Journal of Intelligence doi: 10.3390/jintelligence14040071

Authors: Lilan Chen Zhiyong Zhong Wenyuan Jiang

Mathematical abilities are critical for the developmental outcomes of children with autism spectrum disorder (ASD). However, little is known about these abilities and their association with the approximate number system (ANS) in preschoolers with ASD beyond Western samples, including Chinese children. This cross-sectional study examined whether formal and informal mathematical abilities differed between children with and without ASD and assessed the extent to which these abilities were associated with ANS acuity. Participants included 47 children with ASD and 47 typically developing (TD) children aged 3–7 years. All children were assessed on measures of formal and informal mathematical abilities, ANS acuity, and non-verbal IQ. No significant group differences in mathematical abilities were found among children aged 3–5 years. However, among children aged 6–7 years, the ASD group showed significantly lower performance in mathematical abilities compared to their TD peers. ANS acuity was significantly correlated with both formal and informal mathematical abilities in the ASD group, but only with informal mathematical abilities in the TD group. Furthermore, ANS acuity accounted for 5.4% of the unique variance in formal mathematical abilities specifically within the ASD group. The patterns of mathematical abilities and their relationship with ANS acuity differ between preschoolers with and without ASD. These findings suggest a differential association between ANS and formal mathematics learning in children with ASD, highlighting implications for the design of early numeracy interventions.

Journal of Intelligence doi: 10.3390/jintelligence14040070

Authors: Huan Kuang

Computer-based assessments generate rich process data that captures examinees’ interactions with test items. Using process data from the U.S. PISA 2012 computer-based mathematics assessment sample, this study applied recurrent neural networks to predict item-level correctness and assessment-level latent proficiency. The analysis also examines the impact of expert-engineered features, levels of architectural complexity, action variability, and score variability on model performance. At the item level, most models achieved AUC values around 0.80, indicating good predictive performance. Moderate correlations were observed between latent proficiency from 30 items and predictions based on process data from a subset of items (n = 10). For item-level models, adding expert-engineered features reduces training time and may improve predictive performance with low action variability. For the assessment-level models, adding expert-engineered features improved performance. Model complexity, including model type (i.e., standard RNN, GRU, and LSTM), number of nodes, and number of layers, had little effect on accuracy and efficiency. Moreover, items with greater action variability were associated with better model performance. The findings suggest that simple neural network architectures are sufficient for modeling process data with limited action variability and that combining action sequences with expert-engineered features improves accuracy, efficiency, and interpretability.

Journal of Intelligence doi: 10.3390/jintelligence14040069

Authors: Colin Peperkorn Claas Wegner

Matrix reasoning tests are frequently used to measure intelligence and identify gifted students across domains. To date, there is limited evidence on the usefulness of contextualised tasks for identifying domain-specific giftedness. In the current study, matrix reasoning tasks tailored to biological contexts were developed and validated for students in grades 3–6. The tasks were evaluated across two research cycles, involving a total of N = 895 students (n1 = 470; n2 = 425). An item analysis based on item response theory indicated acceptable item parameters and fit indices for the final item pool. Correlation analyses revealed moderate-to-strong associations with IQ, assessed via abstract matrix reasoning, as well as with domain-specific achievement in biological inquiry processes. A known-groups comparison revealed that students identified as gifted in biology outperformed a comparison group of peers, providing preliminary known-groups validity evidence for the developed tasks. Overall, the matrix reasoning tasks tailored to biology showed acceptable psychometric properties, demonstrated positive correlations with achievement in biological inquiry, and the study provided initial evidence of their usefulness for identifying gifted students in biology.

Journal of Intelligence doi: 10.3390/jintelligence14040068

Authors: Shangqing Yuan Yifei Fang Luming Zheng Jun Zhang Hengrui Zhang Tie Sun

Creative problem solving often fails because people rely on heuristic responses reinforced by prior experience. According to the default–interventionist account, analytic intervention can override these heuristic defaults only when the semantic system provides access to competing representations. We tested this prediction using a modified Chinese Remote Associates Task in which two factors were independently manipulated: semantic accessibility (high vs. low) and situational induction (strong vs. weak). A significant interaction emerged: strong induction impaired performance only under low semantic accessibility, whereas high semantic accessibility was associated with attenuated induction costs. This pattern is consistent with semantic accessibility serving as a cognitive buffer that may support analytic override of induced heuristic defaults. A separate comparison between induction and non-induction trials confirmed that induction reliably produced a mental set. These findings resolve conflicting claims about the role of semantic knowledge in creativity by showing that knowledge both constrains and enables insight depending on its interaction with experience-driven heuristics.

Journal of Intelligence doi: 10.3390/jintelligence14040067

Authors: Csongor Toth Brigitte Osser Laura Ioana Bondar Gyongyi Osser Roland Fazakas Nicoleta Anamaria Pascalau Ramona Nicoleta Suciu Liliana-Oana Pobirci Corina Dalia Toderescu Bombonica Gabriela Dogaru

Background/Objectives: The increasing prevalence of digital media use among children and adolescents has raised concerns regarding its potential impact on cognitive and communication development. Previous research has linked higher screen exposure to poorer language outcomes; however, the mechanisms underlying these associations remain insufficiently understood, particularly with respect to pragmatic communication. The present study aimed to examine the relationships between daily screen time, executive functioning (EF), and communication-related outcomes, and to test whether EF mediates the association between digital media exposure and pragmatic communication and language performance. Methods: A cross-sectional observational study was conducted with 240 children and adolescents aged 6–15 years. Caregivers reported children’s daily screen time, digital consumption and communication skills. EF was assessed using performance-based tasks measuring inhibitory control, working memory, and cognitive flexibility. Language performance was evaluated using a standardized composite measure. Pearson correlations, mediation analyses with bootstrapped confidence intervals, and factorial analyses of variance were performed, controlling for age, sex, parental mediation, and educational content exposure. Results: Higher daily screen time was significantly associated with lower EF, weaker pragmatic communication, and poorer language performance. EF was positively related to both pragmatic and language outcomes and partially mediated the relationship between screen time and communication measures. Educational digital content and parental mediation showed positive associations with EF and communication outcomes, whereas recreational content exhibited negative associations. Group comparisons indicated that negative associations between screen exposure and developmental outcomes were more pronounced in younger children. Conclusions: These findings suggest that EF may represent a key intermediary mechanism underlying the association between digital media exposure and communication-related development. The results highlight the importance of considering not only the quantity but also the quality and context of children’s digital media use, particularly during early developmental stages.

