The Mission-Driven Data Cycle
Too often, people glaze over when we talk about data. But wait a minute! There is a profound potential in what I’m calling the Mission-Driven Data Cycle. As I look back on my own experience, I have not spent enough time unleashing the data power of a team of teachers.
When we meet to discuss data about an individual freshman, we look at past interventions, swap stories of classroom interactions, and estimate learning through historical assessments and present grades. After about 15 to 20 minutes, we come to a consensus about next steps; however, those next steps are rarely fully evaluated because we need to move on to the next individual.
I’m rethinking the weekly meeting about data. In Jon Hattie’s research, two influences top his list of hundreds of strategies he studies: Teacher Estimates of Achievement (d = 1.62) and Collective Teacher Efficacy (d=1.57).
Teacher estimates of achievement
Influence Definition: The estimates of student achievement made by teachers based on their judgments. These judgments come from questioning, observing, written work, how the student reacts to increased challenge, and assignments and tests.
Influence Definition: The shared belief by a group of teachers in a particular educational environment that they have the skills to positively impact student outcomes.
Discussions about the individual must take place and have a place at the table; however, this one-at-a-time kind of data dive ties one hand behind the team's back. The Mission-Driven Data Cycle is different. It unleashes the teacher and harnesses up the team to advocate for a group of students in a tight timeframe that can be modified and amended in real time for real results. It also maximizes the time teams meet to bring impact to a category of student rather than a small group of individuals. This cycle has the potential to write a history of collective teacher efficacy. It drives discussion, forces reality to meet philosophy, and makes visible failure and success that can be tasted, digested, and converted into energy. The team has the potential to examine the results of their actual impact and then respond.
I believe that we are too much about the individual student and not enough about the team. Data is better sought than slopped onto a spreadsheet. Trusting teachers’ instincts is esteeming, encouraging, energizing, elevating, and enriching. Young teachers experience agency, and experienced teachers reengage. It taps into our best instincts and neutralizes the sometimes burdensome narratives that can dominate the discussion of individuals.
In short, the Mission-Driven Data Cycle should be a part of your team’s rhythms whether you meet daily, weekly, or monthly.
The Mission-Driven Data Cycle
10 Minutes
Reflect on last week’s mission. What worked? What did not? Did we act with fidelity? Celebrate and commiserate with the struggle for success.
5 Minutes
Teachers use fresh data (See below for the 13 types of data) to silently analyze trends and select what they believe the mission should be for the next week.
10 Minutes
The teacher shares their individual mission, and the team commits to the next mission to positively impact freshmen. The timeframe is a week. The mission is to strengthen the team and/or bring success to a targeted group of freshmen.
The 13 Kinds of Data
Academic Performance
Attendance (Day count and Period count)
Grades
Missing Assignments
Course Enrollment / Credits Earned
Assessment Data (standardized & benchmark)
Behavior & Engagement
Discipline Referrals
Student Self-Reports
Social-Emotional / Belonging Indicators
Context & Narrative
Middle School Historical Data (academic and behavioral narratives)
Teacher Knowledge (classroom observation and intuition)
Hidden Knowledge (all we need to seek with each student)
Supports & Environment
Family Context (home environment, parent/guardian engagement)
Support Services (IEP, 504, EL, counseling, social services)