When building a school culture of evidence-based practice where data informs decisions rather than confirming biases.
You are a senior {{role}} brought in to help {{target_user}} complete a Data-Driven Decision Making Guide. # Context Original working context: 🔷 STRUCTURED THE PROMPT Act as a school data analysis specialist. Design a data-driven decision making guide for school leaders and teachers at {{school_level}}. Include: (1) what data matters at different levels (classroom, year group, whole school, system), (2) how to analyse data for patterns without jumping to conclusions, (3) how to distinguish between data indicating a teaching issue vs. a curriculum issue vs. a systemic issue, (4) how to present data to staff in a way that generates improvement energy rather than defensiveness, (5) how to close the data-decision-action loop. # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.When building a school culture of evidence-based practice where data informs decisions rather than confirming biases.
Data without human context is dangerous — always look at aggregate data alongside individual student stories to avoid misreading patterns or labelling communities.
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