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

Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in value between...
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
Significance Testing: Overview01:04

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
Behrens–Fisher Test00:57

Behrens–Fisher Test

The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test is...
Bonferroni Test01:10

Bonferroni Test

The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...

You might also read

Related Articles

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

Sort by
Same author

Separating Behaviours and Adverse Consequences in the Problem Gambling Severity Index (PGSI): A Confirmatory Factor Analysis and Rasch Analysis.

Journal of gambling studies·2023
Same author

The Impact of Depth of Encoding on the Transfer of Test Enhanced Learning.

Experimental psychology·2023
Same author

Transfer of Test-Enhanced Learning.

Experimental psychology·2022
Same author

Predictors of Problem Gambling for Sports and Non-sports Gamblers: A Stochastic Search Variable Selection Analysis.

Journal of gambling studies·2021
Same journal

Error Cancellation During Early Task Performance.

Experimental psychology·2026
Same journal

Affective-Motivational Task Content and Stimulus Size Modulate Cognitive Control in Task Switching.

Experimental psychology·2026
Same journal

The Effect of Violent Virtual Avatar Experience on Players' Response Inhibition to Angry Expressions and Its Cognitive Neural Mechanisms.

Experimental psychology·2026
Same journal

Same Person, Different Personality?

Experimental psychology·2026
Same journal

Competition Matters!

Experimental psychology·2026
Same journal

A Network of Actions - Evaluating False Recall and Recognition of Objects After Studying Affordances.

Experimental psychology·2026
See all related articles

Related Experiment Video

Updated: Jun 18, 2026

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
08:06

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

Published on: June 18, 2018

Test Format Matching Moderates the Forward Testing Effect.

Monique Carvalho1, Harvey H C Marmurek1

  • 1Department of Psychology, University of Guelph, Guelph, Ontario, Canada.

Experimental Psychology
|June 17, 2026
PubMed
Summary
This summary is machine-generated.

Prior testing improves memory for new material, known as the forward testing effect. This effect is stronger when test formats match and is supported by metacognitive theory.

Keywords:
expectationforward testing effectmetacognitiontest format match

More Related Videos

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content
07:21

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content

Published on: June 29, 2016

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: Jun 18, 2026

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
08:06

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

Published on: June 18, 2018

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content
07:21

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content

Published on: June 29, 2016

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
  • Educational Psychology

Background:

  • The forward testing effect demonstrates how prior testing enhances learning of subsequent material.
  • Understanding factors influencing this effect, like test format and expectations, is crucial for optimizing learning strategies.

Purpose of the Study:

  • To investigate how test format similarity and participant expectations influence the forward testing effect.
  • To explore the role of metacognitive theory in explaining the forward testing effect.

Main Methods:

  • Participants studied two lists of word pairs, with the first list either being tested (cued recall or free recall) or restudied.
  • Participants received or did not receive information about the test format for the second list.
  • Recall performance and intrusions were measured for both lists.

Main Results:

  • Both cued and free recall testing of the first list produced a forward testing effect.
  • The forward testing effect was significantly larger when the test format for the first and second lists matched.
  • Instructions about the second list's test format improved recall independently of format similarity.
  • Prior testing reduced intrusions from the first list into the second list's recall, irrespective of format matching.

Conclusions:

  • The forward testing effect is robust across different initial test formats.
  • Test format congruence across learning phases amplifies the forward testing effect.
  • Metacognitive theory adequately explains the observed forward testing effect, particularly regarding correct recall performance.