Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Group Design02:01

Group Design

11.1K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
11.1K
Language and Cognition01:27

Language and Cognition

1.0K
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
1.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Unsupervised Machine Learning in the Evaluation of Telerehabilitation Interventions for Reading Fluency.

International journal of telerehabilitation·2026
Same author

Pancreatic Cancer-Derived Small Extracellular Vesicles Remodel Hepatic Pre-Metastatic Niche via Hybrid Epithelial-Mesenchymal States.

International journal of molecular sciences·2026
Same author

Very Low Energy Ketogenic Therapy Effects on Fibrosis-Dependent Metabolic Reprogramming: A Serum NMR Pilot Study.

Nutrients·2026
Same author

Pilot Study of an Alpha-2-Macroglobulin-Enriched Plasma-Derived Orthobiologic Preparation in Sport Horses with Chronic Degenerative Joint Disease.

Veterinary sciences·2026
Same author

Neuronal Syndecan reduction modulates age- and sex-specific changes in sleep architecture and metabolic remodeling in Drosophila melanogaster.

Mechanisms of ageing and development·2026
Same author

From evidence to action: Italian recommendations for the diagnosis and treatment of spatial neglect in stroke patients.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2026

Related Experiment Video

Updated: Apr 19, 2026

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

7.3K

Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing

Pierluigi Zoccolotti1, Maria De Luca2, Chiara V Marinelli2

  • 1Department of Psychology, Sapienza University of Rome Rome, Italy ; Neuropsychology Unit, IRCCS Fondazione Santa Lucia Rome, Italy.

Frontiers in Psychology
|December 6, 2014
PubMed
Summary

Predicting reading fluency in children is possible using basic skills like decoding and rapid naming. Adding digit naming improves predictions in typical readers but not in dyslexic children due to their decoding challenges.

Keywords:
RANdyslexiaindividual differencesreadingsuppression effectvocal reaction times

More Related Videos

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.9K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

10.0K

Related Experiment Videos

Last Updated: Apr 19, 2026

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
06:33

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

Published on: October 11, 2018

7.3K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.9K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

10.0K

Area of Science:

  • Cognitive Psychology
  • Developmental Psychology
  • Educational Psychology

Background:

  • Reading fluency is crucial for academic success.
  • Individual differences in reading fluency are influenced by underlying cognitive processes.
  • Understanding these processes aids in identifying and supporting struggling readers.

Purpose of the Study:

  • To predict individual differences in text reading fluency.
  • To investigate the contribution of orthographic decoding and rapid automatized naming (RAN) to reading fluency.
  • To examine the added predictive value of discrete digit naming.

Main Methods:

  • Commonality analysis was used to model reading fluency.
  • Data were collected from typically developing readers and dyslexic children (ages 11-13).
  • Measures included discrete pseudo-word reading, RAN, and discrete digit naming, considering pronunciation time.

Main Results:

  • In typical readers, orthographic decoding and RAN significantly predicted reading fluency.
  • Including discrete digit naming increased prediction variance (37% to 52%) and suppressed pseudo-word reading effects.
  • In dyslexic readers, the two-factor model explained high variance (69%) which did not improve with digit naming, likely due to decoding deficits.

Conclusions:

  • Basic cognitive processes like orthographic decoding and RAN integration are strong predictors of text reading fluency.
  • Discrete digit naming can enhance prediction in typical readers but its effect is limited in dyslexic readers.
  • Predicting reading fluency can be achieved without invoking higher-order linguistic factors.