One of the highlights we鈥檝e witnessed so far as we work with our Instructional Leadership Collectives (), is how leaders are breaking down the isolation of working in a silo and seeing the impact of working in a collective.
Take what鈥檚 going on with one of our collectives. Over the last few meetings, the participants鈥攕chool principals, assistant principals, or regional leaders鈥攈ave been focusing their efforts on getting teachers to use data to drive instruction.
Yet, we鈥檝e noticed that the participants are not necessarily explicitly modeling for their teachers what that process looks like. That鈥檚 essential because teachers take cues from what we do as leaders, not just what we say.
So we asked members in our data collective to bring back specific examples to our sessions to show how their leadership models data use for staff. Some are engaging in impactful actions while others are just beginning to dive into the work.
Below are four leadership moves inspired by that data collective session that we believe you can start tomorrow. Just make sure these moves are directly tied to the problem you are trying to solve.
1) Make student voice visible (and usable)
One participant shared how her team pairs brief 鈥渓ook鈥慺ors鈥� during random classroom walk-throughs using student micro鈥憇urveys about belonging.
She talked about 鈥渟chool process evidence鈥� (what adults are doing) and 鈥減erception evidence鈥� (how students experience it). In our collectives, we draw on the four sources of evidence developed by : demographics, perceptions, student learning, and school processes.
2) Turn benchmark data into coaching, not compliance
A middle school principal talked about how he uses benchmarks to identify students who need deeper interventions and then combines those benchmarks and interventions with specific feedback for teachers.
He creates a one鈥憄ager that links (1) a grade鈥憀evel STAR pattern, (2) the related classroom practice he observes, and (3) the micro鈥慶hange the teacher tries. Then, he and his team meet to check the impact of student outcomes.
3) Give bite鈥憇ize, actionable feedback
Another principal talked about what she defined as a small shift: coaching for small鈥慻roup instruction and discerning when technology in the classroom helps versus hinders student progress.
While modeling evidence鈥憀inked feedback, she asks questions such as, 鈥淲hat did we observe during the observation鈥� and 鈥淲hat impact did the technology tool have on students at that time?鈥� She matches the answers to her questions with observations teachers are making about student learning with technology. Then she provides feedback on the answers to those questions in the form of a conversation and bases it on information gleaned from such sources as progress data, teacher-feedback loops, and student reflections.
4) Normalize 鈥渆rrors鈥� and focus on 鈥渋nquiry鈥� to raise collective efficacy
A middle school assistant principal discussed how he reframes data discrepancies as opportunities to model how teams build confidence and skill together.
For example, the students of members of one professional learning community showed high assignment completion/grades but low performance on the team鈥檚 common formative assessment. This raises a learning question, not a blame statement.
His team noticed a pattern: a 92% assignment-completion rate, with students receiving mostly A鈥檚 and B鈥檚, yet only 46% achieved proficiency on the common formative assessment aligned with the specified ELA standard. 鈥淩ather than hunting for mistakes,鈥� he said, 鈥渨e treated this as a curiosity trigger, a chance to learn together to more accurately communicate student progress to the learner themselves.鈥�
In the End
We want our blog to be a resource that you come back to, so we can continue to develop a community that we have been trying to foster for a few years. Mostly, what we want you to know if you are a leader or a teacher is that data need to be used as a flashlight and not a hammer.
As facilitators for these collectives, we both left the session excited. The learning we engaged in with these leaders inspired us to dig deeper into what we can do better and what actions we should be taking next.
Let us know how you use data to drive your leadership. Connect with us to share your thoughts on or BlueSky ( and ).