Journal of Intelligence doi: 10.3390/jintelligence14040066

Authors: Abdullah Zulaikha Fatima Miguel Jesús Torres Ruiz Osvaldo Espinosa-Sosa Carlos Guzmán Sánchez-Mejorada Rolando Quintero Téllez José Luis Oropeza Rodríguez Grigori Sidorov

Early diagnosis of cognitive decline is vital for timely treatment of mild cognitive impairment (MCI) and Alzheimer’s disease (AD), yet standard clinical assessments often miss subtle longitudinal language changes. We propose a hierarchical hybrid intelligence framework integrating long-context language modeling, temporal progression, semantic graph reasoning, psycholinguistic biomarkers, and contrastive progression learning to classify patient states (Normal, MCI, AD) from longitudinal electronic health record (EHR) notes. The model was trained on 4500 patients and 68,000 clinical notes from Medical Information Mart for Intensive Care III (MIMIC-III) and externally validated on the Medical Information Mart for Intensive Care IV (MIMIC-IV) clinical notes dataset (5200 patients, 72,000 notes). Inputs combined Biomedical and Clinical Bidirectional Encoder Representations from Transformers (BioClinicalBERT) embeddings, Bidirectional Long Short-Term Memory (Bi-LSTM) temporal encodings, Graph Sample and Aggregate (GraphSAGE)-based Unified Medical Language System (UMLS) concept graphs, and psycholinguistic vectors (lexical diversity, grammatical complexity, discourse coherence). On the MIMIC-III hold-out set, the model achieved 99.999% accuracy, a macro F1-score of 0.999, a Receiver Operating Characteristic Area Under the Curve (ROC AUC) of 0.999, and a temporal stability variance of 0.0008. Monte Carlo cross-validation (10,000 folds) yielded 99.997±0.003% accuracy and 0.999±0.001 macro F1. Feature ablation confirmed distinct gains from temporal, semantic, and psycholinguistic modules, improving performance by 1.1% over text-only baselines. Cross-cohort zero-shot testing on MIMIC-IV showed strong generalization with minimal decline in macro F1 and balanced accuracy. Explainability analyses, such as SHapley Additive exPlanations (SHAP) token/concept attribution, attention maps, counterfactual perturbations, and psycholinguistic importance, revealed clinically interpretable markers, such as pronoun overuse, reduced lexical diversity, and syntactic simplification, as predictors of decline. Our framework supports scalable, non-invasive early screening in a variety of healthcare settings by providing longitudinally stable predictions.

Journal of Intelligence doi: 10.3390/jintelligence14040065

Authors: Ziyang Huang Jiajia Zhao Xuan Fu

Generative artificial intelligence (GenAI) is rapidly transforming design education by enabling new forms of human–AI collaborative learning. However, how GenAI relates to cognitive and motivational processes in design learning contexts remains insufficiently understood. This study examines whether integrating GenAI into visual design instruction is associated with improvements in domain-specific creative performance and explores the relationships among cognitive load, learning motivation, and learning outcomes. A six-week randomized instructional experiment was conducted with 120 undergraduate students majoring in visual communication design. Creative performance was evaluated through blind expert ratings, and the relationships among key variables were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that GenAI-integrated instruction is associated with higher levels of learning motivation, engagement, and expert-rated creative performance compared with traditional instruction, whereas cognitive-load indicators show comparatively limited predictive strength within the overall model. In addition, Integrated Teaching Alignment (ITA) significantly moderates the relationship between perceived relevance and learning satisfaction. These findings suggest that GenAI may function as an external cognitive support tool, with learning outcomes appearing to be associated with motivational and instructional factors, while cognitive-load indicators show comparatively limited associations within this instructional context.

Journal of Intelligence doi: 10.3390/jintelligence14040064

Authors: Shoeb Saleh Rommel AlAli

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.

Journal of Intelligence doi: 10.3390/jintelligence14040063

Authors: Lena Paulus Charlotte K. L. Dißelkamp Andreas J. Forstner Frank M. Spinath

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.

Journal of Intelligence doi: 10.3390/jintelligence14040062

Authors: Mohammad Hamad Al-khresheh Mayez Almayez Shatha F. Alruwaili

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.

Journal of Intelligence doi: 10.3390/jintelligence14040061

Authors: Hui Yan Han Xiao Jianlin Yuan

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.

Journal of Intelligence doi: 10.3390/jintelligence14040060

Authors: Vincenza Tommasi Caterina Padulo Giulia Prete Antonio Leo Alessandra Franco Tatiana De Francesco Maria Rosaria Viva Luca Tommasi Giuliana Lucci Chiara Valeria Marinelli

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.

Journal of Intelligence doi: 10.3390/jintelligence14040059

Authors: Makai A. Ruffin Margaret E. Beier Felix Y. Wu Nathaniel M. Voss Anoop A. Javalagi Harrison J. Kell

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.

Journal of Intelligence doi: 10.3390/jintelligence14040058

Authors: Pedro Teques

Football refereeing involves rapid decision-making in dynamic, uncertain, and socially demanding environments. This study examined an integrative cognitive-behavioral model of football refereeing performance, focusing on perceptual processing speed (PPS), attentional control (AC), and social intelligence (SI). Sixty-one male football referees (Mage = 30.04, SD = 4.06) enrolled in a national talent development program across multiple competitive seasons participated in the study. At the beginning of each season, referees completed standardized, ability-based assessments of PPS (processing speed task), AC (selective and inhibitory task), and SI (performance-based social intelligence measure). Refereeing performance was operationalized using season-standardized end-of-season officiating ratings assigned by the national refereeing authority. Mediation analyses did not support AC or SI as mechanisms transmitting the effect of PPS on performance. However, moderation analyses revealed a significant PPS × AC interaction, indicating that attentional control amplified the positive association between perceptual processing speed and refereeing performance. PPS emerged as a robust predictor of performance, particularly among referees with high attentional control. Social intelligence showed a positive bivariate association with performance but did not function as a mediator or moderator in multivariate models. These findings support an interactive and ecological view of applied intelligence in football refereeing, emphasizing functional coordination highlighting the functional coordination of cognitive resources rather than isolated cognitive abilities as key to performance under real-world competitive demands.

Journal of Intelligence doi: 10.3390/jintelligence14040056

Authors: Petra Vargek Sašo Karakatič Karin Bakračevič

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.

Journal of Intelligence doi: 10.3390/jintelligence14040057

Authors: Leandro S. Almeida Gina C. Lemos Ana Cristina Silva Francisco Peixoto

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.

Journal of Intelligence doi: 10.3390/jintelligence14040055

Authors: Barbara Arfé Maria Elisa delle Fave Chiara Montuori Lucia Ronconi Sofia Carbone Raffaella Colombatti

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.

Journal of Intelligence doi: 10.3390/jintelligence14040054

Authors: Nicoletta Scionti Claudia Ceruti Maria Laura Guercio Gian Marco Marzocchi

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.

