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

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of attention,...

You might also read

Related Articles

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

Sort by
Same author

Comparative safety of postoperative HIPEC with recombinant mutant TNF-α versus paclitaxel for gastric cancer peritoneal metastasis: a randomized controlled trial.

Surgical oncology·2026
Same author

Deciphering immune-inflammatory dysregulation in the endometriotic microenvironment: insights from single-cell omics and artificial intelligence.

Frontiers in immunology·2026
Same author

Topology-Aware Segmentation for Tubular Structure in 3D Microscopy.

Physics in medicine and biology·2026
Same author

A predictive model for mortality in VA-ECMO patients based on early coagulation-immune interactions: A single-center retrospective study.

Respiratory medicine·2026
Same author

TACE plus donafenib and immune checkpoint inhibitors for intermediate HCC (CHANCE2410 study): a propensity score matching analysis.

European radiology experimental·2026
Same author

Early Apple Bruise Detection via Discrete Hyperspectral Signatures with SHAP-Guided Feature Selection and a CNN-Transformer Model.

Foods (Basel, Switzerland)·2026
Same journal

An Eye-Tracking Study on Text Accessibility and Comprehension in University Students.

Behavioral sciences (Basel, Switzerland)·2026
Same journal

The Relationship Between Physical Activity, Social Support, and Life Satisfaction Among Female College Students: A Variable- and Person-Centered Analysis.

Behavioral sciences (Basel, Switzerland)·2026
Same journal

Shifting the Blame: How Narrative Framing, Coercive Strategies, and Rape Myth Acceptance Distort Perceptions of Sexual Assault and Fuel Victim Blame.

Behavioral sciences (Basel, Switzerland)·2026
Same journal

An AI Perspective on Counseling Supervision.

Behavioral sciences (Basel, Switzerland)·2026
Same journal

Symbolic Participation or Substantial Learning Behavior? A PSM-Based Comparison Between Honors and Non-Honors Undergraduates from Two Top Elite Universities in China.

Behavioral sciences (Basel, Switzerland)·2026
Same journal

Literacy Profiles in Twice-Exceptional Preadolescents with Intellectual Giftedness and Dyslexia.

Behavioral sciences (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 28, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
10:58

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

Published on: August 28, 2021

Individual Differences in Detecting and Correcting Logical Errors in Mathematical Texts.

Zhenhua Luo1,2, Xinyuan Yang1,2, Yong Zhang3

  • 1School of Mathematical Sciences, East China Normal University, Shanghai 200241, China.

Behavioral Sciences (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

High-achieving students excel at identifying and fixing logical errors in math reasoning. Their error detection is more active and effective compared to average students, who are more passive and text-dependent.

Keywords:
error detection and correctionindividual differenceslogical errorsmathematical reasoningthink-aloud

More Related Videos

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

Related Experiment Videos

Last Updated: May 28, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
10:58

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

Published on: August 28, 2021

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

Area of Science:

  • Cognitive Psychology
  • Mathematics Education

Background:

  • Logical reasoning is crucial for mathematical problem-solving.
  • Understanding individual differences in error detection can inform pedagogical strategies.

Purpose of the Study:

  • To investigate how senior high school students with varying mathematical abilities detect and correct logical errors.
  • To compare the cognitive processes and error detection styles between high and average ability students.

Main Methods:

  • Employed think-aloud protocols and interviews with 16 senior high school students (8 high ability, 8 average ability).
  • Students solved three mathematical logical error-detecting tasks.

Main Results:

  • High ability students demonstrated superior performance in error detection and correction speed, judgment, explanation, and accuracy.
  • Distinct error detection styles emerged: high ability students were active and efficient, while average ability students were passive and text-reliant.
  • Cognitive processes involved reading, analyzing, checking, judging, and correcting errors.

Conclusions:

  • Mathematical ability significantly influences the capacity for logical error detection and correction.
  • Tailored instructional approaches may be needed to support average ability students in developing more active and effective error detection skills.
  • Logical error-detecting tasks are valuable learning tools, particularly for fostering critical thinking in mathematics.