Judgments of Learning Reactively Improve Memory by Enhancing Learning Engagement and Inducing Elaborative Processing: Evidence from an EEG Study.

Making judgments of learning (JOLs) can reactively alter memory itself, a phenomenon termed the reactivity effect. The current study recorded electroencephalography (EEG) signals during the encoding phase of a word list learning task to explore the neurocognitive features associated with JOL reactivity. The behavioral results show that making JOLs reactively enhances recognition performance. The EEG results reveal that, compared with not making JOLs, making JOLs increases P200 and LPC amplitudes and decreases alpha and beta power. Additionally, the signals of event-related potentials (ERPs) and event-related desynchronizations (ERDs) partially mediate the reactivity effect. These findings support the enhanced learning engagement theory and the elaborative processing explanation to account for the JOL reactivity effect.

Confidence ratings increase response thresholds in decision making.

Many mental processes are reactive - they are altered as a result of introspection and monitoring. It has been documented that soliciting trial-by-trial confidence ratings (CRs) reactively improves decision accuracy and lengthens response times (RTs), but the cognitive mechanisms underlying CR reactivity in decision-making remain unknown. The current study conducted two experiments and employed the drift-diffusion model (DDM) to explore why reporting confidence reactively alters the decision-making process. The results showed that CRs led to enhanced decision accuracy, longer RTs, and higher response thresholds. The findings are consistent with an increased conservatism hypothesis which asserts that soliciting CRs provokes feelings of uncertainty and makes individuals more cautious in their decision making.

Soliciting judgments of forgetting reactively enhances memory as well as making judgments of learning: Empirical and meta-analytic tests.

Recent studies found that making judgments of learning (JOLs) can reactively facilitate memory, a phenomenon termed the reactivity effect of JOLs. The current study was designed to explore (1) whether making judgments of forgetting (JOFs) can also enhance memory and (2) whether there is any difference between the reactivity effects of JOFs and JOLs. Experiment 1 found that soliciting JOFs significantly enhanced retention of single words. Experiments 2 and 3 observed minimal difference in reactivity effects between JOFs and JOLs on learning of single words and word pairs. Finally, a meta-analysis was conducted to integrate results across studies to explore whether retention of items studied with JOLs differed from that of items studied with JOFs. The meta-analytic results showed minimal difference. Overall, the documented findings imply that (1) making JOFs reactively enhances memory, and (2) there is little difference in reactivity effects between JOFs and JOLs. These findings support the positive-reactivity theory to account for the reactivity effect.

When judging what you know changes what you really know: Soliciting metamemory judgments reactively enhances children's learning.

Recent studies established that making concurrent judgments of learning (JOLs) can significantly alter (typically enhance) memory itself-a reactivity effect. The current study recruited 190 Chinese children (Mage  = 8.68 years; 101 female) in 2020 and 2021 to explore the reactivity effect on children's learning, its developmental trajectory and associated metacognitive awareness. The results showed that making JOLs significantly enhanced retention for students in Grades 1, 3, and 5, with Cohen's ds ranging from 0.40 to 1.33. Grade 5 students exhibited a larger reactivity effect than Grade 1 and 3 students. Children's metacognitive appreciation of the effect was weak. Firsthand experience of the reactivity effect, induced by taking a memory test, enhanced their awareness and calibrated their judgment accuracy.

The contribution of metamemory beliefs to the font size effect on judgments of learning: Is word frequency a moderating factor?

Previous studies found that metamemory beliefs dominate the font size effect on judgments of learning (JOLs). However, few studies have investigated whether beliefs about font size contribute to the font size effect in circumstances of multiple cues. The current study aims to fill this gap. Experiment 1 adopted a 2 (font size: 70 pt vs. 9 pt) * 2 (word frequency (WF): high vs. low) within-subjects design. The results showed that beliefs about font size did not mediate the font size effect on JOLs when multiple cues (font size and WF) were simultaneously provided. Experiment 2 further explored whether WF moderates the contribution of beliefs about font size to the font size effect, in which a 2 (font size: 70 pt vs. 9 pt, as a within-subjects factor) * 2 (WF: high vs. low, as a between-subjects factor) mixed design was used. The results showed that the contribution of beliefs about font size to the font size effect was present in a pure list of low-frequency words, but absent in a pure list of high-frequency words. Lastly, a meta-analysis showed evidence supporting the proposal that the contribution of beliefs about font size to the font size effect on JOLs is moderated by WF. Even though numerous studies suggested beliefs about font size play a dominant role in the font size effect on JOLs, the current study provides new evidence suggesting that such contribution is conditional. Theoretical implications are discussed.