Journal of Intelligence doi: 10.3390/jintelligence14040053

Authors: Asem Mohammed Ibrahim Reem Ebraheem Saleh Alhomayani Azhar Saleh Abdulhadi Al-Shamrani

Generative Artificial Intelligence (GAI) is rapidly transforming higher education by introducing new mechanisms for supporting the development of advanced cognitive processes and research-related capabilities. This study examines how postgraduate students employ GAI to develop their cognitive and research talent, conceptualized here as higher-order academic skills such as analysis, synthesis, and critical reasoning, across six domains: literature review, theoretical development, research design, data analysis, academic writing, ethical use, and challenges encountered—signaled explicitly rather than listed line by line. We administered a validated multidimensional scale to 214 postgraduate students, and the results indicate a moderate overall use of GAI, with notably high involvement in practices that emphasize ethics and responsibility. Students reported clear cognitive benefits in tasks involving information processing, linguistic refinement, and conceptual clarification while showing caution toward delegating higher-order analytical or theoretical reasoning to AI systems. Key challenges included limited institutional training, concerns about data privacy and academic integrity, and difficulties evaluating the originality and reliability of AI-generated content. Inferential analyses indicated significant differences based on gender, academic level, and general technology proficiency, whereas no differences emerged across age groups, departments, or specializations. Overall, this study demonstrates how GAI can contribute to the development of higher-level cognitive skills and research competencies, with “moderate use” operationalized as consistent but selective engagement across domains, while underscoring the need for structured training, clear guidelines, and teaching approaches that foster the responsible and effective incorporation of AI within postgraduate research. The results highlight practical implications for higher education, including the importance of institutional training programs, governance frameworks for responsible AI use, and pedagogical models that foster critical engagement with GAI.

Journal of Intelligence doi: 10.3390/jintelligence14040052

Authors: Sophie Alina Schneider Nina Krüger

Intelligence test batteries are a common tool in psychological assessment. Their results can have a large impact on an individual’s life, especially for children and adolescents. Despite this, uncertainty remains as to what extent these results are dependent on the test battery used. Two commonly used intelligence test batteries for children and adolescents in German speaking countries are the WISC-V and the AID 3. This study aimed to investigate the degree of comparability between the two test batteries in terms of their resulting scores, subtest content and test profiles in a mathematically gifted sample. A total of 36 children and adolescents (aged M = 12.89 years, SD = 0.58) completed all subtests of both test batteries. Results revealed that most IQ measures did not differ significantly between the two test batteries for this sample. The correlations of the subtests revealed a structure with four main nodes that was in line with previous factor analytical studies. The standard deviations of the τ-adjusted test scores within test profiles were not significantly different; however, significantly higher ranges were found in the AID 3. Results indicate higher IQ scores on the WISC-V, differential validity for factor structures, and methodological benefits of adaptive testing with the AID 3, particularly in gifted samples. Despite subtest overlaps, composite scores diverge and require individualized interpretation.

Journal of Intelligence doi: 10.3390/jintelligence14040051

Authors: Wenqing Lin Xinmei Deng

Adolescence is a key period of significant physiological and social development, during which social anxiety symptoms often emerge and can impact academic and social functioning. Social anxiety disorder (SAD) involves heightened sensitivity to social cues and impaired social information processing, potentially contributing to persistent anxiety symptoms. However, research exploring the neural mechanisms of social information processing in adolescents with social anxiety remains limited. The investigation employed a facial dot-probe paradigm combined with EEG measurements to assess differences in attentional processing and neurophysiological activity between two adolescent groups: a high-social-anxiety (HSA) group (N = 27) and a low-social-anxiety (LSA) group (N = 18). Results showed (1) there was a significant reduction in P2 amplitudes in the HSA group compared to the LSA group. (2) A significant negative correlation between the disengagement index (DI) and P2 amplitude was found. (3) Weaker functional connectivity in the theta band was found in the HSA group. (4) In the graph theory analysis, the HSA group exhibited significantly higher node efficiency across various frequency bands compared to the LSA group. The findings suggest that socially anxious adolescents have impaired attentional control toward social cues. This difficulty may reinforce their anxiety symptoms over time.

Journal of Intelligence doi: 10.3390/jintelligence14030050

Authors: Gülçin Oflaz Kübra Polat Yılmaz Mutlu Zekeriya Çam

The aim of this study is to develop a valid and reliable scale for measuring the self-efficacy of primary school and mathematics teachers regarding dyscalculia. Grounded in Bandura’s Social Cognitive Theory, the study followed established scale development procedures. In the initial phase, a pool of 42 items was generated to assess teachers’ self-efficacy regarding dyscalculia. The items were reviewed by a panel of seven experts in the fields of psychometrics, mathematics education, special education, and psychology to ensure content validity. Based on expert evaluations, four items were removed due to overly technical phrasing that could lead to misinterpretation, reducing the pool to 38 items. Subsequently, Exploratory Factor Analysis (EFA) conducted with 273 teachers indicated that four additional items exhibited inadequate factor loadings or problematic cross-loadings; these items were also excluded. The resulting Dyscalculia Self-Efficacy Scale (DSES) comprises 34 items organized into four factors: “Dyscalculia Symptoms”, “Providing Psychological Support to Children with Dyscalculia”, “Diagnosing Dyscalculia”, “Providing Support in the Teaching Process”. Confirmatory Factor Analysis conducted with a separate sample of 242 teachers yielded strong model fit indices, supporting the construct validity of the scale. The overall scale demonstrated high internal consistency (Cronbach’s α = 0.980, McDonald’s ω = 0.980). Correlation analyses with established instruments provided evidence of convergent and discriminant validity. The findings indicate that the DSES is a valid and reliable instrument for assessing teachers’ self-efficacy regarding dyscalculia.

Journal of Intelligence doi: 10.3390/jintelligence14030049

Authors: Ümit İzgi Onbaşılı

This study examined psychological well-being as the outcome and its associations with emotional intelligence and occupational anxiety in a sample of pre-service teachers (n = 360) from 74 universities in Türkiye. Participants completed the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), the Ryff Psychological Well-Being Scale (PWBS), and the Occupational Anxiety Scale (OAS). After descriptive statistics and Pearson correlations, multiple linear regression was conducted; incremental validity was examined with a two-block hierarchical model. Emotional intelligence was positively associated with psychological well-being, whereas occupational anxiety showed a negative association. In the regression model, emotional intelligence (Beta = 0.66) and occupational anxiety (Beta = −0.28) jointly explained 71% of the variance in psychological well-being (R = 0.84, R2 = 0.71, F(2, 357) = 426.18, p < 0.001). Mediation analysis (PROCESS Model 4, 5000 bootstrap resamples) further supported an indirect association whereby higher emotional intelligence was related to lower occupational anxiety, which in turn was related to higher psychological well-being, while the direct association remained significant. These findings suggest that strengthening socio-emotional competencies and integrating anxiety regulation strategies within teacher education may support well-being outcomes. The principal limitations are the cross-sectional design and reliance on self-report measures, so inferences are correlational rather than causal. Future research should include longitudinal or quasi-experimental evaluations of interventions targeting emotional intelligence and anxiety regulation, using multi-method measurement and tests of moderation and multilevel models.

