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The testing effect (also known as retrieval practice, active recall, practice testing, or test-enhanced learning) [1] [2] [3] suggests long-term memory is increased when part of the learning period is devoted to retrieving information from memory. [4]
In essence, testing of old information had a negative impact on learning new information, rather than the positive effect predicted by the forward testing effect. [13] These findings prompted another study to be conducted by Chan and Davis in 2015 which aimed to explain these findings which undermined the validity of the forward testing effect.
Some researchers include a metacognitive component in their definition. In this view, the Dunning–Kruger effect is the thesis that those who are incompetent in a given area tend to be ignorant of their incompetence, i.e., they lack the metacognitive ability to become aware of their incompetence.
Washback effect refers to the impact of testing on curriculum design, teaching practices, and learning behaviors. [1] The influences of testing can be found in the choices of learners and teachers: teachers may teach directly for specific test preparation, or learners might focus on specific aspects of language learning found in assessments.
In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
Upon a recognition memory test, there was no spacing effect found for the nonwords presented in different fonts during study. These results support the hypothesis that short-term perceptual priming is the mechanism that supports the spacing effects in cued-memory tasks when unfamiliar stimuli are used as targets.
In typical use, it is a function of the test used (including the desired level of statistical significance), the assumed distribution of the test (for example, the degree of variability, and sample size), and the effect size of interest. High statistical power is related to low variability, large sample sizes, large effects being looked for ...
If the interaction effect A*B is still significant, we will be more confident in saying that there is indeed a moderation effect; however, if the interaction effect is no longer significant after adding the nonlinear term, we will be less certain about the existence of a moderation effect and the nonlinear model will be preferred because it is ...