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Related Concept Videos

Multiple Comparison Tests01:13

Multiple Comparison Tests

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Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
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Comparing Experimental Results: Student's t-Test01:09

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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...
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McNemar's Test01:23

McNemar's Test

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McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
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Bonferroni Test01:10

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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...
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Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

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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...
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Statistical Significance01:50

Statistical Significance

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Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
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Related Experiment Video

Updated: Jan 6, 2026

Using Practice Testing, Public Speaking, and Source Monitoring to Examine the Influences of Learning Strategies and Stress on Episodic Memory
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Using Practice Testing, Public Speaking, and Source Monitoring to Examine the Influences of Learning Strategies and Stress on Episodic Memory

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Does pre-testing promote better retention than post-testing?

Alice Latimier1,2, Arnaud Riegert3, Hugo Peyre1,4,5

  • 11Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Etudes Cognitives, ENS, EHESS, CNRS, PSL University, Paris, France.

NPJ Science of Learning
|October 5, 2019
PubMed
Summary
This summary is machine-generated.

Testing students after learning content significantly improves long-term retention and knowledge transfer compared to testing before. Post-testing is a more effective retrieval practice strategy than pre-testing for learning outcomes.

Keywords:
EducationHuman behaviour

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Area of Science:

  • Cognitive Psychology
  • Educational Psychology
  • Learning Sciences

Background:

  • Retrieval practice is a highly effective learning strategy for long-term retention.
  • While post-testing (testing after learning) is well-established, pre-testing (testing before learning) also shows benefits.
  • Optimal timing of retrieval practice relative to learning content exposure remains an area of investigation.

Purpose of the Study:

  • To directly compare the efficacy of pre-testing versus post-testing for learning.
  • To evaluate the impact of retrieval practice timing on long-term retention and knowledge transfer.
  • To determine the most effective retrieval practice strategy within a fixed time allocation.

Main Methods:

  • An experiment comparing three conditions: post-testing, pre-testing, and extended reading.
  • Learners were exposed to learning content and then tested.
  • A final retention test was administered 7 days later to assess long-term recall and knowledge transfer.

Main Results:

  • Both post-testing (d=0.74) and pre-testing (d=0.35) effects were replicated, confirming retrieval practice benefits.
  • Post-testing resulted in significantly better long-term retention compared to pre-testing.
  • Post-testing facilitated knowledge transfer to new questions, while pre-testing did not.

Conclusions:

  • Testing learners after exposure to learning material is more beneficial for long-term retention than testing beforehand.
  • Post-testing enhances both recall and the ability to apply knowledge to novel situations.
  • Educational strategies should prioritize post-testing for maximizing learning gains.