Predicting Text Comprehension, Processing, and Familiarity in Adult Readers: New Approaches to Readability Formulas

Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers u...

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Bibliographic Details
Published in:Discourse processes 2017-07, Vol.54 (5-6), p.340-359
Main Authors: Crossley, Scott A., Skalicky, Stephen, Dascalu, Mihai, McNamara, Danielle S., Kyle, Kristopher
Format: Article
Language:English
Subjects:
Adults
Comparative Analysis
Computational Linguistics
Computer Software
Connected Discourse
Correlation
Criticism
Familiarity
Identification
Multiple Regression Analysis
Natural Language Processing
News Reporting
Online Surveys
Periodicals
Prediction
Readability
Readability Formulas
Reading Comprehension
Reading Habits
Reading Processes
Statistical Analysis
Television Viewing
Text Structure
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Summary:Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e., natural language processing, crowd-sourced ratings, and machine learning). The primary focus is on the identification of the linguistic features that predict adult text readability judgments, and how these features perform when compared to traditional text readability formulas such as the Flesch-Kincaid grade level formula. The results indicate the traditional readability formulas are less predictive than models of text comprehension, processing, and familiarity derived from advanced natural language processing tools.
ISSN:0163-853X
1532-6950
DOI:10.1080/0163853X.2017.1296264