Rising interest in artificial intelligence in education reinforces the demand for evidence-based implementation. This study investigates how tutor agents' physical embodiment and anthropomorphism (student-reported sociability, animacy, agency, and disturbance) relate to affective (on-task enjoyment) and cognitive (task performance) learning within an intelligent tutoring system (ITS). Data from 56 students (M = 17.75 years, SD = 2.63 years; 30.4% female), working with an emotionally-adaptive version of the ITS "Betty's Brain", were analyzed. The ITS' agents were either depicted as on-screen robots (condition A) or as both on-screen avatars and physical robots (condition B). Physical presence of the tutor agent was not significantly related to task performance or anthropomorphism, but to higher initial on-task enjoyment. Student-reported disturbance was negatively related to initial on-task enjoyment, and student-reported sociability was negatively related to task performance. While physical robots may increase initial on-task enjoyment, students' perception of certain characteristics may hinder learning, providing implications for designing social robots for education.

The COVID-19 pandemic resulted in significant disruption in schooling worldwide. Global test score data is used to estimate learning losses by modeling the effect of school closures on achievement by predicting the deviation of the most recent results from a linear trend using data from all rounds of PISA. Mathematics scores declined an average of 14 percent of a standard deviation, roughly equal to seven months of learning. Losses are greater for students in schools that faced relatively longer closures, for boys, immigrants, and disadvantaged students. Educational losses may translate into significant national income losses over time.

Observational learning enables us to make decisions by watching others' behaviors. The quality of such learning depends on the abilities of those we observe, but also on our beliefs about those abilities. We have previously demonstrated that observers learned better from demonstrators described as high vs. low in ability, regardless of their actual performance. The current study aimed to conceptually replicate these findings, and explore the neural mechanisms involved. Forty-five participants performed an observational learning task while undergoing functional magnetic resonance imaging (fMRI). We hypothesized that participants would perform better when demonstrators were described as having high vs. low ability. Unexpectedly, participants performed equally well regardless of described demonstrator ability. The behavioral effects of biased observational learning seem to be driven by mentalizing processes together with general learning and decision-making processes.

New information that is compatible with pre-existing knowledge can be learned faster. Such schema memory effect has been reported in declarative memory and in explicit motor sequence learning (MSL). Here, we investigated if sequences of key presses that were compatible to previously trained ones, could be learned faster in an implicit MSL task. Participants trained a motor sequence before switching to a completely new sequence, to a compatible sequence with high overlap in ordinal positions, or to an incompatible sequence with low overlap, while the compatible and incompatible sequences had the same overlap in movement transitions. We observed accelerated learning in the Compatible and Incompatible groups compared to the New group, if participants trained for 3 sessions before switching to the altered sequence. Overall, our study suggests facilitative learning of implicit motor sequences that are compatible in movement transitions, if the previous sequence has been trained extensively.

Statistical learning is a core ability for individuals in extracting and integrating regularities and patterns from linguistic input. Yet, the developmental trajectory of visual statistical learning has not been fully examined in the orthographic learning domain. Employing an artificial orthographic learning task, we manipulated three levels of positional consistency of radicals, i.e., high (100%), moderate (80%), and low (60%), embedded in pseudocharacters to investigate visual statistical learning across a wide age range between 4-12-year-olds and adults. The non-linear power-function models indicated that the rates of improvement in acquiring varying positional consistencies increased with age, particularly for high and moderate levels. Specifically, we observed a significant enhancement in statistical learning abilities between the ages of 4-5 years and 5-6 years, followed by a stabilization of performance after 8-9 years. Our findings support the age-dependent perspective that individuals' visual statistical learning ability improves significantly in early childhood and then decelerates its improvement progressively until adulthood.

Studies have found that flipped classroom teaching (FT) improves learning compared to lecture-based teaching (LT). However, whether the structured teacher-student interaction-the key feature of FT-plays an essential role in enhancing learning remains unclear, as do its neural underpinnings. Here, we compared three teaching conditions: FT with a video lecture and structured interaction, LT with a face-to-face lecture and spontaneous interaction, and control teaching (CT) with a video lecture and spontaneous interaction. The fNIRS-based hyperscanning technique was used to assess the interbrain synchrony (IBS) from teacher-student dyads. Results showed that the learning was significantly improved in FT than in LT and CT, and FT significantly increased teacher-student IBS in left DLPFC. Moreover, the IBS and learning improvements were positively correlated. Therefore, these findings indicate that the structured teacher-student interaction is crucial for enhancing learning in FT, and IBS serves as its neural foundation.

