In collaboration with REA, SPI, Funded Programs and Leadership Development 1 Mining for Data - Part 2

In collaboration with REA, SPI, Funded Programs and Leadership Development 1

Mining for Data - Part 2


Goals of the Day

• Examine MCA data

• Apply a problem solving process to monitoring teaching, learning and leadership

• Utilize the new knowledge to refine the School Continuous Improvement Plans (SCIPs)


8:00-8:15 Introduction/Welcome8:15-8:45 MCA Overview8:45-10:15 MCA Growth & Proficiency

• Strengths• Obstacles• Inferences

10:15-10:30 BREAK10:30-11:30 Attendance & Discipline Part I


11:30-12:30 LUNCH12:30-1:15 Attendance & Discipline Part II


1:15-3:00 Goal Setting, Strategies, & Monitoring3:00-3:30 Wrap Up

Agenda:


Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 All Students

2010 57.7 51.0 59.4 55.7 44.1 45.2 48.9 52.0

2011 58.0 56.2 65.1 59.9 50.6 46.8 53.3 56.0

2012 63.2 53.9 62.0 60.5 51.8 50.6 56.4 57.2

2012 Vision 75.0 75.0 75.0 75.0 75.0 75.0 75.0 75.0

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Saint Paul Public SchoolsMCA-II Reading Change in Percent Proficient

Trend by Grade & SPPS Vision

NOTE: Numbers in italics are the difference between 2012 percent proficient and 75% SPPS Vision.

-11.8 -21.1 -13.0 -14.5 -23.2 -24.4 -18.6 -17.8


American Indian

Asian American

HispanicAfrican

AmericanCaucasian

Special Education

ELLow

IncomeAll

Students

2010 48.3 46.6 52.9 44.9 82.9 25.3 39.3 45.9 56.0

2011 48.3 46.6 52.9 44.9 82.9 25.3 39.3 45.9 56.0

2012 51.2 47.9 53.7 45.8 84.7 26.5 39.1 46.8 57.2

2012 Vision 75.0 75.0 75.0 75.0 75.0 75.0 75.0 75.0 75.0

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Saint Paul Public SchoolsMCA-II Reading Change in Percent Proficient

Trend by Student Group & SPPS Vision

-23.8 -27.1 -21.3 -29.2

+9.7

-48.5 -35.9 -28.2 -17.8

NOTE: Numbers in italics are the difference between 2012 percent proficient and 75% SPPS Vision.


*MCA-III replaced MCA-II in 2011 grades 3-8. MCA-III measures different standards than MCA-II, so comparisons to prior years are not recommended.

Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11

2011 48.5% 51.0% 40.8% 37.6% 38.9% 36.8% 27.6%

2012 51.4% 50.4% 41.0% 40.1% 38.9% 37.0% 26.6%

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MCA-II & MCA-III* Math Percent ProficientTrend by Grade

*MCA-III replaced MCA-II in 2011 in grades 3-8. MCA-III measures dif ferent standards than MCA-II, so comparisons to prior years are not recommended.


American Indian

Asian American

HispanicAfrican-

AmericanCaucasian

Special Education

EL Low Income All Students

2011 30.6% 39.7% 32.3% 23.7% 67.7% 18.1% 29.8% 30.5% 40.7%

2012 27.6% 39.4% 33.2% 24.1% 69.3% 19.0% 29.9% 30.8% 41.3%

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MCA-II & MCA-III* Math Percent Proficient Trend by Race

*MCA-III replaced MCA-II in 2011 in grades 3-8. MCA-III measures dif ferent standards than MCA-II, so comparisons to prior years are not recommended.


During the next protocol you will compare your school’s data for last year with the data for this year.

Think about your strategies. What do you need to “reconsider” based on the MCA results? Center your thinking on the link between your strategies and your school’s results on the MCA.

What can be your Courageous Conversation with building staff next year?

Reflections


The Olympics and SPPS?

What 2008 Central Graduate earned a medal at the 2012 Olympics?


Susannah Scanlan

Fencing Princeton


MCA Growth – Whaddya know?

How does MDE calculate

MCA Growth?


MDE Calculates MCA growth based on:

Select all that are true

a) National norms.

b) All the students in the district.

c) Only the white students in the district.

d) All the students in 3 comparable districts.

e) Students who MCA-

tested two consecutive years in Minnesota.

f) Students who MCA- tested three consecutive years in Minnesota.

g) Students who MCA- tested three consecutive years in your district.

Quiz!


MCA Growth and Proficiency

Objectives:

1. Using MCA data, determine the extent to which student groups are meeting the necessary growth targets to become on track for success.

2. Identify the largest gaps in student proficiency over the past two years.

3. Use the Cause Inference Matrix to reflect on which adult actions were in part responsible for 2012 results and revise SCIP accordingly.


Protocol 1: MCA Growth Protocol Goals

• Identify students who test proficient making low, medium and high growth and those who are not proficient and their growth.

• Determine the students who are achieving at the lowest levels (protocol 2) and whether or not they made the necessary growth to become on track for success.


