Judgments of Learning Following Retrieval Practice Produce Minimal Reactivity Effect on Learning of Education-Related Materials
Testing (i.e., retrieval practice) is one of the most powerful strategies to boost learning. A recent study observed an incidental finding that making judgments of learning (JOLs) following retrieval practice further enhanced learning of education-related texts to a medium extent (Cohen’s d = 0.44)...
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Veröffentlicht in: | Journal of intelligence 2023-09, Vol.11 (10), p.190 |
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Sprache: | eng |
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Zusammenfassung: | Testing (i.e., retrieval practice) is one of the most powerful strategies to boost learning. A recent study observed an incidental finding that making judgments of learning (JOLs) following retrieval practice further enhanced learning of education-related texts to a medium extent (Cohen’s d = 0.44) by comparison with retrieval practice itself, suggesting that making JOLs may serve as an easy-to-implement educational intervention to improve the benefits of testing. Three experiments (one pre-registered) were conducted to test the replicability of Ariel et al.’s incidental finding and to further determine whether making JOLs following retrieval practice reactively enhances the benefits of testing for text learning. The three experiments consistently provided Bayesian evidence supporting no reactivity effect of JOLs following retrieval practice, regardless of whether the replication experiments were conducted in a laboratory (Experiment 1) or online (Experiments 2 and 3), whether the stimuli were presented in the same language (Experiments 2 and 3) or not (Experiment 1), and whether participants were recruited from the sample pool (Experiment 2) or not (Experiments 1 and 3) as in the original study. These null findings imply that making JOLs cannot be utilized as a practical strategy to enhance the benefits of testing for learning of educationally related materials. Possible explanations for the null reactivity effect of JOLs following retrieval practice are discussed. |
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ISSN: | 2079-3200 2079-3200 |
DOI: | 10.3390/jintelligence11100190 |