This study investigated whether transcranial direct current stimulation (tDCS) targeting the inferior frontal gyrus (IFG) can alter the thinking process and neural basis of creativity. Participants' performance on the compound remote associates (CRA) task was analyzed considering the semantic features of each trial after receiving different tDCS protocols (left cathodal and right anodal, L + R-; right cathodal and left anodal, L-R+; and Sham). Moreover, we constructed and compared 80 prediction models of CRA performance for each group based on task-related functional connectivity. Results showed that L + R- stimulation improved performance in semantically bundled CRA trials, while L-R+ stimulation enhanced performance in trials with greater semantic distance. Furthermore, alpha-band task connectivity models for the L + R- group showed inferior performance and greater left frontal lateralization than other two groups. These findings suggest that tDCS targeting the bilateral IFG alters cognitive processes during creative ideation rather than enhancing or impairing an established thinking process.

The primary motor cortex (M1) is crucial for motor skill learning. We examined its role in interleaved practice, which enhances retention (vs. repetitive practice) through M1-dependent consolidation. We hypothesized that cathodal transcranial direct current stimulation (ctDCS) to M1 would disrupt retention. We found that ctDCS reduced retention due to weakened encoding during acquisition, not disrupted consolidation. These results highlight M1's broad role in encoding and retention of novel motor skills.

Perception and perceptual memory play crucial roles in fear generalization, yet their dynamic interaction remains understudied. This research (N = 80) explored their relationship through a classical differential conditioning experiment. Results revealed that while fear context perception fluctuates over time with a drift effect, perceptual memory remains stable, creating a disjunction between the two systems. Surprisingly, this disjunction does not significantly impact fear generalization behavior. Although most participants demonstrated generalization aligned with perceptual rather than physical stimulus distances, incorporating perceptual memory data into perceptual distance calculations did not enhance model performance. This suggests a potential shift in the mapping of the perceptual memory component of fear context, occurring alongside perceptual dynamics. Overall, this work provides evidence for understanding fear generalization behavior through different stimulus representational processes. Such mechanistic investigations can enhance our understanding of how individuals behave when facing threats and potentially aid in developing mechanism-specific diagnoses and treatments.

This study evaluates the ability of large language models (LLMs) to deliver criterion-based grading and examines the impact of prompt engineering with detailed criteria on grading. Using well-established human benchmarks and quantitative analyses, we found that even free LLMs achieve criterion-based grading with a detailed understanding of the criteria, underscoring the importance of domain-specific understanding over model complexity. These findings highlight the potential of LLMs to deliver scalable educational feedback.

Generalization is central to motor learning. However, few studies are on the learning generalization of BCI-actuated supernumerary robotic finger (BCI-SRF) for human-machine interaction training, and no studies have explored its longitudinal neuroplasticity mechanisms. Here, 20 healthy right-handed participants were recruited and randomly assigned to BCI-SRF group or inborn finger group (Finger) for 4-week training and measured by novel SRF-finger opposition sequences and multimodal MRI. After training, the BCI-SRF group showed 350% times compared to the Finger group in the improvement of sequence opposition accuracy before and after training, and accompanied by significant functional connectivity increases in the sensorimotor region and prefrontal cortex, as well as in the intra- and inter-hemisphere of the sensorimotor network. Moreover, Granger Causality Analysis identified causal effect main transfer within the sensorimotor cortex-cerebellar-thalamus loop and frontal-parietal loop. The findings suggest that BCI-SRF training enhances motor sequence learning ability by influencing the functional reorganization of sensorimotor network.

Analysis of linguistic abilities that are concurrently impaired in individuals with language deficits allows identification of a shared underlying mechanism. If any two linguistic abilities are mediated by the same underlying mechanism, then both abilities will be absent if this mechanism is broken. Clustering techniques automatically arrange these abilities according to their co-occurrence and therefore group together abilities mediated by the same mechanism. This study builds upon the discovery of three distinct mechanisms of language comprehension in 31,845 autistic individuals. The current clustering analysis of a more diverse group of individuals with language impairments resulted in the three mechanisms identical to those found previously: (1) the most-basic command-language-comprehension-mechanism; (2) the intermediate modifier-language-comprehension-mechanism mediating comprehension of color, size, and number modifiers; and (3) the most-advanced syntactic-language-comprehension-mechanism. This discovery calls for mapping of the three empirically-defined language-comprehension-mechanisms in the context of cognitive neuroscience, which is the main goal of this study.

Mobile devices are ubiquitous, but their potential for adaptive educational interventions remains largely untapped. We identify three key promises of mobile interventions for educational research and practice: 1) intervening when it is most beneficial (i.e., "just-in-time adaptivity"), 2) estimating causal effects of interventions in ecologically valid settings, 3) considering the impact of context on the effectiveness of interventions. We discuss the challenges and next steps to advance this field.