Journal of Intelligence doi: 10.3390/jintelligence14030048

Authors: Moritz Herzog Michael Grosche Gunnar Bruns Gino Casale

The moderation of intervention effects by intelligence and prior knowledge deserves further investigation, because they inform how to design and implement interventions. This study analyzed the moderation of the effectiveness of a computer-based mathematics intervention in 10 primary school students with low mathematics performance and low-to-average intelligence in an ABAB-single-case research design. Prior knowledge and intelligence were assessed before the intervention. The computer-based intervention trained basic numerical skills. Visual inspection of the learning trajectories revealed a broad heterogeneity of effectiveness of the intervention. A hierarchical piecewise regression analysis across all students revealed a significant negative moderation of the intervention effectiveness through intelligence. Whereas prior knowledge did not have a moderating influence, children with higher intelligence showed slower learning rates during the intervention in this specific low-performing sample. One reason for the negative moderation of the intervention effects could be that the intervention trained strategies and skills that more intelligent students had already developed.

Journal of Intelligence doi: 10.3390/jintelligence14030047

Authors: Baike Li Chunliang Yang

JOLs are widely used to measure metacognitive monitoring, yet their elicitation can reactively enhance memory—a phenomenon known as the positive reactivity effect. The enhanced engagement theory posits that JOLs improve memory by increasing attentional and cognitive engagement during encoding, but direct experimental evidence remains scarce. Across three experiments, we directly manipulated key components of learning engagement—attentional focus (via silent vs. aloud production), cognitive effort (via massed vs. spaced repetition), and motivational involvement (via standard vs. time-saving instructions)—while assessing their impact on the JOL reactivity effect in word recognition memory. Results consistently demonstrated robust positive reactivity effects, critically, the magnitude of these effects was significantly attenuated under high-engagement conditions (aloud reading, spaced learning, and heightened motivation). These converging findings provide the first direct, multi-method experimental support for the enhanced engagement theory, specifying that making JOLs benefit memory most when baseline engagement is low. The results delineate boundary conditions under which making JOLs yield beneficial effects and provide practical insights into leveraging JOLs to regulate engagement in real-world learning environments.

Journal of Intelligence doi: 10.3390/jintelligence14030046

Authors: Chaoyi Wang Dong Yang Jiangbo Hu Zhenyu Cai

The engagement and burnout profiles of preschool teachers are closely linked to young children’s developmental outcomes. This study investigated engagement and burnout profiles among 529 Chinese preschool teachers in relation to their emotional states, varying experiences, and professional backgrounds. The sample predominantly consisted of early-career educators, with 47.8% aged between 21 and 30 years and 33.1% having 0–5 years of work experience. Using a quantitative cross-sectional design and latent profile analysis (LPA), this study identified four distinct profiles: slightly exhausted (48.58%), moderately burned out (18.53%), engaged (25.90%), and highly burned out (6.99%). Positive emotional states, such as enjoyment, were associated with higher work engagement, while anxiety was associated with a higher probability of belonging to burnout profiles. In contrast, perceived career success and negative emotions like anger did not significantly predict work engagement and burnout profiles. Teachers with extensive teaching experience and pre-service early childhood education (ECE) training were more likely to maintain high work engagement. This study highlights the critical role of emotional states and professional ECE training in promoting preschool teachers’ work engagement and sustainable practice, particularly among early-career teachers.

Journal of Intelligence doi: 10.3390/jintelligence14030045

Authors: Albert Ziegler Sonja Bayer Heidrun Stoeger

There is a growing consensus that we must look beyond IQ to understand the mechanisms of talent development. Grounded in the Actiotope Model of Giftedness, this study adopts a resource-based approach and examines the incremental and interactive contributions of educational and learning capital to STEM achievement beyond IQ. Data were collected from 318 German secondary school students (grades 6–10; Mage = 12.08; 50.3% male) using domain-specific measures of educational and learning capital, a nonverbal matrix intelligence test, and STEM grades. Robust regression and mediation analyses showed that learning capital significantly predicted STEM achievement beyond general intelligence, whereas educational capital exerted no direct effect. Instead, the relationship between educational capital and achievement was fully mediated by learning capital. Moreover, the interaction term of educational and learning capital predicted achievement. A further interaction indicated that the positive effect of learning capital on STEM achievement was stronger for students with higher intelligence, consistent with an intelligence utilization (Matthew) effect. These findings support a systemic interpretation of achievement in which intelligence reflects prior resource utilization and functions as a catalyst, while current learning resources constitute the proximal determinants of STEM performance.

Journal of Intelligence doi: 10.3390/jintelligence14030044

Authors: Tindara Caprì Giada Benedetta Catalano Rosa Angela Fabio

Growing evidence indicates that executive functions, metacognition, and reading comprehension are crucial for academic success; however, their contribution to academic achievement in gifted children remains insufficiently understood. The main aim of this study was to compare planning processes and metacognitive abilities among gifted children with high academic achievement, gifted children with low academic achievement, and typically developing children with high academic achievement. A secondary aim was to examine reading comprehension in gifted children compared to typically developing peers. Seventy-three children (34 males, 39 females), aged between 8 and 11 years (M = 9.5, SD = 0.91), were divided into three groups: gifted children with high academic achievement, gifted children with low academic achievement, and typically developing children. Participants completed the Tower of London task, the MT Reading Comprehension Test, and the Me and My Mind metacognition questionnaire. Results showed that both groups of gifted children performed significantly better than typically developing peers in planning efficiency and reading comprehension. No significant differences emerged between high- and low-achieving gifted children in planning, reading comprehension, or metacognition. Overall, the findings suggest that planning abilities and reading comprehension represent cognitive strengths that distinguish gifted children from typically developing high achievers, whereas differences in academic achievement within the gifted population may be more closely related to metacognitive regulation and other non-cognitive factors rather than to planning or reading comprehension alone.

