Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Binet's Contribution to Measures of Intelligence

Binet's Contribution to Measures of Intelligence

Alfred Binet, along with his student Théophile Simon, was tasked by the French Ministry of Education in 1904 to create a method for identifying students who struggled to learn through conventional classroom instruction. This initiative aimed to address overcrowding by placing such students in specialized schools. Binet and Simon developed an intelligence test comprising 30 tasks, ranging from simple commands, like touching one's nose or ear, to more complex tasks, such as drawing...

Arithmetic Mean

Arithmetic Mean

The arithmetic mean is the most commonly used measure of the central tendency of a data set. It is defined as the sum of all the elements constituting the data set, divided by the total number of elements. It is sometimes loosely referred to as the “average.”
When all the values in a data set are not unique, the sum in the numerator can be calculated by multiplying each distinct value by its frequency.
Sometimes, the arithmetic mean of a sample can be affected by a few data points...

Variation: Normal Distribution, Range, and Standard Deviation

Variation: Normal Distribution, Range, and Standard Deviation

In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...

Arithmetic Sequences

Arithmetic Sequences

An arithmetic sequence is a structured arrangement of numbers where each term is derived by adding a constant value, known as the common difference, to the previous term. This consistent pattern allows for the efficient computation of any term within the sequence as well as the cumulative sum of multiple terms. The formula for finding the nth term of an arithmetic sequence is:Here, aₙ represents the nth term of the sequence, a is the first term, d is the common difference, and n is the...

Real Number Operations

Real Number Operations

The concept of real numbers includes all the values that can be represented on a continuous number line. The system began with basic counting values used for enumeration. It later expanded to include values that represent the absence of quantity and opposites of the counting values. When situations required expressing parts of a whole or dividing quantities evenly, values capable of representing such proportions were developed. When written using decimal notation, these values can end or repeat...

Statistical Analysis: Overview

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

You might also read

Related Articles

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

Sort by

Same author

Survival After Pancreatic Resection for Intraductal Papillary Mucinous Neoplasm: Supporting Selective Surgery.

United European gastroenterology journal·2026

Same author

Non-Symbolic Magnitude Processing Is a Strong Correlate of Symbolic Math Skills in Children From Ghana and Côte d'Ivoire.

Developmental science·2026

Same author

Digital quantification of stroma percentage enhances prognostic stratification in pancreatic cancer.

Surgery open science·2026

Same author

Crossroads in the Learning Brain: The Neural Overlap Between Arithmetic and Phonological Processing.

Human brain mapping·2026

Same author

A Tissue-based Biomarker Risk Score for Predicting Survival in Pancreatic Ductal Adenocarcinoma.

Cancer diagnosis & prognosis·2025

Same author

Prognostic model establishment and immune microenvironment analysis based on transcriptomic data of long-term survivors of pancreatic ductal adenocarcinoma.

Biochemistry and biophysics reports·2025

Search research articles

Related Experiment Video

Updated: May 6, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

What basic number processing measures in kindergarten explain unique variability in first-grade arithmetic

Dimona Bartelet¹, Anniek Vaessen, Leo Blomert

¹Top Institute for Evidence Based Education Research, Maastricht University, 6200 MD Maastricht, The Netherlands.

Journal of Experimental Child Psychology

|October 17, 2013

Summary

This summary is machine-generated.

Early math skills matter for arithmetic fluency. Kindergarteners' ability to process symbolic numbers, like digits, uniquely predicts first-grade math success, regardless of their initial math level.

Keywords:

Arithmetic proficiency Elementary school Non-symbolic number processing skills Symbolic number processing skills Task-specific effects Unique predictors

More Related Videos

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Related Experiment Videos

Last Updated: May 6, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Universal Screening for Prevention of Reading, Writing, and Math Disabilities in Spanish

Published on: July 18, 2020

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

Area of Science:

Cognitive Psychology
Developmental Psychology
Educational Psychology

Background:

Children's mathematics achievement is linked to basic number processing skills.
Unresolved questions remain regarding which specific kindergarten skills predict arithmetic fluency and if these predictors are skill-contingent.

Purpose of the Study:

To identify unique kindergarten predictors of first-grade arithmetic fluency.
To examine the influence of symbolic and non-symbolic number processing efficiency on arithmetic achievement.
To determine if these predictors are contingent on children's initial arithmetic proficiency.

Main Methods:

Assessed kindergarteners' non-symbolic and symbolic number processing efficiency.
Evaluated the contribution of magnitude representations to arithmetic achievement.
Measured arithmetic proficiency in Grade 1 using hierarchical and quantile regression analyses.

Main Results:

Digit comparison, counting, and numerosity estimation efficiency uniquely predicted arithmetic differences.
Symbolic number processing efficiency consistently predicted arithmetic achievement across all proficiency levels.
Non-symbolic number processing efficiency did not predict arithmetic achievement, and representational precision was not associated with fluency.

Conclusions:

Symbolic number processing efficiency in kindergarten is crucial for developing arithmetic fluency in Grade 1, independent of non-numerical factors.
The predictive power of non-symbolic number skills on arithmetic achievement is not dependent on the child's achievement level in a nonclinical population.