Course Content
Finding Patterns Without Overcomplicating It
This week shows you how to turn raw data into clear insight. You will learn simple routines for trend checks, subgroup scans, and triangulation. You will finish with a short pattern scan that leads to a practical next step.
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From Patterns to Causes
This week helps you move from “what we see” to “why it might be happening”. You will practise simple diagnosis tools that reduce guesswork. You will finish with a cause map and three testable hypotheses.
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Choosing Actions That Match the Evidence
This week helps you select actions that fit the problem you have diagnosed. You will learn a simple way to choose an intervention, set success criteria, and plan implementation. You will finish with a one-page action logic model that can be shared with your team.
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Leading a Sustainable Data-to-Action Culture
This week focuses on sustainability. You will learn how to build routines, roles, and meeting protocols that make data use normal, not seasonal. You will finish the course with a complete school data decision plan.
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Data-Driven Decision-Making for School Leaders

Practise a short routine that turns data into a decision-ready statement.

Task

Using one dataset from your school, complete a one-page pattern scan:

  1. Name the dataset and timeframe.

  2. Identify the unit of analysis.

  3. Describe the pattern as a neutral statement.

  4. List two hypotheses that could explain it.

  5. Identify two triangulation checks.

  6. State one next step you will take within two weeks.

Now create the one page document. Title it:
Week 2 pattern scan – [School/Campus] – [Your name]

Your work meets expectations when all are true:

  • Pattern statement is neutral and clear.

  • Hypotheses are plausible and not blame-based.

  • Triangulation checks are realistic and specific.

  • Next step is time-bound and actionable.

Optional Extension

Add one decision rule. Example: “If attendance stays below 92% for two more weeks, we will…”

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