Journal of Intelligence doi: 10.3390/jintelligence14030043

Authors: Xingyuan Xue Yuan Yao

Number sense, the ability to rapidly perceive, estimate, and understand relationships between quantities, constitutes a fundamental basis for mathematical cognition. However, the extent to which it is modulated by top-down regulatory processes remains poorly understood. Rewards inherently carry quantitative attributes of abundance and scarcity, and prospect theory further suggests that individuals tend to underestimate rewards and overestimate punishments of equal magnitude, implying that the perception of reward quantities may be systematically biased. To address this issue, the present study employed EEG to examine how reward-related properties of stimuli modulate number sense, using socially relevant reward stimuli as experimental materials. Behavioral results demonstrated that rewarding stimuli were underestimated compared to neutral and punishing stimuli, while punishing stimuli were overestimated relative to neutral stimuli. EEG analyses revealed that at number-sensitive electrodes (PO7, PO8, Oz), the C1 component was sensitive to reward properties; the N1 component at PO7 was specifically sensitive to punishment; and in the P2p time window, neutral stimuli elicited the largest amplitudes, suggesting inhibitory processing of reward-related attributes during quantity perception. Together, these findings indicate that reward-based modulation of number sense occurs unconsciously and follows a dynamic temporal profile.

Journal of Intelligence doi: 10.3390/jintelligence14030042

Authors: Vered Markovich Shoshi Dorfberger Vered Halamish Tami Katzir Dana Tal Rotem Yinon

This study examined associations between vocabulary knowledge, reading fluency, cognitive flexibility, and metacognitive monitoring accuracy in reading comprehension among fifth-grade students. Participants (N = 104) completed measures of cognitive–linguistic abilities and reading comprehension, with global metacomprehension judgments after reading and item-level confidence ratings. Metacognitive monitoring accuracy was assessed using calibration of global metacomprehension judgments and item-level confidence ratings. Calibration bias (confidence minus performance) indexed miscalibration direction, and its absolute value indexed calibration accuracy. Resolution reflected discrimination between correct and incorrect item-level responses. Structural equation modeling (SEM) was used exploratorily to examine theoretically motivated direct and indirect pathways via reading comprehension. Vocabulary knowledge showed the strongest associations with calibration accuracy and resolution, fully mediated by comprehension. Reading fluency showed a dual pattern: it contributed positively to resolution through comprehension, while also showing direct associations with lower calibration accuracy, indicating greater miscalibration and overconfident judgment tendencies among more fluent readers. Cognitive flexibility was not significantly related to any monitoring index. By jointly examining distinct indices of monitoring accuracy and separating comprehension-mediated from direct pathways, the study clarifies how cognitive–linguistic abilities may support or bias metacognitive monitoring in developing readers. Linguistic abilities, particularly vocabulary and fluency were central to students’ comprehension monitoring accuracy.

Journal of Intelligence doi: 10.3390/jintelligence14030041

Authors: Amit Skurnik Yoed N. Kenett

Creativity involves generating ideas that are both original and useful, relying on intertwined cognitive and metacognitive processes. We examined how individual differences in semantic memory structure and ideation fluency predict creative performance and self-evaluations across two studies. In Study 1, participants completed a creative problem-solving (CPS) task, with semantic memory networks estimated from a relatedness judgment task. Creative output was assessed for originality and usefulness, alongside participants’ self-evaluations. In Study 2, a within-subjects design compared participants’ output and self-evaluation of their performance in a divergent thinking task (alternative uses task) and CPS. Results revealed that ideation fluency and semantic memory network integration consistently predicted originality across tasks. In contrast, usefulness was less reliably predicted, showing task-specific associations with semantic memory network properties primarily in CPS. Importantly, self-evaluations often diverged from objective outcomes, reflecting metacognitive biases shaped by heuristic cues. These findings highlight both stable and context-sensitive mechanisms in creative performance and self-evaluation.

Journal of Intelligence doi: 10.3390/jintelligence14030040

Authors: Chunli Zhang Kai An Jiacheng Li Qinchen Yang Meihui Song Li Wang

Auxiliary line construction has been identified as a crucial approach to fostering mathematical creative thinking. However, existing studies have only focused on the correlations between auxiliary line construction tasks and mathematical creative thinking, without investigating whether engaging in auxiliary line construction can improve mathematical creativity. As a well-established research paradigm, cognitive priming can elicit changes in thinking within a short period. Based on this idea, the present study adopted the cognitive priming paradigm combined with functional near-infrared spectroscopy (fNIRS) technology, and randomly assigned 42 Chinese college students to an auxiliary line group or a control group. The students’ brain activity was monitored in real time during the priming phase (the auxiliary line group completed geometric problems requiring auxiliary line construction, while the control group finished proof problems with pre-set auxiliary lines) and the post-test phase (both groups completed a mathematical creative thinking test). The behavioral results showed that the auxiliary line group achieved significantly higher scores in fluency and originality of mathematical creative thinking than the control group in the post-test phase. The fNIRS data revealed that during the priming phase, the auxiliary line group exhibited stronger activation of the right superior frontal gyrus and higher variability in dynamic functional connectivity; meanwhile, in the post-test phase, the right superior frontal gyrus and right middle frontal gyrus maintained robust neural activation, and brain functional connectivity exhibited a lower clustering coefficient and attenuated small-world network properties. This study confirms that short-term engagement in auxiliary line construction exerts a priming effect on the fluency and originality of mathematical creative thinking, which may be associated with the enhanced activation of specific brain regions and the dynamic adjustment of brain functional connectivity. These findings provide theoretical and empirical evidence for the cultivation of mathematical creative thinking.

Journal of Intelligence doi: 10.3390/jintelligence14030039

Authors: Michaela A. Meier Lara Spitzley Serra Ulusoy Alexandra Hubmann Rylie DelaCruz Roland H. Grabner Daniel Müllensiefen

Numerous studies have aimed to improve mathematical achievement via musical interventions because it is argued that music and mathematics draw on related representations and similar skills. However, findings on their effectiveness are inconclusive. This might be because studies neglect to investigate the cognitive mechanisms that might link musical and mathematical abilities. Therefore, this study aimed to systematically investigate the relationships between facets of musical and mathematical ability while taking into account intelligence as a possible explanation for this link. Among 170 young adults with backgrounds in mathematics and/or music, as well as control subjects, we measured mathematical abilities using basic numerical abilities, arithmetic fluency, and higher mathematical competencies. Musical abilities were assessed using beat alignment, mistuning perception, and melodic discrimination. Intelligence was assessed using a verbal, figural, and numerical scale of an intelligence test. Using a latent variable model, we found a moderate to strong positive association between mathematical and musical abilities. However, after including intelligence as a predictor for both mathematical and musical abilities in our model, the relationship between mathematics and music became nonsignificant. These results imply that intelligence accounts for a substantial proportion of the association between mathematical and musical abilities.

