Related Experiment Video
Updated: Jun 18, 2026

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
Summary
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.
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.
More Related Videos
Related Concept Videos
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...
To conduct the sign test, we first calculate the differences in value between...
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: 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 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...
This test is...
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...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
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...

