Data Tools to disaggregate student performance data

Exhibited by:

• Marisol Weiner

PLO Attended:

• Data Liaison Series (9 - 12)

Coached by:

• Joseph Daniele

PLO GOALS

At Columbia Secondary School (05M362), we are already achieving at a high level so it did not seem clear how city and statewide data could help us improve significantly.

• Reasons for attending PLO: to acquire knowledge of DOE data tools, to acquire analytical skills to identify for which students interventions could make a greater impact, and to learn how to turnkey data tools and engage school staff in a cycle of learning.
• Goal from attending: to use data tools to disaggregate student performance data to identify those most in need of support.

PLO LEARNINGS

• I gained an understanding of how the NYCDOE and the NYSED measure, analyze, and display school performance data.

School Performance Dashboard (NYC DOE): combines multiple years of data from School Quality Reports and displays schools’ results and key comparisons in visual form to show trends, patterns, strengths, areas for improvement, and areas for further investigation.

- I learned how to gauge trends.

Graduation, Credit, and Performance Index (GCPI) Analyzer (MFSC), tool designed to build capacity of key stakeholders in schools, to engage in meaningful conversations about strategic changes in student programming, school operations, and allocation of school resources. The strategic changes in these areas, motivated by analyses of GCPI data, drive student performance upward, and subsequently schools’ Performance Indexes that drive state accountability.

- I learned how to disaggregate student performance data by cohort, ethnicity, and additional statuses, and identify exactly which students are in need of additional support.

• I learned how to turnkey these data tools to other stakeholders at my school, and afterwards, to engage in a cycle of learning with them.

IMPLEMENTATION OF TECHNIQUES AND PRACTICES

Conversations between teachers and administrators are part of the school culture; accessing data is important for us to grow and improve.

• Process: I introduced the SCHOOL PERFORMANCE DASHBOARD. Based on the analysis, we identified high level tendencies that were important to our school. Afterwards, I shared the GCPI ANALYZER TOOL as a means for disaggregating student data in order to understand the high level trends we saw on the dashboard.
• Stages: The stages of implementation were accessing data, analyzing data, sharing data, and gathering feedback.
• Monitoring: I monitored the progress by requesting key stakeholders with whom I discussed and shared data to report on their findings, and next steps.

IMPACT

• School Performance Dashboard showed: high performance/low impact, college readiness does not match graduation rate, Math has a lower score than English.
• Graduation, Credit, & Performance Index (GCPI) Analyzer showed: the math program is not supporting all students to succeed in a high performance environment.

CONCLUSION

• Math should be our target if we want to increase the impact on our lower achievers.
• Areas of further exploration: a) is our accelerated Math program having impact on ALL students? b) In our 6-12 school, are we doing our best to accelerate our new HS students? c) Do we need a better transition for incoming 9^th graders?

NEXT STEPS

Make the feedback forms electronic, invite Field Support Center instructional leads into the school to help develop and give feedback on proposed interventions, work with teachers of students receiving interventions to develop baseline and interim assessments, and discuss progress in Monday PDs.