I love working with data. Warm-Up Exercise Reflect on this statement: I love working with data. Red/orange means you DISAGREE Yellow means you are IN THE MIDDLE Green means you AGREE

Using Data to Increase Attendance Presented September 8, 2017, in Albuquerque, New Mexico, at the Every Day Matters: Building School-Based Plans to Reduce Chronic Absenteeism Conference Using Data to Increase Attendance Deborah Good Director of Data and Research, Mission: Graduate

Presentation Overview The Basics Understanding the Problem Continuous Improvement

The Basics

The Basics: Calculating Chronic Absence # of days absent # of days enrolled = XX % days missed SEVERE Chronic Absence (missing 20% or more of school days) MODERATE Chronic Absence (missing 10-19.99% of school days) AT-RISK Attendance (missing 5-9.99% of school days) SATISFACTORY Attendance (missing less than 5% of school days)

Chronic Absence is Research-Based Excused Absences Chronic Absence + Unexcused Absences + Suspensions

ADA versus Chronic Absence Average Daily Attendance and Chronic Absence Average Daily Attendance (percentage of students present on the average day) % Chronic Absence (percentage of students who missed 10% or more of school days)

The Basics: Calculating Chronic Absence # of days absent # of days enrolled CHALLENGE: Some data systems are not currently set up to calculate chronic absence rates HELPFUL RESOURCE: http://www.attendanceworks.org/tools/tools-for-calculating-chronic-absence/ ALTERNATIVE: Use total number of absences for each student (excused + unexcused + suspensions), and establish cutoffs based on the # of school days to date.

The Basics: Calculating Chronic Absence For example: As of 40 days into the school year, Any student with ____ or more absences (10%) is chronically absent Any student with 8 or more absences (20%) is severely chronically absent 4 ALTERNATIVE: Use total number of absences for each student (excused + unexcused + suspensions), and establish cutoffs based on the # of school days to date.

The Basics: Data Best Practices Source: StriveTogether (2015). Student Data Privacy Best Practices.

The Basics: Qualitative and Quantitative Structured data Numbers Collected through assessments, surveys, databases Analyzed with statistics Presented through graphs and tables Qualitative Unstructured Words and images Collected through observations, surveys, interviews, focus groups Analyzed with themes Presented as summaries and quotes

Understanding the Problem

Understanding WHO is absent Chronic Absence by Race/Ethnicity 30% of ALL students were chronically absent % SATISFACTORY Attendance (missing less than 5% of school days) % AT-RISK Attendance (missing 5-9.99% of school days) TOO FEW STUDENTS % MODERATE Chronic Absence (missing 10-19.99% of school days) % SEVERE Chronic Absence (missing 20% or more of school days) AFRICAN AMERICAN (4 STUDENTS) NATIVE AMERICAN (294 STUDENTS) WHITE (35 STUDENTS) HISPANIC (392 STUDENTS)

Understanding WHEN they are absent

Understanding WHY are they absent? Surveys Focus Groups Interviews Observations Self-Assessment Attendance Codes

Understanding WHY are they absent? What are all the different reasons that you have missed school this year?

Continuous Improvement

Continuous Improvement Plan Do Study Adjust

Continuous Improvement: STUDY Are we doing the right things? Are we doing things right? What data do we need to collect in order to answer these questions?

Performance Measures Answer Three Questions Quantity Quality Effort How much did we do? # clients/customers served # activities (by type of activity) How well did we do it? % common measures (e.g., client-staff ratio, % clients seen in their own language) Responses to a satisfaction survey Effect Did we make a difference? Changes in: Attitudes, Knowledge, Behavior, Circumstance How much did we do? How well did we do it? Did we make a difference?

Results-Based Accountability Websites raguide.org resultsaccountability.com resultsleadership.org

Performance Measures Example What data can we use to evaluate whether PSAs and robocalls before holidays helps increase attendance? How much did we do? How well did we do it? Did we make a difference? Effort Effect

Setting Performance Measures (excerpt from Attendance Success Plan) How much did we do?  How well did we do it? Did we make a difference? # of robocalls sent # of flyers that went out # and % of calls that reached a live person % of student body that received the calls Feedback from parents # of days before holiday robocalls were sent # of languages flyer was translated into Comparison of last year’s attendance rate the day before the holiday compared with this year

Data Collection and Analysis Plan Data- related Action Steps By When Do We Plan to Get This Completed Who Oversees the Action Step Who Does the Work Who Approves the work Who Must Be Consulted Who Must Be Informed Design survey September 15  Phyllis Joseph Phyllis Principal Robinson and Attendance Team members Third period teachers Administer survey to all 8th graders September 16-20  Violeta Third period teachers Principal Robinson N/A  etc.   Attendance Team Debrief re: Perf. Measures Mid- December Mid-April  N/A

Questions? Thoughts? Deborah.Good@uwcnm.org