . .
I believe that the data suggests . . . because, …
91% 89%
82% 81%
77%73% 71%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Percent Proficient
Percentage of Students Proficient on Local Assessment at EOY 2010 2nd Grade
and Proficient on Fall 2011 MEAP Reading
STAR Reading Grade Equivalency (2.8)
NWEA Reading Lexile (450)
NWEA Reading RIT Score (190)
DIBELS Oral Reading Fluency (90)
AIMSWeb MAZE (14)
DIBELS Next DORF Words Correct (87)
DRA (28)
MEAP Reading Domains
• Word Study– Use strategies to
construct meaning– Determine meaning of
words and phrases in context
• Narrative Text– Describe genre– Describe elements
of story– Describe use of literary
devices
• Informational Text– Describe genre– Describe use of text
features
• Comprehension– Retell main idea and
relevant details– Compare/contrast
relationships across texts– Apply knowledge across
subjects
Range of Student Scores onNWEA Reading Goal RIT Scores
Who Were Also Proficient on Fall 2011 Reading MEAP Strand "Green" Scores
Word Study 167-221Narrative Text 168-226
Informational Text 161-230Comprehension 167-227
Standard/Cluster Average
Michigan MA.4.N.ME.04.05 ( 4 ) 74%
Michigan MA.4.N.MR.04.07 ( 4 ) 43%
Michigan MA.4.N.ME.04.09 ( 4 ) 42%
Michigan MA.4.N.FL.04.11 ( 4 ) 29%
Michigan MA.4.N.FL.04.12 ( 4 ) 31%
Michigan MA.4.N.ME.04.15 ( 4 ) 43%
Michigan MA.4.N.MR.04.22 ( 4 ) 76%
Michigan MA.4.N.MR.04.19 ( 4 ) 10%
Sand Creek Ruth McGregor Data Dialogues
[We] have decided for now to meet with our teachers during
one of their grade level meeting times and hold the
monthly Data Meetings at that time. The smaller setting
worked great for our teachers – truly had good discussion
about data[…] They also seemed to be willing to doing a case study on one student
and bring that knowledge back to the table in a month.
Overall, it was great professional conversations.”
33
DORF Retell 65Grade 3 Comprehension 5
25
14
4th Grade Math PreTest
Morenci Elementary Electronic Student Data Profiles
Dolch Word List
3rd Tri
Star Test Grade Equivalent (GE) 3rd Tri
Star Test Independent
Reading Level 3rd Tri
AR Comp% 3rd
Tri
Math 3rd Tri % Post
Test
Addition Facts 3rd
Tri %
Subtraction Facts 3rd Tri
%
Multiplication Facts 3rd Tri %
Division Facts 3rd Tri
%
Writing 3rd Tri
Special Services
Recommendations
100 3.2 3.2 86 84 80 84 57 48 2 TITLE I
100 4.6 4.2 69 62 100 99 90 97 2 TITLE I PR
100 4.6 4.2 89 74 49 71 65 54 2
100 6.2 5.5 89 86 100 95 100 99 1 speech PR
100 3.1 3 79 86 99 100 100 92 2 TITLE I PR
Data Driven Decision Making in Early Literacy Teaching, Fall RDI Symposium
http://www.gomiem.org/files/handouts/g_1.pdf
• Current use of data used more to inform decision on intervention groups than to pace or change content
• Current collaboration time is limited• Collaboration with literacy expert had
most impact on teachers’ data use• The most effective schools allocated time
for structured teacher collaboration around data analysis and instructional planning
Assessment Calendars
Growth Models
Pre - Post Procedures• Administered before and after instruction• Look at the scores of individual students
to determine how many had higher post-test scores (Simple Growth Model)
• Compare the percentage to the threshold agreed upon by school/district
• Calculate the mean pre-test score and compare that with the mean post-test score (Simplified Value-Added Growth Model)
Source: Measurement Issues Inherent in Educator Evaluation, Presentation by the Michigan Assessment Consortium to the OEAA Educator Evaluation Best Practices Conference, April 15, 2011.
