ROAR, AI, and Rapid Assessment for Adolescent Readers
A rapid-assessment partnership focused on AI-supported item development, vocabulary measurement, and actionable reading data for older students.
Overview
This project connects my vocabulary assessment work with ROAR and the broader challenge of building rapid, scalable reading assessments for older students. The focus is on AI-supported item development, principled vocabulary sampling, and feedback that can help schools understand adolescent readers more precisely.
ROAR is best understood on this site as a connected assessment partnership within the broader BEAM agenda. It provides a pathway for translating vocabulary and reading measurement research into tools that can be used at scale.
Why this matters
Older struggling readers often need timely information about specific strengths and needs, but many assessments are too slow, too broad, or too disconnected from instruction. Rapid assessment can help if it is designed around strong measurement principles and linked to practical supports.
Current work
- Supporting vocabulary item development for rapid assessment.
- Using lexical dimensions to guide word and meaning sampling.
- Exploring how AI can accelerate assessment development while preserving quality.
- Connecting assessment results to learner profiles and instructional recommendations.
Guiding questions
- How can rapid assessments provide useful information for adolescent literacy support?
- How can AI-generated assessment content be validated responsibly?
- How should vocabulary, comprehension, and learner profile data be connected?