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arXiv CS.AI·1d ago·5 min read
Using Evidence-Centered Design to Guide Prompt Engineering in Measurement: An Illustration with Automated Essay Scoring
TL;DR
Evidence-Centered Design (ECD) can enhance prompt engineering for generative AI in education, improving the validity and reliability of automated essay scoring. An empirical study shows ECD-designed prompts outperform traditional methods, leading to fairer AI-generated assessments.
✦ Why It Matters
Start applying Evidence-Centered Design principles to your prompt engineering for more reliable AI outputs today.
Key Takeaways
- Adopt Evidence-Centered Design for structured prompt engineering.
- Focus on validity and reliability in AI-generated educational outputs.
- Utilize the student, evidence, and task models in prompt design.
- Conduct empirical studies to validate prompt effectiveness.
How It Works
Evidence-Centered Design (ECD) provides a structured approach to prompt engineering by aligning prompts with educational assessment principles. The framework emphasizes understanding the student, the evidence needed for assessment, and the tasks to be performed.
By applying these principles, prompts can be designed to elicit more accurate and relevant responses from AI models, thereby enhancing the quality of automated scoring.