7.1.1: The Value of LLMs for Data Analysis in RM Compare
Applying Question-Led Expertise to Data
You’ve already learned the power of asking great questions to drive understanding and learning. This lesson now extends those skills to working with session data—showing how LLMs make it possible to interrogate complex assessment results quickly and meaningfully.
What’s New: LLMs in the Data Analysis Workflow
- Targeted Insights: LLMs respond directly to your context - for example, uncovering which classes improved most over time, or where unexpected patterns exist in your sessions.
- Efficiency in Review: Instead of sifting through static reports, you guide the LLM to generate summaries, comparisons, or even bespoke charts - cutting through the noise.
- Support for Action: The output isn’t just more information; it’s actionable, helping you decide what to do next in curriculum planning or practical teaching.
Example Scenarios You Can Now Explore
- “How did student performance shift between two multi-centre sessions?”
- “Which question types show the widest variation in judging agreement?”
- “Has any group closed the gap since last term?”
What this means for you:
Lesson 1.1 bridges your questioning approach with practical, LLM-powered data work in RM Compare—setting the stage for actionable, efficient insight without duplicating earlier, more general training.