The level and development of cognitive ability are associated with parental socioeconomic status (SES). Some of these cognitive differences are presumably due to individual differences in genetic predispositions, but the potential mechanisms and influencing factors are still relatively unclear. Previous research has identified factors that show a relation with both cognitive abilities and SES (e.g., parental cognitive ability, home environment, and polygenic scores). Regarding these factors, we analysed three age cohorts (N = 6715; 5, 11, and 17 years old) at a 6-year interval using multiple regressions and decomposition analyses. Firstly, results indicated that cognitive differences linked to SES emerged particularly between the ages of 5 and 11. A substantial part of the SES effect was associated with parental cognitive ability. Secondly, particularly in the oldest cohort, the polygenic score for cognitive ability was related to the SES-associated change in cognitive ability. Finally, in several analyses, the influence of SES on cognitive ability was no longer significant after considering the attendance of the academic track in secondary school. This pattern could indicate that SES-associated differences in secondary school recommendations shown in previous studies may also be associated with SES-related differences in cognitive ability, which should be investigated in future studies.

Children with Autism Spectrum Disorder (ASD) frequently exhibit marked impairments in nonverbal communication, particularly in eye contact, which serves as a foundational element for social interaction and relational development. This study evaluated the effectiveness of an early intervention program utilizing interactive games supported by Augmented Reality (AR) technology to enhance eye contact behaviors, specifically initiation and maintenance, in children with autism. Using a multiple baseline across participants single-case experimental design, four boys (aged 5-7 years) diagnosed with ASD participated in an 8-week intervention at a specialized center in Saudi Arabia. The intervention featured tablet-based, gamified AR tasks incorporating real-time visual feedback, graduated difficulty levels, and reinforcement mechanisms designed to elicit social gaze and sustained eye contact. Eye contact duration and frequency were measured during structured social interactions via systematic direct observation. The results demonstrated significant improvements across all participants, with the mean duration of eye contact increasing from a baseline of 2.0 s to 5.8 s post-intervention. Visual analysis revealed robust treatment effects, further supported by substantial Tau-U effect sizes (range = 0.89-0.96; M = 0.93). Follow-up data collected three weeks post-intervention confirmed the maintenance of gains for three of the four participants. These findings suggest that AR-based interventions provide an effective and culturally responsive approach for enhancing specific nonverbal communication behaviors among children with autism in Middle Eastern contexts. Implications for clinical practice and directions for future research are discussed.

Out-of-school tutoring, as a form of privatized compensatory education beyond formal schooling, has become increasingly prevalent, yet its role in fostering students' holistic competencies remains insufficiently examined. Drawing on a student engagement perspective, this study investigates how different types of out-of-school tutoring, including academic, arts, and sports tutoring, are associated with the development of students' holistic competencies. Data were drawn from a survey of 704 Grade 10 students in central China. Tutoring engagement during junior secondary school was measured using a self-developed Likert-scale instrument, while holistic competencies were obtained from official Comprehensive Quality Assessment records. The findings reveal differentiated effects across tutoring types. Academic tutoring shows no significant association with academic performance or other dimensions of holistic competence. In contrast, sports tutoring is positively associated with physical and mental health, and arts tutoring demonstrates a significant positive relationship with artistic literacy. Regarding engagement characteristics, simply increasing the number of programs or financial investment yields limited benefits. Instead, time investment and cognitive involvement in sports tutoring, as well as affective involvement in arts tutoring, are positively related to specific dimensions of holistic competence. These results suggest that the effectiveness of out-of-school tutoring depends less on participation amount and more on the nature of students' engagement. The study highlights the uneven developmental returns of compensatory education and calls for a more balanced and development-oriented approach to tutoring participation.