• Find all students in the state with test scores from two successive years.

• Select all students with a particular score one year (e.g. 350 in Grade 3) and look up their scores the next year.

• Calculate the mean and standard deviation of the second year’s scores.

How does MDE calculate growth?


How does MDE calculate growth? (cont.)

• Label ½ standard deviation or more above the mean “High Growth”, ½ standard deviation or more below the mean “Low Growth”, everyone else “Medium Growth”.

• This method puts approximately 1/3 of students into each category, no matter where they started.


330

Hi# +

Lo# -

340

Hi# +

Lo# -

350

Hi# +

Lo# -

An Example


Which students are included in MCA Growth data?

• Took MCA (not MTAS) current year and prior year

• Have valid scores from both years

• Did not skip or get held back a grade level

• For grade 10 & 11 students, their “prior year” score is

actually from grade 8


If possible, use a PC and Internet Explorer as your browser.

Go to: MDE Data Center at http://education.state.mn.us/MDE/index.html

1. Click on Data Reports and Analytics.

You will be using data from the MDE Data Center to complete this session.

Protocol 1: MCA Growth

http://education.state.mn.us/MDE/index.html

http://education.state.mn.us/MDE/index.html


2. Click on Growth Summary Report and Download.

2


3

Login using your Educator Portal username and password.


4. Choose your school from the drop down menu 5. Choose Subject: Math6. Choose Category: All or predicted largest gap group7. Choose Measure: View growth by grade and category8. Click on Run Report


Scroll down to view tables for all groups



Reflecting on your school’s overall and gap group growth:

Q5. What are the Strengths?

Q6. What are the Obstacles?


Protocol 2: MCA Proficiency Protocol Goals

• Identify MCA proficiency results by student group.

• Determine which student groups have the greatest gaps compared to District wide white students (DWW).


Protocol 2: MCA Proficiency Protocol

• You will be using data from the NCLB Categories report on Viewpoint to complete this worksheet.

• Go to: Viewpoint at https://viewpoint.spps.org/login.aspx

https://viewpoint.spps.org/login.aspx

https://viewpoint.spps.org/login.aspx


1. Login using your school or district level Viewpoint username and password.(Usually your CAMPUS username and password.)

1


2. Choose: A. Year = 2010-2011 (or 2011-2012) and your school.B. NCLB/AYP Reports = NCLB Categories.

When you click on the report name, the report filters will appear.

2 A

2 B


Note: Below are the names of tests for 2010-2011 & 2011-2012.

Subjects & Grades 2010-2011 2011-2012

Reading 3-8 & 10 MCA II MCA II

Math 3-8 MCA III MCA III

Math 11 MCA II MCA II


3. Choose specific test filters.• Test: grades 3-8 & 10 reading=MN AYP-MCA II; grades 3-8 math=MN

AYP MATH III; grade 11 math=MN AYP-MCAII• Season: 2010-2011 or 2011-2012 (same as Year in step 2A)• Category: Math or Reading• Scale: Proficiency• Status: AYP Demographics• Demographic: AYP/Ethnicity, AYP/ELL, or AYP/Special Ed


4. Complete the MCA Achievement Gaps exercise using the data in the NCLB Categories report.

Note: Enter on form but disregard any student group with less than 10 students, see numbers circled below.


Data Analysis Guiding Questions

MCA Growth and Proficiency

• Complete matrix and reflect on cause data to determine how the work of the school (cause data) links with the outcome data (MCA achievement and growth).

• Revise SCIP based on new insights and knowledge from results and analyses.


Attendance and Suspension Data

Using Our Racial Lens

August 2012 Data Dig


• Why is attendance and discipline data important?

• How does it relate to student achievement?

• What does race have to do with it?

Purpose


What does the Research say about the Impact of Attendance on Academic Achievement?

• The majority of students who drop out of high school enter 9th grade with a pattern of chronic absenteeism that goes back at least several years (Baltimore, 2010)

• Probability of graduation increases steadily as 9th grade attendance rates increase (Baltimore, 2012).

• Students with high attendance rates suffer academically from being in an environment where absenteeism is a problem (NYC, 2011).

• 9th grade attendance was a better predictor of dropout than 8th grade test scores (Chicago, 2007).

• Poor school attendance is the number one reason students drop out of school (North Carolina, 2012).

• Students who arrived in kindergarten academically ready to learn, but then missed 10% of their kindergarten and 1st grade, scored an average of 60 points below similar students with good attendance on 3rd grade reading tests (2011).

• African American males are almost twice as likely as the general population and more than three times as likely as White boys to be chronically absent (Oakland, 2011).

Full report available on the Data Center, datacenter.spps.org/data_digs

http://www.datacenter.spps.org/data_digs

http://www.datacenter.spps.org/data_digs


Know the attendance and discipline data of the student groups in your building

Study your data through an equity lens

Create an action plan for the school year

Finalize SCIP

Objective


Agenda:1. Analysis of attendance data (11 or more days absent) for gap and growth

2. Analysis of discipline/suspension data for gap and growth

3. Review SCIP and update- SMART goal(s)- Strategies- Monitoring plan

Attendance and Suspension Data

Using Our Racial Lens


• All data comes from CAMPUS

• This is self-reported data as of 7/30/12

• You will be accessing attendance and discipline data from the SPPS Data Center website.