Journal of Intelligence doi: 10.3390/jintelligence14030038

Authors: Lorenzo Esposito Irene Tonizzi Maria Carmen Usai David Giofrè

Previous research indicates that cognitive and affective-motivational factors, along with gender, influence students’ educational choices, especially regarding STEM tracks. However, few longitudinal studies have examined these factors during middle school, a critical stage in shaping future academic trajectories. This study investigated the longitudinal contribution of gender, cognitive abilities, and affective-motivational factors, such as self-concept, math interest, and math anxiety, in predicting students’ school choice between STEM and non-STEM tracks at the end of middle school. Data were collected from 159 Italian students, followed from seventh to eighth grade. Findings indicated that gender and positive attitudes toward math were strongly associated with STEM school choice. Boys were more likely than girls to choose STEM tracks (b = 5.048). Higher levels of math self-concept (b = 4.848) and interest (b = 0.887) significantly predicted the likelihood of choosing a STEM school. These results highlight how gender and affective-motivational factors shape educational pathways during adolescence.

Journal of Intelligence doi: 10.3390/jintelligence14030037

Authors: Eisvina Burbaite Ilona Tilindiene Saulius Sukys

Background. The present study aimed to examine the psychometric properties of the Lithuanian adaptation of the TEIQue-SF. Methods. The analyses were performed using a sample of 199 preschool teachers (100% women; mean age = 46.70, SD = 11.70 years, age range = 21–69 years) from across Lithuania. The Teacher Subjective Wellbeing Questionnaire was also administered as an external validation measure. The reliability of the TEIQue-SF was assessed by Cronbach’s α and McDonald’s ω. Finally, we examined the relationship between sociodemographic characteristics and global trait emotional intelligence. Results. Confirmatory factor analysis of the Lithuanian TEIQue-SF supported the one-factor structure of trait emotional intelligence (CFI = 0.99, TLI = 0.98, IFI = 0.99, RMSEA = 0.04, SRMR = 0.02). Good internal consistency was observed for global trait emotional intelligence (α = 0.85, ω = 0.84). Global trait emotional intelligence was significantly and positively associated with the teacher general well-being (β = 0.28), school connectedness (β = 0.26), and teaching efficacy (β = 0.28). Age was the only sociodemographic indicator positively related to global trait EI (β = 0.26). Conclusions. Our research showed that the Lithuanian version of the TEIQue-SF is a valid and reliable instrument to measure trait emotional intelligence and can be recommended for research and practical use.

Journal of Intelligence doi: 10.3390/jintelligence14030036

Authors: Al Mansor Helal Jonathan Wai

This study draws from two cohorts of students (total N = 10,508) to examine cognitive ability and achievement inequality around the COVID-19 pandemic. Before and after the pandemic, two groups of Arkansas students were given both the Cognitive Abilities Test (CogAT), which is considered more of an ability or reasoning measure, and the ACT-Aspire, which is considered more of an achievement measure. We use a quantile regression framework to examine possible distributional impacts of the COVID-19 pandemic. Results demonstrate that the cognitive ability and/or achievement gaps did not widen after the pandemic, instead they stayed stable or narrowed moderately across groups. Results also indicate that cognitive ability was a significant and consistent predictor of achievement before COVID-19, but the strength of this relationship attenuated noticeably after the pandemic. This work helps add to the literature on COVID learning changes (large losses for many students), drawing from a large database of students in one state.

Journal of Intelligence doi: 10.3390/jintelligence14030035

Authors: Maybí Morell-Ruiz Eva-Maria Ternblad Betty Tärning Sonja Holmer Magnus Haake Agneta Gulz

The present study examined the cognitive mechanisms underlying decision-making in number-line estimation in 26 preschoolers through the lens of the evidence-accumulation paradigm. Children completed a traditional Number Line Estimation Task (NLET) and the Numeracy Screener test, which assessed symbolic and nonsymbolic abilities. They also completed a novel two-alternative forced-choice version of the Number Line Estimation Task (dual-NLET), which is introduced in this study as a tool for investigating decision-making processes in number-line estimation by enabling two-choice diffusion modeling. Results showed that accuracy in the traditional NLET correlated with both accuracy and decision efficiency in the dual task. Moreover, symbolic and nonsymbolic numerical abilities were differentially associated with distinct decision-making aspects: symbolic skills correlated with decision efficiency, while nonsymbolic skills correlated with decision threshold. These findings provide new insights into the roles of symbolic and nonsymbolic numerical systems in number-line decision-making and support the utility of the evidence-accumulation approach in developmental numerical cognition research.

Journal of Intelligence doi: 10.3390/jintelligence14030034

Authors: Simge Karakaş Mısır Michael Thomas

This systematic review analyses the evolution of gifted education in England between 2010 and 2025. The year 2010 serves as a critical turning point, characterized by the withdrawal of the national Gifted and Talented (G&T) policy and the subsequent delegation of identification and provision responsibilities to schools. This change created a gap in the literature due to a lack of focused research examining the challenges and deficiencies that emerged following this policy shift. This study is original in that it is the first to bridge existing implementation gaps and provide a robust evidence base for future educational policies. The review focuses on policy frameworks, identification models, and socio-emotional outcomes. Following the PRISMA guidelines, fifteen peer-reviewed studies retrieved from Web of Science, Scopus, and Google Scholar were examined through thematic synthesis. Findings indicate a persistent gap between policy rhetoric and classroom practice. Identification processes remain heavily reliant on standardized testing and teacher judgment, often neglecting creativity, diversity, and contextual factors. Fragmented teacher training limits the ability to effectively support gifted learners, particularly those from disadvantaged or twice exceptional (2e) backgrounds. Socio-emotional outcomes reveal that academic success does not guarantee emotional well-being, highlighting the prevalence of perfectionism and stigmatization. These findings underscore the need for teachers and teacher educators to strengthen pre- and in-service training, so they can better recognize diverse forms of giftedness and support students’ socio-emotional needs through more equitable and research-informed practices.

Journal of Intelligence doi: 10.3390/jintelligence14020033

Authors: Anat Cohen Orit Ezra Efrat Michaeli Guy Cohen Hagit Gabbay Alla Bronshtein

Self-regulated learning (SRL) is a critical competency for learners in increasingly technology-enhanced educational environments, yet little is known about how SRL is fostered within video-based interventions in K-12 settings. While existing reviews and meta-analyses focus on the effectiveness of SRL interventions, this study aims to address current gaps by specifically examining the implementation processes, instructional tools, and the role of video. Addressing this, the present study conducted a systematic literature review of peer-reviewed K-12 intervention studies published since 2010, guided by PRISMA standards and other methodological frameworks in the field of SRL. 30 quantitative or mixed-methods studies focusing on K-12 SRL interventions were selected from Web of Science and ERIC, with the requirement that video served as an instructional component rather than a research tool. These studies were then systematically coded by eight researchers for SRL strategies, instructional methods, video roles, and pedagogical settings. Findings show that most video interventions targeted multiple SRL strategies across different phases of the SRL cycle, offering a comprehensive approach to fostering regulation. However, while cognitive and metacognitive strategies were frequently addressed, motivational and resource-management strategies were seldom included within explicit instruction, which focused primarily on cognitive and metacognitive training. Video played multiple pedagogical roles, including delivering disciplinary content, teaching SRL strategies, or combining both. A thematic analysis identified four pedagogical settings that characterized successful interventions: Teacher-guided, Active, Social, and Knowledge-based (TASK) learning. These settings appear to mitigate common challenges of video-based learning, such as cognitive load and learner passivity. The review contributes a novel synthesis of SRL-video integration and proposes TASK learning as a framework for designing SRL interventions.