This study examined how working memory, attention control, and frequency of ChatGPT-4 use are structurally associated with vocabulary retention in foreign language learning. A quantitative cross-sectional survey design was employed, with data collected from 1002 EFL learners via stratified random sampling. Validated self-report instruments measured working memory, attention control, frequency of ChatGPT use, and vocabulary retention (immediate recall, delayed retention, semantic integration, and productive use). Structural equation modelling was used to test the proposed model. The results showed that working memory was strongly associated with attention control and exerted a direct effect on vocabulary retention across all dimensions. Attention control explained a substantial share of the relationship between working memory and retention, indicating that regulatory allocation of attention, rather than memory capacity alone, governs whether lexical information is stabilised during ChatGPT-assisted learning. The frequency of ChatGPT use conditioned these cognitive pathways by strengthening links between working memory and attention control, and between attention control and vocabulary retention, at higher levels of engagement. Frequency did not predict retention independently, indicating that repeated use supports learning only to the extent that it reinforces cognitive regulation rather than increasing exposure. Vocabulary learning with AI relies more on cognitive regulation and engagement than exposure.

This study examined the interaction between spatial frequencies and emotion processing using tachistoscopic presentations of emotional faces, in a patient with right capsulo-thalamic damage and a matched control group (N = 3). Emotional (happy, angry and sad) and neutral faces were presented in one of two ways: broadband emotional images and hybrid faces, which were created by superimposing emotional Low Spatial Frequencies (LSFs) to the High Spatial Frequencies (HSFs) of the same identity with a neutral expression, resulting in a subliminal presentation of the emotional content. According to LeDoux's dual-route model, which suggests a cortical-conscious emotional analysis and subcortical-unconscious emotional processing, we expected healthy participants to show different variations in friendliness ratings compared with the case study patient. In particular, we hypothesized that while healthy participants should show friendliness ratings varying consistently with the facial expressions for both unfiltered (conscious) and filtered (unconscious) stimuli, reflecting the efficiency of both routes, the patient should show a selective deficit in the unfiltered condition due to the disruption of the thalamo-cortical connections. The results showed that healthy controls evaluated emotions consistently across both conditions. Notably, there were no significant differences between the case study patient and the control group for hybrid faces, suggesting that the "hidden" LSF successfully activated the intact subcortical route. However, significant differences emerged for unfiltered stimuli: the case study patient was able to distinguish between positive and negative valence, but she failed to discriminate between negative emotions. This finding suggests that the fine-grained differentiation of negative emotions requires an intact cortical analysis, mediated by the internal capsule.

Research on academic achievement highlights the combined role of cognitive abilities and motivational beliefs. Grounded in the CHC framework, this study examined how three broad cognitive abilities-verbal, numeric, and spatial-and academic self-concept jointly predict achievement in Portuguese and mathematics. A sample of 3034 students from the third cycle (grades 7-9) and secondary education (grades 10-12) completed the BAC-AB cognitive battery and a validated academic self-concept scale. Using multigroup structural equation modelling, we tested whether the predictive patterns differed across educational stages. Academic self-concept emerged as the most consistent predictor across subjects and levels. Cognitive contributions displayed clear developmental differentiation: verbal ability was more strongly associated with Portuguese (and increasingly with Mathematics) in secondary education, whereas numeric and spatial abilities were comparatively more relevant for Mathematics in the third cycle. These patterns support the view that linguistic, quantitative, and visuospatial processes contribute to achievement in distinct and developmentally sensitive ways. Overall, the findings underscore the importance of instructional approaches that build on quantitative and spatial strengths in earlier grades while progressively supporting advanced verbal comprehension and reasoning in later schooling.

This study investigates the relationship between language, motor, and social-relational development in early childhood and the development of executive functions in a sample of 110 preschoolers (M = 57 months, SD = 9.8; 47.3% male, 52.7% female). Through the administration of the Preschool Observation of Development and Self-Regulation questionnaire to parents, information about motor, language, and socio-relational skills at 6-36 months and 37-72 months was collected for each participant. Executive functions were investigated by the administration of a neuropsychological battery. The scores obtained on these tests were summarized through confirmatory factor analysis in the two dimensions: working memory-cognitive flexibility and inhibitory control. Multiple regressions were performed to determine whether the development of certain motor, language or social-relational skills had an impact on the development of working memory, flexibility and inhibitory control observed at preschool. The results show that prior language skills, especially grammatical skills, are predictive factors for the development of working memory and cognitive flexibility at preschool. Additionally, some gross-motor skills at 6-36 months are significant predictors for the development of inhibitory control. These skills are therefore clinically important to prevent possible executive impairment in preschool children and to intercept early at-risk children.