Sand Creek High SchoolPre-Test and Post-Test
Student Name
Life Skills Pre-test
Life Skills Post-test
Life Skills Growth
Life Skills Writing Pretest
Life Skills Writing Post
test
WritingGrowth
95 95 0 55 64 9
85 90 5 38 92 54
70 75 5 51 65 14
65 76 11 32 116 84
60 65 5 50 54 4
65 70 5 70 80 10
65 50 -15 103 130 27
Onsted Middle School,NWEA Growth, by Teacher, by Class PeriodStudent Name
Teacher Name
Class Period
10-11 NWEAFall Reading
Test RIT Score
10-11 NWEASpring Reading Test RIT Score
10-11 NWEATest RIT Score
Growth
10-11 NWEAFall Reading
Test Percentile
10-11 NWEASpring Reading Test Percentile
10-11 NWEATest Percentile
Growth
7 207 206 -1 15 18 3
2 207 219 12 10 40 30
2 212 202 -10 16 9 -7
1 207 219 12 15 50 35
2 210 213 3 14 25 11
2 220 216 -4 28 32 4
6 226 219 -7 53 50 -3
7 221 214 -7 41 35 -6
6 227 214 -13 56 35 -21
7 225 226 1 51 70 19
2 224 223 -1 36 52 16
6 231 202 -29 66 13 -53
6 232 213 -19 68 33 -35
“On Target” “Off Target”
College and Career Readiness
24
College Readiness Benchmark Scores
Early Indicators of College Readiness
EXPLORE PLAN ACT
English English Composition 13 15 18
Reading Social Sciences 15 17 21
Math Algebra 17 19 22
Science Biology 20 21 24
ACT SubjectArea Test College Course(s)
Predictions UsingEXPLORE to PLAN to ACT
• Uses scores in each subject area• Use color-coding to indicate probability
– Dark Green– Light Green– Yellow– Orange– Red
Reasonable Growth
• “On Target” • (met or exceeded CRB)
• “Nearly On Target” • (<2 points from CRB)
• “Off Target” • (>2 points from CRB)
Average Growth PointsBetween Tests
“On Target” (met or exceeded CRB)
“Nearly On Target” (<2 points from CRB)
“Off Target” (>2 points from CRB)
Test EXPLORE to PLAN
PLAN to ACT
EXPLORE to PLAN
PLAN to ACT
EXPLORE to PLAN
PLAN to ACT
English 2-3 2-3 3-4 1 3-4 1
Math 2-3 2-3 1-2 1-2 2-3 1-2
Reading 1-2 4-5 3-4 2-3 3-4 1-2
Science 1-2 2-3 1-2 2-3 2-3 1
Secondary Principals Study College and Career Readiness
10-11 PLAN Expected ACT 10-11 PLAN Expected ACT 10-11 PLAN Expected ACT 10-11 PLAN Expected ACT
Last name First name English English Reading Reading Mathematics Mathematics Science Science
16 16-20 17 17-21 14 14-18 16 16-20
17 17-21 17 17-21 20 21-25 21 22-26
22 23-27 20 21-25 21 22-26 21 22-26
16 16-20 14 14-18 16 16-20 20 21-25
10-11 Expected 10-11 Expected 10-11 Expected 10-11 Expected
EXPLORE PLAN EXPLORE PLAN EXPLORE PLAN EXPLORE PLAN
Last name First name English English Reading Reading Mathematics Mathematics Science Science
9 10-13 11 12-15 11 12-15 11 12-1514 15-18 12 13-16 14 15-18 15 16-1914 15-18 14 15-18 17 18-21 16 17-2013 14-17 12 13-16 15 16-19 16 17-2013 14-17 10 11-14 11 12-15 13 14-17
PLAN and EXPLORE Item Analysis
• Use test booklets from 11-12 testing– Order extra materials for
your staff (no cost)– Review items from the
booklet and the student responses
Identify students who need assistance with the testing formats
• Needs identified by students on PLAN test
– Writing– Reading– Math– Study Skills
• Identify students who need assistance with the testing formats
– Writings using ACT rubric– Analyzing data in graphs,
charts, and tables– Use of released items from
MDE– Use of release practice items
from ACT– Strategies for completing
timed portions of ACT – Close and critical reading
strategies from MS/HS Literacy Team
Dropout Prevention
Common Educational Risk FactorsSource: http://www.achieve.org/files/DataDrivenDropoutPreventionPolicy.pdf
• Attendance: High absences and tardies• Behavior: Poor classroom conduct,
office referrals, suspensions• Grades: Failing marks in academic courses• Achievement: Low test scores• Progress: Held back at any point,
falling behind in credits during high school
Middle School StudentsPersistently Scoring Below Proficient
110 students in Reading129 students in Math
Suggested Next Steps
• Move from scores to criteria around the scores
• Move from existing rubric/scoring guides to more concise rubric/scoring guides
• Move from individual analysis to team analysis
Common Assessments
A common assessment is an assessment typically created collaboratively by a team of teachers responsible for the same grade level, course, or content area.
So, do your students know what are the targets for their learning?
Existing Summative and Formative Classroom Assessments Not Aligned with Expectations
Classroom Summative and Formative Assessments Aligned to Expectations
Common Classroom Summative and Formative Assessments Aligned to Expectations
Common Formative and Summative Assessments Aligned to Expectations and
Delivered Online Through DataDirector
Implementing Assessments with DataDirector
Adapted from St. Clair RESA
Developing Common Assessments:
A Design Overview
• Step 1 – Define Purpose• Step 2 – Identify “Fair Game” in Terms of Standards• Step 3 – Balance of Representation• Step 4 – Develop an Assessment Blueprint• Step 5 – Select or Develop Items• Step 6 – Develop the Assessment• Step 7 – Administer and Score the Assessment• Step 8 – Set the Cut Scores
Source: Center for Curriculum Renewal, www.curriculumrenewal.com
Test Blueprint Methods of Assessment
Selected Response
Extended Written Performance Personal
Communication Target Totals
# Points # Points # Points # Points # Points
Learnin
g Targets
Target 1 3 3 2 2 5 5
Target 2 1 1 2 2 2 4 5 7
Target 3 2 2 1 3 3 5
Target 4 3 3 1 2 4 5
Target 5 2 4 1 4 3 8
DOKTotals 6 6 10 14 4 10 0 0 20 30
Reverse Blueprint Design Adrian—Lincoln Elementary
Teacher 1
Excellent Examples
Webb (1997) Depth of Knowledge • Recall • Use • Strategic • Extended
Anderson & Krathwohl (2001)
Revised Bloom’s Taxonomy
Questions?Stan MastersCoordinator of
Instructional Data ServicesLenawee Intermediate School DistrictFireside Building4107 N. Adrian HighwayAdrian, Michigan 49921
517-265-1606 (phone)517-265-2953 (fax)[email protected]/links/data