Smartphone-based study reminders can be a double-edged sword.

Reminders are a popular feature in smartphone apps designed to promote desirable behaviors that are best performed regularly. But can they also promote students' regular studying? In the present study with 85 lower secondary school students aged 10-12, we combined a smartphone-based between- and within-person experimental manipulation with logfile data of a vocabulary learning app. Students were scheduled to receive reminders on 16 days during the 36-day intervention period. Findings suggest that reminders can be a double-edged sword. The within-person experimental manipulation allowed a comparison of study probability on days with and without reminders. Students were more likely to study on days they received a reminder compared to days when they did not receive a reminder. However, when compared to a control group that never received reminders, the effect was not due to students studying more frequently on days with reminders. Instead, they studied less frequently on days without reminders than students in the control group. This effect increased over the study period, with students becoming increasingly less likely to study on days without reminders. Taken together, these results suggest a detrimental side effect of reminders: students become overly reliant on them.

Do reflection prompts promote children's conflict monitoring and revision of misconceptions?

We tested whether reflection prompts enhance conflict monitoring and facilitate the revision of misconceptions. German children (N = 97, Mage = 7.20, 56% female) were assigned to a prediction or a prediction with reflection condition that included reflection prompts. Children in the prediction with reflection condition (1) showed greater error-related response times and pupil dilation responses, indicating better conflict monitoring, and (2) performed closer to an optimal Bayesian learner, indicating better monitoring-based control. However, by the end of the study, all children had similar levels of misconception revision. Thus, reflection prompts can enhance learning from anomalous evidence by improving conflict monitoring, but they may need to be repeated often to sustain their beneficial effects.

Prediction error and memory across the lifespan.

The influence of Prediction Errors (PEs) on episodic memory has generated growing empirical and theoretical interest. This review explores how the relationship between PE and memory may evolve throughout lifespan. Drawing upon the predictive processing framework and the Predictive, Interactive Multiple Memory System (PIMMS) model in particular, the paper highlights the hierarchical organization of memory systems and the interaction between top-down predictions and bottom-up sensory input, proposing that PEs promote synaptic change and improve encoding and consolidation processes. We discuss the neuroscientific mechanisms underlying PE-driven memory enhancement, focusing on the involvement of the hippocampus, the entorhinal cortex-hippocampus pathway, and the noradrenergic sympathetic system. Recognizing the divergent trajectories of episodic and semantic memory across the lifespan is crucial when examining the effects of PEs on memory. This review underscores the heterogeneity of memory processes and neurocognitive mechanisms underlying PE-driven memory enhancement across age. Future research is suggested to directly compare neural networks involved in learning from PEs across different age groups and to contribute to a deeper understanding of PE-driven learning across age.

Examining the role of attentional allocation in working memory precision with pupillometry in children and adults.

Working memory (WM) precision, or the fidelity with which items can be remembered, is an important aspect of WM capacity that increases over childhood. Why individuals are more or less precise from moment to moment and why WM becomes more stable with age are not yet fully understood. Here, we examined the role of attentional allocation in visual WM precision in children aged 8 to 13 years and young adults aged 18 to 27 years, as measured by fluctuations in pupil dilation during stimulus encoding and maintenance. Using mixed models, we examined intraindividual links between change in pupil diameter and WM precision across trials and the role of developmental differences in these associations. Through probabilistic modeling of error distributions and the inclusion of a visuomotor control task, we isolated mnemonic precision from other cognitive processes. We found an age-related increase in mnemonic precision that was independent of guessing behavior, serial position effects, fatigue or loss of motivation across the experiment, and visuomotor processes. Trial-by-trial analyses showed that trials with smaller changes in pupil diameter during encoding and maintenance predicted more precise responses than trials with larger changes in pupil diameter within individuals. At encoding, this relationship was stronger for older participants. Furthermore, the pupil-performance coupling grew across the delay period-particularly or exclusively for adults. These results suggest a functional link between pupil fluctuations and WM precision that grows over development; visual details may be stored more faithfully when attention is allocated efficiently to a sequence of objects at encoding and throughout a delay period.

Seeing the Error in My "Bayes": A Quantified Degree of Belief Change Correlates with Children's Pupillary Surprise Responses Following Explicit Predictions.

