2011-2012 data dialogues stan masters lenawee isd february 10, 2012

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Dropout Rates

2011-2012 Data Dialogues

Stan Masters

Lenawee ISD

February 10, 2012

Data Driven Dialogue

dialogue or dialog 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. --dialogue v.

Deb Clancy, Washtenaw ISD, 2008


The idea is that from this dialogue, new understandings may emerge. This shared understanding forms the base from which we may begin to design changes that will effect our students in positive ways.

Ways of Talking







Deep Understanding



That Stick

Culture of Collaboration



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 Reading

Grade 3Grade 4Grade 5Grade 6Grade 7Grade 8MMEAdvanced3644785656537608531141Proficient3244195216197218181108Partially Proficient3013955016026987961081

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




Elementary Principals Study 3rd Grade Reading Readiness

Last NameFirst NameAIMSweb S-RCBM (90)AIMSweb S-Maze (14)Dolch % 100% of all 4 listsDRA Independent Lev. (28)Spelling Inven. %701210014861732310015972123010017100681110028737391002887

How well do the existing local assessments predict success on the Grade 3 Reading MEAP?




I predict . . .

I can count . . .

I believe that the data suggests . . . because,

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


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 Study167-221Narrative Text168-226Informational Text161-230Comprehension167-227
Standard/ClusterAverageMichigan 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.

33DORF Retell65Grade 3 Comprehension52514

4th Grade Math PreTest

Morenci Elementary Electronic Student Data Profiles

Dolch Word List 3rd TriStar Test Grade Equivalent (GE) 3rd TriStar Test Independent Reading Level 3rd TriAR Comp% 3rd TriMath 3rd Tri % Post TestAddition Facts 3rd Tri % Subtraction Facts 3rd Tri % Multiplication Facts 3rd Tri % Division Facts 3rd Tri %Writing 3rd TriSpecial ServicesRecommendations1003.23.28684808457482TITLE I1004.64.269621009990972TITLE IPR1004.64.289744971655421006.25.5898610095100991speechPR1003.13798699100100922TITLE IPR


Data Driven Decision Making in Early Literacy Teaching, Fall RDI Symposiumhttp://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

with colleagues was typically 1/wk,

less often w/ literacy or data expert;

w/admin the least frequent


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 NameLife Skills Pre-testLife Skills Post-testLife Skills GrowthLife Skills Writing PretestLife Skills Writing Post testWritingGrowth9595055649859053892547075551651465761132116846065550544657057080106550-1510313027

Onsted Middle School,NWEA Growth, by Teacher, by Class Period

Student NameTeacher NameClass Period10-11 NWEAFall Reading Test RIT Score10-11 NWEASpring Reading Test RIT Score10-11 NWEATest RIT Score Growth10-11 NWEAFall Reading Test Percentile10-11 NWEASpring Reading Test Percentile10-11 NWEATest Percentile Growth7207206-1151832207219121040302212202-10169-7120721912155035221021331425112220216-4283246226219-75350-37221214-74135-66227214-135635-21722522615170192224223-13652166231202-296613-536232213-196833-35

On Target Off Target

College and Career Readiness


College Readiness Benchmark Scores

Early Indicators of

College Readiness


EnglishEnglish Composition 13 15 18 ReadingSocial Sciences 15 17 21 Math Algebra 17 19 22 ScienceBiology 20 21 24

ACT Subject

Area Test

College Course(s)


Students who meet a Benchmark on the ACT have 50% chance of earning a B or better and 75% chance of earning a C or better in the corresponding college course or courses.

Students who meet a Benchmark on EXPLORE or PLAN are likely to have approximately this same chance of earning such a grade in the corresponding college course(s) by the time they graduate high school.

Predictions UsingEXPLORE to PLAN to ACT

Uses scores in each subject area

Use color-coding to indicate probability

Dark Green

Light Green




Reasonable Growth

On Target

(met or exceeded CRB)

Nearly On Target

(2 points from CRB)

Average Growth PointsBetween Tests

On Target (met or exceeded CRB)Nearly On Target (2 points from CRB)TestEXPLORE to PLANPLAN to ACTEXPLORE to PLANPLAN to ACTEXPLORE to PLANPLAN to ACTEnglish2-32-33-413-41Math2-32-31-21-22-31-2Reading1-24-53-42-33-41-2Science1-22-31-22-32-31

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 nameFirst nameEnglishEnglishReadingReadingMathematicsMathematics ScienceScience1616-201717-211414-181616-201717-211717-212021-252122-262223-272021-252122-262122-261616-201414-181616-202021-2510-11Expected10-11Expected10-11Expected10-11ExpectedEXPLORE PLANEXPLORE PLANEXPLORE PLANEXPLORE PLANLast nameFirst nameEnglishEnglishReadingReadingMathematicsMathematicsScienceScience910-131112-151112-151112-151415-181213-161415-181516-191415-181415-181718-211617-201314-171213-161516-191617-201314-171011-141112-151314-17

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




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



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