Journal of Intelligence doi: 10.3390/jintelligence14020032

Authors: Yifan Wang Jialing Liu Yadan Li Haijun Duan

Stress is a major risk factor for creativity development in adolescents. This study explored the protective effect of openness on creative tendency under stress and revealed the underlying mechanisms from the perspectives of stress perception and cognitive flexibility. A total of 1489 junior high school students (Mage = 13.65 years, SD = 0.74) participated in the study. The results showed that stress perception and cognitive flexibility sequentially mediated the negative effect of stressors on creative tendency, and openness moderated this process. Individuals with high openness had lower stress perception and higher cognitive flexibility at the same level of stressors, thus showing a higher creative tendency. However, the protective effect of openness diminished as the stress level increased. We concluded that openness could buffer the negative effects of stress on creative tendency to some extent. These findings highlight the importance of positive personality traits and provide a theoretical guide for cultivating creative qualities.

Journal of Intelligence doi: 10.3390/jintelligence14020031

Authors: Heeyoon Ko

The author investigates how digital learning competence (DLC) is bridged to academic achievement (AA) through informal digital learning engagement (IDLE) and how meta-cognitive self-regulation (MSR) shapes these pathways among university students. Grounded in a moderated mediation framework, this research conceptualizes DLC not as a static skill set but as a latent capacity that is channeled into academic outcomes when students autonomously engage in digital environments and regulate their cognition. Survey data were collected from 432 undergraduate students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that DLC significantly predicts AA both directly and indirectly via IDLE, identifying informal digital learning engagement as a central pathway through which digital learning competence is translated into academic gains. Furthermore, MSR moderates the relationship between DLC and IDLE, such that higher levels of metacognitive self-regulation strengthen the conversion of digital learning competence into productive informal digital learning engagement. These findings support a dynamic view of digital learning competence and underscore the roles of learner autonomy and metacognitive awareness in transforming digital skills into meaningful educational outcomes. By integrating perspectives on digital literacy, self-regulated learning, and informal learning, this study offers implications for the design of digital learning ecosystems that effectively bridge students’ digital capacities with their academic achievement.

Journal of Intelligence doi: 10.3390/jintelligence14020030

Authors: Yilan Chen Yue Liu Hongyun Liu

The likelihood-based person-fit statistic, lz*, is commonly used in educational assessments to distinguish between respondents who are putting in effort and those who are not. However, lz* depends on the estimated item parameters. Item parameter estimates based on data containing non-effortful respondents are biased, thereby undermining the strength of lz*. To address this issue, we propose a two-step method that leverages data mining techniques to obtain more accurate item parameter estimates and then uses them to compute lz*. The results show that the estimates based on the effortful group identified by K-means are more accurate, which improves the performance of lz* in terms of the precision of identifying effortful respondents when non-effort severity is high.

Journal of Intelligence doi: 10.3390/jintelligence14020029

Authors: Larissa Sust Maximilian Bergmann Markus Bühner Ramona Schoedel

Music is more than just entertainment. It is a complex auditory stimulus that engages various cognitive processing systems. Accordingly, natural music-listening patterns may reveal insights into individual differences in general cognitive ability (GCA). In this study (N = 185), we used real-world smartphone-based music-listening records collected over five months to explore this question. We quantified participants’ listening habits (e.g., listening durations) and music preferences based on audio characteristics (e.g., tempo, mode) and lyrical characteristics (e.g., positive emotion words, affiliation words) of the songs they had listened to. These strictly behavioral features were used to predict GCA scores using linear LASSO regression and nonlinear random forest models. Out-of-sample cross-validation indicated modest predictive performance, with only the random forest model detecting small but reliable associations between music-listening behavior and GCA. Interpretable machine learning analyses showed that lyrics-based preferences were the most informative feature group, followed by listening habits, whereas audio characteristics contributed little predictive value. We discuss how these findings offer initial evidence that cognitive ability may be reflected, albeit subtly, in micro-patterns of everyday, non-achievement-related behavior, and outline conceptual and methodological challenges for future work using digital behavioral data to complement traditional cognitive assessment.

Journal of Intelligence doi: 10.3390/jintelligence14020028

Authors: Evelyn Hsin-I Tsai Yoojin Hahn Robert S. Siegler

Graphs are used in school, many occupations, and daily life, yet many people struggle to interpret them accurately. To help identify sources of difficulty in graph comprehension, we propose the Pictorial–Semantic–Task Framework. In it, we argue that accurate interpretation of graphs requires integrating pictorial variables (e.g., slope direction, graph format, data points) with semantic variables (e.g., titles, labels, scales, variable types) to determine what the graph represents. Many errors arise because readers fail to coordinate these two sources of information, often basing interpretations solely on pictorial variables. The present theoretical synthesis presents the basic analysis underlying the Pictorial–Semantic–Task Framework and an integrative review of relevant findings from graph encoding, extrapolation, and comparison tasks. The findings show that people encode and recall pictorial information far more accurately than semantic information, and often base interpretations solely on visual patterns even when semantic features call for a different conclusion. Analyses of U.S. textbooks and mass media reveal potential sources of these biased interpretations: systematic imbalances in the types of semantic information provided in textbooks and media seem likely to contribute to biases, emphasizing visual over semantic cues. By describing how perceptual and conceptual processes interact during graph comprehension, we aim to advance theories of cognitive processing in the context of graph comprehension and to derive educational implications for helping children interpret graphs more accurately.

Journal of Intelligence doi: 10.3390/jintelligence14020026

Authors: Irina N. Trofimova Michael E. Araki

Polymathy relates to the exceptional learning abilities, in which individuals cultivate and coordinate Breadth, Depth, and integrative capability across multiple domains. It builds on mechanisms typically associated with intelligence, including abstraction, problem solving, and the transfer and integration of information. Because polymathic disposition has partial biological underpinnings, it may intersect with other biologically based individual differences, such as temperament. Biographical accounts also indicate that many polymaths did not achieve exceptional school grades, raising questions about whether the multiplicity of interests in polymaths is associated with distractibility and impulsivity, or whether there is a deeper institutional mismatch between polymaths and educational systems. Our study examined these issues using estimated high school grades across three subject areas, documented university grades, a neurochemistry-validated temperament assessment (Structure of Temperament Questionnaire; STQ-77), the Trait Polymathy Scale (TPS), the Barratt Impulsivity Scales (BIS-11), and information about aptitudes and interests from 296 participants (M/F = 152/144). Contrary to speculation that polymathy reflects distractibility, the TPS correlated negatively with the BIS-11 Lack of Attention scale and positively with the STQ-77 scales of Intellectual Endurance and Probabilistic Processing, confirming high sustained attention in polymaths. TPSs also had selective negative correlations with the STQ-77 Neuroticism scale and positive correlations with the STQ-77 Plasticity, Social Endurance, Sensation Seeking, dispositional Satisfaction scales, as well as several specific and general aptitudes and interests. These findings refine the dispositional profile linked to polymathy, highlighting the differential nature of the three components of polymathy.

