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Related Experiment Video

Updated: Sep 30, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
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A large-scaled corpus for assessing text readability.

Scott Crossley1, Aron Heintz2, Joon Suh Choi3

  • 1Georgia State University, Atlanta, GA, USA. scrossley@gsu.edu.

Behavior Research Methods
|March 17, 2022
PubMed
Summary
This summary is machine-generated.

The CommonLit Ease of Readability (CLEAR) corpus offers unique readability scores for 5000 text excerpts. This resource aids researchers in developing and testing text readability metrics.

Keywords:
Corpus linguisticsNatural language processingReadabilityReadability formulas

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Area of Science:

  • Computational Linguistics
  • Educational Technology
  • Psycholinguistics

Background:

  • Readability metrics are crucial for understanding text complexity.
  • Existing corpora may lack sufficient size, scope, or relevant metadata for advanced research.
  • Developing robust readability models requires diverse and well-annotated text datasets.

Purpose of the Study:

  • Introduce the CommonLit Ease of Readability (CLEAR) corpus.
  • Provide researchers with a comprehensive resource for studying text readability and discourse processing.
  • Facilitate the development and validation of new readability metrics.

Main Methods:

  • Compilation of approximately 5000 text excerpts spanning over 250 years and multiple genres.
  • Generation of unique readability scores based on teacher ratings of text difficulty.
  • Inclusion of metadata such as publication year and genre for each excerpt.

Main Results:

  • The CLEAR corpus contains ~5000 text excerpts with associated readability scores and metadata.
  • The corpus covers a wide range of historical periods and genres, offering broad applicability.
  • Reliability metrics for the human readability ratings have been established and are presented.

Conclusions:

  • The CLEAR corpus represents a significant advancement over previous readability resources.
  • It provides a valuable foundation for research in reading comprehension, discourse analysis, and educational technology.
  • The corpus enables the development and testing of more accurate and nuanced readability assessment tools.