Bayesian models allow us to investigate children's belief revision alongside physiological states, such as "surprise". Recent work finds that pupil dilation (or the "pupillary surprise response") following expectancy violations is predictive of belief revision. How can probabilistic models inform the interpretations of "surprise"? Shannon Information considers the likelihood of an observed event, given prior beliefs, and suggests stronger surprise occurs following unlikely events. In contrast, Kullback-Leibler divergence considers the dissimilarity between prior beliefs and updated beliefs following observations-with greater surprise indicating more change between belief states to accommodate information. To assess these accounts under different learning contexts, we use Bayesian models that compare these computational measures of "surprise" to contexts where children are asked to either predict or evaluate the same evidence during a water displacement task. We find correlations between the computed Kullback-Leibler divergence and the children's pupillometric responses only when the children actively make predictions, and no correlation between Shannon Information and pupillometry. This suggests that when children attend to their beliefs and make predictions, pupillary responses may signal the degree of divergence between a child's current beliefs and the updated, more accommodating beliefs.

Test Anxiety Does Not Predict Exam Performance When Knowledge Is Controlled For: Strong Evidence Against the Interference Hypothesis of Test Anxiety.

Do test-anxious students perform worse in exam situations than their knowledge would otherwise allow? We analyzed data from 309 medical students who prepared for a high-stakes exam using a digital learning platform. Using log files from the learning platform, we assessed students' level of knowledge throughout the exam-preparation phase and their average performance in mock exams that were completed shortly before the final exam. The results showed that test anxiety did not predict exam performance over and above students' knowledge level as assessed in the mock exams or during the exam-preparation phase. Leveraging additional ambulatory assessment data from the exam-preparation phase, we found that high trait test anxiety predicted smaller gains in knowledge over the exam-preparation phase. Taken together, these findings are incompatible with the hypothesis that test anxiety interferes with the retrieval of previously learned knowledge during the exam.

Explicitly predicting outcomes enhances learning of expectancy-violating information.

Predictive coding models suggest that the brain constantly makes predictions about what will happen next based on past experiences. Learning is triggered by surprising events, i.e., a prediction error. Does it benefit learning when these predictions are made deliberately, so that an individual explicitly commits to an outcome before experiencing it? Across two experiments, we tested whether generating an explicit prediction before seeing numerical facts boosts learning of expectancy-violating information relative to doing so post hoc. Across both experiments, predicting boosted memory for highly unexpected outcomes, leading to a U-shaped relation between expectedness and memory. In the post hoc condition, memory performance decreased with increased unexpectedness. Pupillary data of Experiment 2 further indicated that the pupillary surprise response to highly expectancy-violating outcomes predicted successful learning of these outcomes. Together, these findings suggest that generating an explicit prediction increases learners' stakes in the outcome, which particularly benefits learning of those outcomes that are different than expected.

Predicting vs. guessing: the role of confidence for pupillometric markers of curiosity and surprise.

Asking students to generate a prediction before presenting the correct answer is a popular instructional strategy. This study tested whether a person's degree of confidence in a prediction is related to their curiosity and surprise regarding the answer. For a series of questions about numerical facts, participants (N = 29) generated predictions and rated their confidence in the prediction before seeing the correct answer. The increase in pupil size before viewing the correct answer was used as a physiological marker of curiosity, and the increase in pupil size after viewing the correct answer was used as a physiological marker of surprise. The results revealed that the pupillometric marker of curiosity was most pronounced if students were slightly more confident in their prediction than usual, and it was lower for predictions made with either very high or very low confidence. Furthermore, the results showed that high-confidence prediction errors and low-confidence correct responses yielded a pupillary surprise response, suggesting that highly unexpected results evoke surprise, independent of the correctness of the prediction. Together, results suggest that confidence in a prediction plays an important role in the occurrence of epistemic emotions such as curiosity and surprise.

Tackling Scientific Misconceptions: The Element of Surprise.