In recent years, there has been increasing interest in personalizing cognitive training to enhance the likelihood of positive training effects at the individual level. Machine learning methods have proven suitable for this purpose due to their ability to generate predictions at the individual level. The aim of the study was to develop supervised machine learning models to predict near and far transfer of three cognitive training interventions (memory training, reasoning training and speed-of-processing training) based on baseline characteristics of elderly individuals including sociodemographic data, measures of cognitive and everyday functioning and depressive symptoms. In addition, near-transfer models were further utilized to predict individual responsiveness to all three types of cognitive training. Publicly available data from the ACTIVE study were used, which examined the effects of memory training, reasoning training and speed-of-processing training in healthy adults. Multiple supervised machine learning classification algorithms were applied to establish optimal predictive models for each type of cognitive training and transfer measure. Selected models for predicting near transfer were then used to estimate individual responsiveness to all three interventions. The results show selected models for all three types of cognitive training and both near- and far-transfer outcomes demonstrated better discriminative ability than chance based on all included features (AUC range 0.56-0.74), although models predicting far transfer demonstrated limited performance. Predicted responsiveness to cognitive training varied according to participant characteristics. Differences between model-predicted responders indicate that initially advantaged participants would have greater likelihood of benefiting from a broader range of interventions compared to initially disadvantaged ones, which would support magnification effects. The developed models need external validation, but have practical potential for selecting effective interventions tailored to individual characteristics, which could improve the future implementation of cognitive training programs.

Millions of workers and job seekers turn to online platforms to gain work-relevant skills to remain competitive for the future of work. However, little is known about whether the skills acquired in work-relevant online courses align with the skills required for 21st-century jobs. Drawing on literature on job and skill matching, this exploratory study examines the alignment between available online training and learning content and the skills demanded by jobs (i.e., training-skills demands fit) using artificial intelligence methods. A large language model (LLM; Claude Haiku 3.5) was instructed to evaluate which of the 35 basic and cross-functional skills from the Occupational Information Network (O*NET) could be acquired in a given course, which was based on 2549 course descriptions extracted from MIT OpenCourseWare. Linkages between online training and skills were broken down by job family and occupations with a bright outlook designation (i.e., occupations estimated to have 75,000 or more job openings between 2024 and 2034 across the United States). Results suggest that the skill of active learning (i.e., using new information for problem-solving; 88%, N = 2242) was linked to the highest number of online courses, whereas the skill of instructing (i.e., teaching others to perform tasks; 5.3%, N = 134) was linked to the least. Computer and mathematical occupations had the highest proportion of courses wherein individuals can acquire basic and cross-functional skills, whereas food preparation and serving occupations had the lowest proportion of courses. Non-bright outlook occupations had a significantly lower proportion of online courses where individuals can acquire basic and cross-functional skills compared to occupations with a bright outlook designation. We expand on existing skills-matching perspectives to consider how training-skills demands fit can constrain or facilitate continuous learning and development. Further, we illustrate how LLMs can be used to efficiently and at scale summarize descriptive information on talent development issues.

Executive function (EF) impairments are common in children with intellectual and developmental disabilities and have a significant impact on learning and daily life. Cognitive training programs aimed at strengthening EFs may show limited feasibility and generalization. However, recent studies suggest that ecological, curriculum-embedded problem-solving activities may be more promising. This multiple-baseline single-case study tested the feasibility and efficacy of a short computational thinking and coding intervention based on problem-solving for children with sickle cell disease, a hemoglobinopathy associated with cognitive decline and EF deficits. The trial followed the What Works Clearinghouse (WWC) Version 5 guidelines for single-case research. Three 7-8-year-old children with lower-range IQ (71-82) and EF impairments completed 11 coding sessions over 5-6 weeks using code.org, with pre/post assessments of non-verbal EF (planning, inhibition, and switching), and verbal EF skills (verbal working memory, phonological fluency and semantic fluency). Results showed 100% adherence to the intervention, significant improvement in coding (IRD range = 0.69-0.79), with positive transfer effects on nonverbal planning skills (gains > 2 z-scores) and also verbal fluency (z-score gains ranging from 0.47 to 1.04). Inter-individual variability in effects was related to the child's individual cognitive profile. Findings suggest that problem-solving, coding-based activities can be feasible and potentially beneficial for children with significant EF impairments.