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Panelists:
- Dr. Rajagopal Appavu
- Jerod Neff
- Kurtis Hewson

Episode Summary:
In this episode of Data in Education, Jenelle and Jessica are joined by researchers, district leaders, and system-level practitioners to explore why data tools often fail when habits are missing, and what it actually takes to build data-literate teams.
Rather than focusing on new dashboards or one-time professional development, the conversation centers on the daily habits, language, and routines that make data usable, actionable, and human.

The conversation focuses on:
- Why data tools break down when habits, clarity, and shared purpose are missing
- How data literacy shows up (or doesn’t) in everyday team conversations
- What educators and leaders can do differently tomorrow to turn data into action instead of anxiety

This episode is especially relevant for educators and leaders who are thinking about how data is used in real classrooms and meetings, and who want data to feel more supportive, actionable, and human rather than overwhelming or compliance-driven.

Actionable Guidance from Our Panelists:

Dr. Rajagopal Appavu
- I can organize the data to gear toward personalized learning.
- I can identify the difference between structured and unstructured data.
- I can identify how my actions connect to the data.
- I can practice the right habits to collect the right data.
- I can visualize the dashboard with intention.

Jerod Neff
- I can understand that I bring my A-game (best intention) before discussing data.
- I can be aware of the purpose by using simple, shared language.
- I can clarify meaning through clear rubrics and expectations.
- I can feel comfortable talking about struggles with student growth.
- I can move from data talks to data action.
- I can reshape how teachers feel about data and transform teacher conversations.

Kurtis Hewson
- Free Leadership Resources from Jigsaw Learning - https://www.jigsawlearning.ca/free
- I can organize the data so teams can respond.
- I can understand how teams use data to inform planning.
- I can see strengths in the data and identify what led to them.
- I can identify gaps and choose one next step.
- I can ask, “How will you know?” and build systems that support the answer.
- I can ask, “What do you think you did?” to connect actions to outcomes.

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