Misconceptions about scientific concepts often prevail even if learners are confronted with conflicting evidence. This study tested the facilitative role of surprise in children's revision of misconceptions regarding water displacement in a sample of German children (N = 94, aged 6-9 years, 46% female). Surprise was measured via the pupil dilation response. It was induced by letting children generate predictions before presenting them with outcomes that conflicted with their misconception. Compared to a control condition, generating predictions boosted children's surprise and led to a greater revision of misconceptions (d = 0.56). Surprise further predicted successful belief revision during the learning phase. These results suggest that surprise increases the salience of a cognitive conflict, thereby facilitating the revision of misconceptions.

Neural Correlates of Successful Memory Encoding in Kindergarten and Early Elementary School Children: Longitudinal Trends and Effects of Schooling.

From age 5 to 7, there are remarkable improvements in children's cognitive abilities ("5-7 shift"). In many countries, including Germany, formal schooling begins in this age range. It is, thus, unclear to what extent exposure to formal schooling contributes to the "5-7 shift." In this longitudinal study, we investigated if schooling acts as a catalyst of maturation. We tested 5-year-old children who were born close to the official cutoff date for school entry and who were still attending a play-oriented kindergarten. One year later, the children were tested again. Some of the children had experienced their first year of schooling whereas the others had remained in kindergarten. Using 2 functional magnetic resonance imaging tasks that assessed episodic memory formation (i.e., subsequent memory effect), we found that children relied strongly on the medial temporal lobe (MTL) at both time points but not on the prefrontal cortex (PFC). In contrast, older children and adults typically show subsequent memory effects in both MTL and PFC. Both children groups improved in their memory performance, but there were no longitudinal changes nor group differences in neural activation. We conclude that successful memory formation in this age group relies more heavily on the MTL than in older age groups.

Predicting as a learning strategy.

This article attempts to delineate the procedural and mechanistic characteristics of predicting as a learning strategy. While asking students to generate a prediction before presenting the correct answer has long been a popular learning strategy, the exact mechanisms by which it improves learning are only beginning to be unraveled. Moreover, predicting shares many features with other retrieval-based learning strategies (e.g., practice testing, pretesting, guessing), which begs the question of whether there is more to it than getting students to engage in active retrieval. I argue that active retrieval as such does not suffice to explain beneficial effects of predicting. Rather, the effectiveness of predicting is also linked to changes in the way the ensuing feedback is processed. Initial evidence suggests that predicting boosts surprise about unexpected answers, which leads to enhanced attention to the correct answer and strengthens its encoding. I propose that it is this affective aspect of predicting that sets it apart from other retrieval-based learning strategies, particularly from guessing. Predicting should thus be considered as a learning strategy in its own right. Studying its unique effects on student learning promises to bring together research on formal models of learning from prediction error, epistemic emotions, and instructional design.

Which Data Do Elementary School Teachers Use to Determine Reading Difficulties in Their Students?

Small-group interventions allow for tailored instruction for students with learning difficulties. A crucial first step is the accurate identification of students who need such an intervention. This study investigated how teachers decide whether their students need a remedial reading intervention. To this end, 64 teachers of 697 third-grade students from Germany were asked to rate whether a reading intervention for their students was "not necessary," "potentially necessary," or "definitely necessary." Independent experimenters tested the students' reading and spelling abilities with standardized tests, and a subsample of 370 children participated in standardized tests of phonological awareness and vocabulary. Findings show that teachers' decisions with regard to students' needing a reading intervention overlapped more with results from standardized spelling assessments than from reading assessments. Hierarchical linear models indicated that students' spelling abilities, along with phonological awareness and vocabulary, explained variance in teachers' ratings over and above students' reading skills. Teachers thus relied on proximal cues such as spelling skills to reach their decision. These findings are discussed in relation to clinical standards and educational contexts. Findings indicate that the teachers' assignment of children to interventions might be underspecified, and starting points for specific teacher training programs are outlined.

Cognitive Prerequisites for Generative Learning: Why Some Learning Strategies Are More Effective Than Others.

This study examined age-related differences in the effectiveness of two generative learning strategies (GLSs). Twenty-five children aged 9-11 and 25 university students aged 17-29 performed a facts learning task in which they had to generate either a prediction or an example before seeing the correct result. We found a significant Age × Learning Strategy interaction, with children remembering more facts after generating predictions rather than examples, whereas both strategies were similarly effective in adults. Pupillary data indicated that predictions stimulated surprise, whereas the effectiveness of example-based learning correlated with children's analogical reasoning abilities. These findings suggest that there are different cognitive prerequisites for different GLSs, which results in varying degrees of strategy effectiveness by age.

