MPR Associates 1 Albert Einstein said… “Not everything that counts can be counted and not everything that can be counted counts.” Using data well depends

Using Attendance DataUsing Attendance DataStrategies for Analysis, Strategies for Analysis,

Interpretation and School Interpretation and School ImprovementImprovement

Connecticut Consortium on School AttendanceConnecticut Consortium on School Attendance

Gary HoachlanderGary HoachlanderKelly OuelletteKelly Ouellette

April 2005April 2005

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CLOSING THEACHIEVEMENT

GAP

Albert Einstein said…

“Not everything that counts

can be counted and not

everything that can be

counted counts.”

Using data well depends on knowingthe difference

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GAP

Overview

Consortium data collection and reporting

Some simple analysis strategies

Beyond first impressions— extending your investigation and avoiding misinterpretation

Benchmarking and goal setting

Strategies to improve attendance

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What Do You Want to Know?

Overall attendance rate

By type of school

By demographic sub-groups

Demographics within levels of school

By grade level

By month

By day of the week

Other

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Average Daily Attendance Defined

For any given time period, the total number of days students attended divided by the total number of days students were enrolled

Calculation is usually adjusted (weighted) to reflect effect of students enrolling for less than the full school year or relevant time period

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Forming a First Impression

Average daily

attendance 2003-2004

Numberof

students

% of students attending less than

90% 2003-2004

Number of students attending less than

90% 2003-2004

Total 93.9 5,001 16.1 804

School level

Elementary 95.0 2,471 10.7 264

Middle 94.3 901 15.1 136

High 92.2 1,629 24.8 404

Average Number of Days Absent?Obvious differences among schools?Clear priorities for further investigation?

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Analyzing Sub-populations

Average daily


Numberof

students


90% 2003-2004


90% 2003-2004

Total 92.2 1,629 24.8 404

Gender

Male 92.4 832 23.6 196

Female 91.9 797 26.1 208

Race/ethnicity

White 92.2 1,486 24.6 366

Black 93.3 32 21.9 7

Hispanic 88.9 54 38.9 21

Asian 93.8 44 13.6 6

American Indian ** ** ** **

Other 94.8 10 20.0 2

All minorities 91.7 143 26.6 38

Special Education 86.0 188 49.5 93

Bilingual/ESL 89.0 23 43.5 10

Low income 86.5 74 35.1 26

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Examining Distributions

Average daily


Numberof

students


90% 2003-2004


90% 2003-2004

Total 93.9 5,001 16.1 804

Grade level

Kindergarten 94.2 285 13.0 37

Grade 1 95.1 296 8.4 25

Grade 2 95.0 304 10.9 33

Grade 3 95.1 312 9.6 30

Grade 4 95.6 407 8.8 36

Grade 5 95.1 432 10.6 46

Grade 6 94.5 435 13.1 57

Grade 7 94.4 440 14.5 64

Grade 8 94.2 461 15.6 72

Grade 9 94.2 436 18.1 79

Grade 10 93.2 419 22.4 94

Grade 11 91.4 424 26.4 112

Grade 12 89.4 350 34.0 119

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Caveats

Small numbers

Artificial precision

Correlation versus causation

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Do You Want to Improve?

Benchmarking Against Consortium

averages Consortium high performers Other districts like you

Setting challenging but realistic goals for improvement

5-year targets Targets for the coming year

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Benchmarking—Consortium Averages

Consortium Your District Consortium Your District

94.3 2,681

Total 93.4 93.9 19.0 16.1

School level

Elementary 94.6 95.0 14.8 10.7

Middle 93.7 94.3 18.8 15.1

High 91.0 92.2 27.5 24.8

Average daily attendance 2003-2004

% of students attending less than 90% 2003-

2004

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Benchmarking—Consortium High Performers

Average daily attendance 2003-2004

Minimum Value

Maximum Value

% of students attending less than 90% 2003-

2004

Minimum Value

Maximum Value

Total 93.4 90.7 96.1 19.0 4.5 30.4

School level

Elementary 94.6 93.2 96.4 14.8 4.2 22.3

Middle 93.7 89.9 95.9 18.8 5.5 35.2

High 91.0 84.2 95.4 27.5 7.7 50.8

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How Will You Reach Your Goals?

Linking attendance to specific strategies for improvement

Incentives Targeting particular schools,

grades, or populations of students

Programs Classroom Services Parents

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Some Simple Analytic Strategies

Develop a first impression—are the numbers credible; what do they seem to say?

Make the statistics concrete

Examine spread or distribution

Examine differences among subgroups

Assess relationship between performance and practice

Pose questions for further analysis

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Hold Yourselves Accountable: Set Performance Targets

Benchmark against

National and state norms

Other districts/schools like yours

Exemplary schools or districts

Set mid-range goals with incremental targets in between

Keep targets challenging but realistic

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Make Using Data a Routine

Schedule time for reflection and strategic planning

Make reporting visible and frequent

Encourage mid-course review and correction

Monitor progress, be honest about what is not working, and celebrate success!

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Strategies to Improve AttendanceSchools and School Districts Improve Attendance by:

Making Attendance a Priority

Establishing Effective Attendance Policies

Collecting and Monitoring Attendance Data

Using Data for Program Planning

Success Factors:

Leadership

Accountability

Good Data

Analysis Skills

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Make Attendance a Priority

Build awareness and commitment to regular school attendance

In school buildings: Communication, rewards, and consequences Attendance is “on the agenda” Accountability and recognition

In the home: Targeted communication Immediate and consistent follow-up Sensitivity to cultural and language

differences

In the community: Awareness-building Community involvement

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Establish Effective Policies

Ensure attendance policies are effective and consistently enforced

Commitment of administrative leaders

Absenteeism is a “red flag” issue

Consistent policy enforcement

Within school buildings

District-wide

Defined procedures and interventions

Faculty and staff involvement in policy development and implementation

Students and families are educated on policy changes and expectations

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Collect and Monitor Data

Ensure intervention occurs when students begin to exhibit patterns of poor attendance Standardized attendance data collection

Useable computer systems and analysis tools

Staff training and support

Teacher involvement in attendance monitoring and intervention

Attendance teams at the district and school building levels

Planned opportunities for data analysis and strategy development

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Use Data for Program PlanningAttendance improvement strategies are based on analysis of attendance data Quantitative data is a starting point

Qualitative analysis: “What is really going on?”

Intervene on a student-by-student basis

Focus on issue-specific programs

Transitions, levels of schooling

Establish attendance habits early (Kindergarten)

Create incentives that students care about

Address attendance in terms of school climate

Kids go to school when they want to be there

Documents

MPR Associates 1 Albert Einstein said… “Not everything that counts can be counted and not everything that can be counted counts.” Using data well depends