The debate about whether the capacity of working memory (WM) varies with the complexity of memory items continues. This study employed novel experimental materials to investigate the role of complexity in WM capacity. Across seven experiments, we explored the relationship between complexity and WM capacity. The results indicated that the complexity of memory items significantly affects WM capacity. However, given the non-linear relationship between complexity and WM capacity, we propose that WM may not allocate resources directly to each individual item. Instead, it might integrate these items to some extent before storage.

To examine the combined effects of maths anxiety (MA), maths self-efficacy (MSE), and maths interest (MI) on STEM career choice, we analysed self-report data from 7908 Twins Early Development Study participants, collected at ages 16 (MSE, MI), 18 (MA) and 21 (STEM career choice). When analysed in the same model, MSE did not independently predict STEM career choice. MI (OR = 1.75) was a stronger predictor than MA (OR = 0.79), which was not significant after controlling for maths achievement. MI was a significant positive predictor of STEM career choices for both males (OR = 1.88) and females (OR = 1.77). However, MA was only predictive for males (OR = 0.62), and MSE was only predictive for females in the unadjusted model (OR = 1.77). These results highlight the importance of nurturing maths interest to bridge the STEM skills gap, regardless of sex. Future research should consider the co-development of maths-related psychological constructs to further understand their influence on STEM career paths.

While statistical learning is often studied individually, its collective representation through self-other integration remains unclear. This study examines dynamic self-other integration and its multi-brain mechanism using simultaneous recordings from dyads. Participants (N = 112) each repeatedly responded to half of a fixed stimulus sequence with either an active partner (joint context) or a passive observer (baseline context). Significant individual statistical learning was evident in the joint context, characterized by decreased reaction time (RT) and intra-brain neural responses, followed by a quadratic trend (i.e., first increasing and then decreasing) upon insertion of an interference sequence. More importantly, Brain-to-Brain Coupling (BtBC) in the theta band also showed learning and modulation-related trends, with its slope negatively and positively correlating with the slopes of RT and intra-brain functional connectivity, respectively. These results highlight the dynamic nature of self-other integration in joint statistical learning, with statistical regularities implicitly and spontaneously modulating this process. Notably, the BtBC serves as a key neural correlate underlying the dynamics of self-other integration.

Older adults struggle with tasks requiring selective attention amidst distractions. Experimental observations about age-related decline have relied on visual search designs using static displays. However, natural environments often embed dynamic structures that afford proactive anticipation of task-relevant information. We investigate the capacity to benefit from spatiotemporal predictions across the adult lifespan. Participants (N = 300, aged 20-80) searched for multiple targets that faded in and out of displays among distractors. Half of the targets appeared at a fixed time and approximate location, whereas others appeared unpredictably. Overall search performance was reduced with age. Nevertheless, prediction-led behaviour, reflected in a higher detection of predictable targets, remained resistant to aging. Predictions were most pronounced when targets appeared in quick succession. When evaluating response speed, predictions were also significant but reduced with progressing age. While our findings confirm an age-related decline, we identified clear indications for proactive attentional guidance throughout adulthood.

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF ValMet polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF ValMet polymorphism, suggesting less efficient learning in Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior.

Using register data and linked student-level sociometric survey data from the Netherlands, this study examines whether the impact of the COVID-19 pandemic on schooling outcomes (track recommendation and track enrollment in the seventh and ninth grades) is conditional on students' academic and social embeddedness in the school setting. We estimated the counterfactual outcomes for the cohort that went through the school transition during the pandemic based on the outcomes of the pre-pandemic cohort, with similar earlier achievements, schools, and social backgrounds. Results show that the pandemic's effect on tracking outcomes is weaker than its effect on student test scores elsewhere reported. Nevertheless, the pandemic has had stronger adverse impact on disadvantaged students. Moreover, student self-efficacy, academic motivation, and parental involvement are related to more negligible negative pandemic effects on schooling outcomes. We find no evidence for an association between student grit or parental network centrality and the magnitude of estimated pandemic effects.

Healthy aging often entails a decline in cognitive and motor functions, affecting independence and quality of life in older adults. Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried to identify responders and non-responders through correlations between behavioral change and baseline parameters, but results lack generalization to independent cohorts. We propose a method to predict an individual's likelihood of benefiting from stimulation, based on baseline performance of a sequential motor task. Our results show that individuals with less efficient learning mechanisms benefit from stimulation, while those with optimal learning strategies experience none or even detrimental effects. This differential effect, first identified in a public dataset and replicated here in an independent cohort, was linked to one's ability to integrate task-relevant information and not age. This study constitutes a further step towards personalized clinical-translational interventions based on brain stimulation.