Being proven wrong elicits learning in children - but only in those with higher executive function skills.

This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9-12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive functions (EF). In Experiment 1, we showed that children exhibited a pupillary surprise response to events that they had predicted incorrectly, hypothesized to reflect the transient release of noradrenaline in response to cognitive conflict. However, children's surprise response was not associated with better belief revision, in contrast to a previous study involving adults. Experiment 2 revealed that, while generating predictions helped children activate their prior knowledge, only those with better inhibitory control skills learned from incorrectly predicted outcomes. Together, these results suggest that good inhibitory control skills are needed for learning through cognitive conflict. Thus, generating predictions benefits learning - but only among children with sufficient EF capacities to harness surprise for revising their beliefs.

Lighting the wick in the candle of learning: generating a prediction stimulates curiosity.

Curiosity stimulates learning. We tested whether curiosity itself can be stimulated-not by extrinsic rewards but by an intrinsic desire to know whether a prediction holds true. Participants performed a numerical-facts learning task in which they had to generate either a prediction or an example before rating their curiosity and seeing the correct answer. More facts received high-curiosity ratings in the prediction condition, which indicates that generating predictions stimulated curiosity. In turn, high curiosity, compared with low curiosity, was associated with better memory for the correct answer. Concurrent pupillary data revealed that higher curiosity was associated with larger pupil dilation during anticipation of the correct answer. Pupil dilation was further enhanced when participants generated a prediction rather than an example, both during anticipation of the correct answer and in response to seeing it. These results suggest that generating a prediction stimulates curiosity by increasing the relevance of the knowledge gap.

A boon and a bane: Comparing the effects of prior knowledge on memory across the lifespan.

We tested 6- to 7-year-olds, 18- to 22-year-olds, and 67- to 74-year-olds on an associative memory task that consisted of knowledge-congruent and knowledge-incongruent object-scene pairs that were highly familiar to all age groups. We compared the 3 age groups on their memory congruency effect (i.e., better memory for knowledge-congruent associations) and on a schema bias score, which measures participants' tendency to commit knowledge-congruent memory errors. We found that prior knowledge similarly benefited memory for items encoded in a congruent context in all age groups. However, for associative memory, older adults and, to a lesser extent, children overrelied on their prior knowledge, as indicated by an enhanced congruency effect and schema bias. Functional MRI (fMRI) performed during memory encoding revealed an age-independent Memory × Congruency interaction in the ventromedial prefrontal cortex (vmPFC). Furthermore, the magnitude of vmPFC recruitment correlated positively with the schema bias. These findings suggest that older adults are most prone to rely on their prior knowledge for episodic memory decisions, but that children can also rely heavily on prior knowledge that they are well acquainted with. Furthermore, the fMRI results suggest that the vmPFC plays a key role in the assimilation of new information into existing knowledge structures across the entire life span. vmPFC recruitment leads to better memory for knowledge-congruent information but also to a heightened susceptibility to commit knowledge-congruent memory errors, in particular in children and older adults. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Specifying the role of the ventromedial prefrontal cortex in memory formation.

Recent neuroimaging research suggests that the ventromedial prefrontal cortex (vmPFC) plays an important role for successful memory formation that takes place in the context of activated prior knowledge. These findings led to the notion that the vmPFC integrates new information into existing knowledge structures. However, a considerable number of neuroimaging studies that have investigated memory formation in the context of prior knowledge have not found vmPFC involvement. To resolve this inconsistency, we propose a distinction between knowledge-relevance (the degree to which new information can be linked to prior knowledge) and knowledge-congruency (the perceived match between prior knowledge and the to-be-encoded information). We hypothesized that the vmPFC contributes to successful memory formation only when perceived knowledge-congruency is high, independent of knowledge-relevance. We tested this hypothesis in a design that varied both congruency and relevance during memory encoding, which was performed in the MR scanner. As predicted, the results showed that vmPFC contributions to memory formation vary as a function of knowledge-congruency, but not as a function of knowledge-relevance. Our finding contributes to elucidating the seemingly inconsistent findings in the literature and helps to specify the role of the vmPFC in memory formation.