A Bayesian inference model for metamemory.

The dual-basis theory of metamemory suggests that people evaluate their memory performance based on both processing experience during the memory process and their prior beliefs about overall memory ability. However, few studies have proposed a formal computational model to quantitatively characterize how processing experience and prior beliefs are integrated during metamemory monitoring. Here, we introduce a Bayesian inference model for metamemory (BIM) which provides a theoretical and computational framework for the metamemory monitoring process. BIM assumes that when people evaluate their memory performance, they integrate processing experience and prior beliefs via Bayesian inference. We show that BIM can be fitted to recall or recognition tasks with confidence ratings on either a continuous or discrete scale. Results from data simulation indicate that BIM can successfully recover a majority of generative parameter values, and demonstrate a systematic relationship between parameters in BIM and previous computational models of metacognition such as the stochastic detection and retrieval model (SDRM) and the meta-d' model. We also show examples of fitting BIM to empirical data sets from several experiments, which suggest that the predictions of BIM are consistent with previous studies on metamemory. In addition, when compared with SDRM, BIM could more parsimoniously account for the data of judgments of learning (JOLs) and memory performance from recall tasks. Finally, we discuss an extension of BIM which accounts for belief updating, and conclude with a discussion of how BIM may benefit metamemory research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Levels of retrieval and the testing effect.

Retrieval enhances subsequent memory more than restudy (i.e., the testing effect), demonstrating the encoding (or reencoding) effects of retrieval. It is important to delineate the nature of the encoding effects of retrieval especially in comparison to traditional encoding processes. The current study examined if the level of retrieval, analogous to the level of processing during encoding, has an effect on subsequent memory. In 4 experiments, participants studied short lists of words, each followed by a retrieval or restudy trial. A final free recall test was given at the end of the experiment. The level of retrieval was manipulated by asking participants to retrieve words with a semantic or phonemic cue in the retrieval trial. In order to isolate the effects of retrieval per se, the semantic or phonemic cue was also presented in the restudy trial. Experiment 1 manipulated levels of retrieval (and restudy) between subjects while Experiment 2 manipulated levels within subjects. Experiment 3 sought to enhance the levels effect by adding an overt levels judgment, and Experiment 4 sought to rule out an alternative account of the equality of the testing effects across levels by increasing the list length. In all 4 experiments, a robust testing effect was obtained but it was not moderated by level of retrieval, a result supported by a small-scale meta-analysis, which demonstrated an overall effect of levels and testing condition, but no interaction. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Using Multilevel Mediation Model to Measure the Contribution of Beliefs to Judgments of Learning.

Recent studies on judgments of learning (JOLs) suggest that beliefs play an important role in the formation of JOLs. The current article introduces a multilevel mediation model to quantify the contribution of beliefs to JOL formation when both JOLs and global belief-based predictions are measured from the same group of participants. Our examples of fitting the multilevel mediation model to hypothetical and published datasets revealed that it is feasible to use the multilevel mediation model to examine the mediation effect of beliefs on the relationship between a cue and JOLs, and quantitatively compare the effects of beliefs and processing fluency on JOLs in one model. Then we compared the current multilevel mediation model and the multilevel moderation model implemented in previous studies, and discussed their similarities and differences. Finally, a data simulation was performed to explain the inflation of Type I error for the multilevel mediation model when we regress global belief-based predictions on the cue, and suggestions about appropriate steps for conducting multilevel mediation analysis are proposed.

How font size affects judgments of learning: Simultaneous mediating effect of item-specific beliefs about fluency and moderating effect of beliefs about font size and memory.

