Questionnaire designers use readability measures to ensure that questions can be understood by the target population. The most common measure is the Flesch-Kincaid Grade level, but other formulas exist. This article compares six different readability measures across 150 questions in a self-administered questionnaire, finding notable variation in…

While hierarchical machine learning approaches have been used to classify texts into different content areas, this approach has, to our knowledge, not been used in the automated assessment of text difficulty. This study compared the accuracy of four classification machine learning approaches (flat, one-vs-one, one-vs-all, and hierarchical) using…

The article presents the results of an exploratory study of the use of T.E.R.A., an automated tool measuring text complexity and readability based on the assessment of five text complexity parameters: narrativity, syntactic simplicity, word concreteness, referential cohesion and deep cohesion. Aimed at finding ways to utilize T.E.R.A. for…

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.,…