Module 5: Evaluating Your Documents
Use the grade level appropriateness evaluator to analyze reading demands, get scaffolding recommendations, and create revised versions for diverse learners.
Overview
The evaluators, developed in collaboration with Learning Commons, provide transparency into your AI-generated materials. The grade level appropriateness evaluator determines the text's appropriate grade level for independent reading and identifies an alternative range where students can access the text with scaffolds. It performs quantitative analysis (word count, Flesch-Kincaid grade level), qualitative analysis (text structure, language features, purpose, knowledge demands), and surfaces background knowledge requirements. Based on this analysis, you receive specific scaffolding recommendations, such as pre-teaching vocabulary, providing graphic organizers, or simplifying review questions, and can create a revised version with those scaffolds applied automatically.
Key Takeaways
Grade Level Analysis
Get independent reading grade level and an alternative range showing where students can access the text with scaffolding support.
Multi-Dimensional Evaluation
Analysis includes quantitative measures (word count, Flesch-Kincaid), qualitative factors (structure, language, purpose), and background knowledge demands.
Scaffolding Recommendations
Receive specific scaffolds: pre-teach vocabulary, provide graphic organizers, break into smaller sections, add guided reading questions, and more.
Inform, Not Judge
Evaluators help you see document properties: reading demands, complexity, and support needs. Use them to decide what to revise, not to label quality.