Numerous studies have provided experience-based or theory-based frameworks for the basis of judgment of learning (JOL). However, few studies have directly measured processing experience and beliefs related to the same cue in one experiment and examined their joint contribution to JOLs. The present study focused on font-size effects and aimed to examine the simultaneous contribution of processing fluency and beliefs to the effect of font size on JOLs. We directly measured processing fluency via self-paced study time. We also directly measured participants' beliefs via two approaches: pre-study global differentiated predictions (GPREDs) as an indicator of preexisting beliefs about font size and memory and ease of learning judgments (EORs) as online generated item-specific beliefs about fluency. In Experiment 1, EORs partially mediated the font-size effect, whereas self-paced study time did not. In Experiments 2a and 2b, EORs mediated the font-size effect; at the same time, beliefs about font size and memory moderated the font-size effect. In summary, the present study demonstrates a major role of beliefs underlying the font-size effect.

Individual Differences in the Accuracy of Judgments of Learning Are Related to the Gray Matter Volume and Functional Connectivity of the Left Mid-Insula.

The judgment of learning (JOL) is an important form of prospective metamemory judgment, and the biological basis of the JOL process is an important topic in metamemory research. Although previous task-related functional magnetic resonance imaging (MRI) studies have examined the brain regions underlying the JOL process, the neural correlates of individual differences in JOL accuracy require further investigation. This study used structural and resting-state functional MRI to investigate whether individual differences in JOL accuracy are related to the gray matter (GM) volume and functional connectivity of the bilateral insula and medial Brodmann area (BA) 11, which are assumed to be related to JOL accuracy. We found that individual differences in JOL accuracy were related to the GM volume of the left mid-insula and to the functional connectivity between the left mid-insula and various other regions, including the left superior parietal lobule/precuneus, bilateral inferior parietal lobule/intraparietal sulcus, right frontal pole and left parahippocampal gyrus/fusiform gyrus/cerebellum. Further analyses indicated that the functional connectivity related to individual differences in JOL accuracy could be divided into two factors and might support information integration and selective attention processes underlying accurate JOLs. In addition, individual differences in JOL accuracy were not related to the GM volume or functional connectivity of the medial BA 11. Our findings provide novel evidence for the role of the left mid-insula and its functional connectivity in the JOL process.

The influence of visual mental imagery size on metamemory accuracy in judgment of learning.

Many studies have found the font size of to-be-remembered words has a significant influence on judgments of learning (JOLs). However, few studies have investigated whether JOLs are affected by the mental imagery size of to-be-remembered words, even when the font sizes themselves are kept identical in study materials. This study investigated whether the visual mental imagery size influences the participants' JOLs and what the underlying mechanisms are. In Experiments 1 and 2, participants learned words with identical font sizes, mentally generated large or small imageries and then made JOLs. We found that JOLs under the large imagery condition were significantly higher than those under the small imagery condition, but actual recall performance exhibited no significant difference. In Experiment 3, participants pressed a button immediately after mental imagery generation and showed that it took significantly longer to generate large imageries than to generate small imageries, and the difference in JOLs between two conditions was no longer significant. In Experiment 4, we used a questionnaire to investigate the contribution of beliefs and found that participants believed large imageries were easier to remember. These findings indicate that imagery size has a significant impact on JOLs, in which beliefs may play a leading role.

How Much Do Metamemory Beliefs Contribute to the Font-Size Effect in Judgments of Learning?

Evidence shows that the font size of study items significantly influences judgments of learning (JOLs) and that people's JOLs are generally higher for larger words than for smaller words. Previous studies have suggested that font size influences JOLs in a belief-based way. However, few studies have directly examined how much people's beliefs contribute to the font-size effect in JOLs. This study investigated the degree to which font size influenced JOLs in a belief-based way. In Experiment 1, one group of participants (learners) studied words with different font sizes and made JOLs, whereas another group of participants (observers) viewed the learners' study phase and made JOLs for the learners. In Experiment 2, participants made both JOLs and belief-based recall predictions for large and small words. Our results suggest that metamemory beliefs play an important role in the font-size effect in JOLs.