Data Parameters


Attendance Data: Absent 11 or more days


Prediction:

Which student group has the highest 11 or more absents for the 2011-12 school year?

Protocol 1: Prediction


Identify by percent of students absent 11 or more days

http://datacenter.spps.org/• Click on “School”• Select your school• Select topic “Attendance”• Select report “Absent 11 days by Ethnicity”

Protocol 2: Data Analysis

http://datacenter.spps.org/


1. What trends or patterns do you notice with the data?

2. What are the strengths? What’s going well?

3. What are the challenges or opportunities?

4. What are the gaps?

Protocol 3: Observations


Based on your observations…..

what inferences can you make about the data?

Protocol 4: Inferences


Discipline Data:Suspension


Prediction:

Which student group has the highest suspension rate?

Protocol 1: Prediction


Identify suspension rate by student group.

http://datacenter.spps.org/• Click on “School”• Select your school• Select topic “Discipline”• Select report “Suspension by Ethnicity”

Protocol 2: Data Analysis

http://datacenter.spps.org/


What trends or patterns do you notice with the data?

What are the strengths? What’s going well.

What are the challenges or opportunities?

What are the gaps?

Protocol 3: Observations


Based on your observations…

what inferences can you make about the data?

Protocol 4: Inferences


Review and make changes and/or updates to:

• SCIP SMART Goals• Strategies• Monitoring Plan

SCIP website: http://scip.spps.org/• To view SCIP – click on 2012-12 SCIPs (in progress)• To edit SCIP – use your CAMPUS user name &

password

What Next?

http://scip.spps.org/


Analyze toPrioritize

Monitor & Evaluate Results

Treasure Hunt

SMART Goals

Specific Strategies

Results Indicators

Inquiry;Develop Questions


Strategies,

Results Indicators &

Setting up for Success


Did what you did last year, get your students where

you planned they would be at the end of the year?


Leadership & Learning Matrix

Leadership/Teacher Practices

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Lucky High results Low understanding of antecedents Replication of success unlikely

Leading High results High understanding of antecedents Replication of success likely

Losing Ground

Low resultsLow understanding of antecedentsReplication of failure likely

LearningLow resultsHigh understanding of antecedentsReplication of mistakes unlikely


Step 3Establish SMART Goals

To identify our most critical goals for student achievement based on the challenges that were identified through the inquiry process

Specific, Measurable, Achievable, Relevant, Timely

Year-long at building level



5757


Strategies

Adult actions will impact student achievement

Strategies are—

• Action-oriented• Measurable/accountable• Specific• Research-based

Most powerful when linked directly to the most urgent needs of students. . . .


Strategies

Instructional- what the adult is doing to impact student cognition

Program- resources to support teaching and learning (program) not practice

Process- how we are doing it

Leadership- guiding actions to improve teaching and learning

Most powerful when linked directly to the most urgent needs of students. . . .


Quality Prioritization

To take immediate action on the most urgent needsQuality prioritization requires a thorough

understanding of:• Student population• Curriculum and Power/Priority Standards

(leverage, readiness)• Antecedents affecting student achievement• Quality of program implementation

White, 2005Most powerful when linked directly to the most urgent needs of students. . . .


Refine Your Specific Strategies via fishbone


1. Go back and look your strengths, obstacles and inferences from morning protocols

2. Place obstacles in the box3. Put inferences in the bones.

Inferences are things that you think influence the obstacle

4. Circle the inferences that are most under your control

5. Prioritize the inferences into the top two or three

6. Go into SCIP document and review your strategies

7. Review strategies to ensure that the strategy is aligned to the prioritized inferences (causes)

8. Refine if needed


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Inferences


Step 5: Determine Results Indicators

• How will we know we are doing it?• How will we know we are doing it well?• How will we know it is working?

To monitor the degree of implementation and evaluate the effectiveness of the strategies


Results Indicators

Considerations

• Serve as an interim measurement

• Used to determine effective implementation of a strategy

• Used to determine if strategy is having the desired impact

• Help to determine midcourse corrections



Step 6Monitor and Evaluate Results

To engage in a continuous improvement cycle that—

– Identifies midcourse corrections where needed

– Adjusts strategies to assure fidelity of implementation


Develop Your Monitoring Plan• This is what needs to happen via the BLT monthly meetings

• Review your work from developing questions to determining results indicators then determine how you will monitor the strategies. When you create your monitoring plan consider:

– Teacher or administrator teams– Monitoring cycles– Goals– Strategies– Impact on student and adult behavior– Ability to make midcourse corrections


Documents

In collaboration with REA, SPI, Funded Programs and Leadership Development 1 Mining for Data - Part 2