Rapid online assessment of reading ability

Jason D. Yeatman, Kenny An Tang, Patrick M. Donnelly, Maya Yablonski, Mahalakshmi Ramamurthy, Iliana I. Karipidis, Sendy Caffarra, Megumi E. Takada, Klint Kanopka, Michal Ben-Shachar, Benjamin W. Domingue

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2–3 min) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.

Original languageEnglish
Article number6396
JournalScientific Reports
Issue number1
StatePublished - 18 Mar 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s).


FundersFunder number
National Institute of Child Health and Human DevelopmentR01HD095861


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