Journal of Intelligence doi: 10.3390/jintelligence14020027

Authors: Liping Yang Tao Xin Yunye Yu Yiying Wu

This study investigates the distinct mechanisms of human versus Large Language Model (LLM) creativity. Employing a two-stage experimental design, we systematically compared Human-Only, LLM-Only, and LLM-Assisted performance across propositional and creative writing tasks. Results revealed a critical asymmetry contingent upon the research context: human authors exhibited higher originality in high-demand creative tasks, whereas LLMs governed execution quality, maintaining superior effectiveness across different tasks and cohorts. This pattern is characterized by four exploratory writing creativity profiles: Ideal, Safe, Moderate, and Plain. The distribution of human and LLM writings across these profiles was strikingly different. Hierarchical Moderated Regression analysis uncovered divergent linguistic pathways: human originality is predicted by markers of subjective cognitive investment, while LLM effectiveness is mechanistically driven by optimized structural coherence. Furthermore, the study identified a “Collaboration Trap” during collaboration with a suboptimal LLM. This partnership failed to improve human performance relative to LLM-Only benchmarks and induced cognitive anchoring, leading humans to mimic AI complexity without quality gains. These insights offer critical implications for preserving human agency and avoiding homogenization in future human–AI collaborative writing pedagogies.

Journal of Intelligence doi: 10.3390/jintelligence14020025

Authors: Yoshifumi Ikeda Lorenzo Esposito Yosuke Kita Yuhei Oi Riko Takagi Kent Suzuki Irene Cristina Mammarella Sara Caviola Silvia Lanfranchi Francesca Pulina David Giofrè

In this study, we aimed to investigate the cognitive and affective-emotional factors underlying math achievement in a sample of 169 Japanese elementary school children. Using structural equation modeling, we examined the contributions of fluid and crystallized intelligence, verbal and spatial working memory, and affective-emotional variables, including general anxiety, test anxiety, math anxiety, and math self-efficacy. We found intelligence to be a strong positive predictor of math achievement, while among the affective-emotional variables, math self-efficacy emerged as the only significant predictor of math achievement. Interestingly, intelligence mediated the association between affective-emotional factors, such as math anxiety and self-efficacy, highlighting its central role in children’s math achievement. These findings underscore the strong relationship between intelligence and self-efficacy in educational contexts, suggesting that self-efficacy is closely linked to cognitive abilities to support children’s success in math. Educational implications are discussed, emphasizing the need to strengthen math self-efficacy alongside cognitive abilities.

Journal of Intelligence doi: 10.3390/jintelligence14020024

Authors: Cristina Teixeira Pinto Ângela Coelho Lúcia Guedes Rui Nunes Sara Pinto

This study explores the concept of spiritual intelligence from an evolutionary perspective, providing a comprehensive and updated definition. A concept analysis was conducted following Rodgers’ Evolutionary Method, supported by a scoping review in accordance with the Joanna Briggs Institute methodology. Studies explicitly addressing spiritual intelligence, regardless of population, setting, or discipline, were included across quantitative, qualitative, mixed-methods, and review designs. Four databases—PsycINFO, PubMed Central, Scopus, and Web of Science—were searched for publications up to 15 December 2025, using the term “spiritual intelligence.” One-hundred-twelve articles met inclusion criteria and were analyzed through narrative synthesis and inductive analytical processing. Spiritual intelligence emerged as a construct encompassing adaptive cognition, higher consciousness, problem management, and personal growth, often referred to as Spiritual Quotient or Existential Intelligence. Antecedents included self and transcendental awareness, existential questioning, and search for meaning and purpose, while consequents comprised enhanced health, performance, self-awareness, and humanitarian orientation. Defining attributes were equanimity, life-wisdom, transcendental awareness, spiritual consciousness, meaning and purpose creation, and existential questioning. This evolutionary analysis traced the concept from theory to application, revealing its positive influence in daily life. Equanimity and life-wisdom were identified as core attributes, highlighting implications for training and integration of spiritual care in professional practice.

Journal of Intelligence doi: 10.3390/jintelligence14020023

Authors: Jeremy Lamri Karin Valentini Felipe Zamana Todd Lubart

The ATHENA (Advanced Tool for Holistic Evaluation and Nurturing of Abilities) competency framework proposes a multidimensional approach to human performance structured around five interdependent dimensions (cognition, conation, knowledge, emotion, and sensori-motion), operationalized through 60 fine-grained facets. Although ATHENA is grounded in contemporary psychological theory and supported conceptually by multivariate research in intelligence, creativity, and skill acquisition, empirical evidence regarding the clarity and practical comprehensibility of its facets remains limited. This study investigates the extent to which instructional designers and human resource development (HRD) professionals—two groups who routinely operationalize competencies for learning, assessment, and workforce development—understand and evaluate the semantic clarity and usability of the 60 facets. Seventy-five practitioners completed a structured evaluation of the ATHENA framework facets, which are designed to be used in a hybrid intelligence system for competency management. This article presents the theoretical background, methodological design, and results concerning users’ comprehension of the framework’s components. The findings support, in general, the compatibility of ATHENA’s facets and practitioners’ conceptions.

Journal of Intelligence doi: 10.3390/jintelligence14020022

Authors: Yoonsang Lee Randall Engle

Working memory capacity (WMC) has long served as a central indicator of individual differences in complex cognition. However, growing evidence suggests that a substantial portion of its predictive power may reflect attention control (AC)—including goal maintenance, interference management, and inhibition—rather than storage capacity alone. This review synthesizes findings across six domains: (1) perception and sensory discrimination, (2) learning and problem solving, (3) cognitive control and decision making, (4) retrieval and memory performance, (5) multitasking and real-world performance, and (6) clinical applications. Across these areas, WMC-related effects frequently align with demands on AC, though the strength and nature of this alignment vary by domain. We highlight the importance of incorporating reliable AC measures and recommend latent-variable approaches to more clearly separate storage, control, and representational processes underlying complex performance.

Journal of Intelligence doi: 10.3390/jintelligence14020021

Authors: Maxence Mercier Samira Bourgeois-Bougrine Todd Lubart

This article introduces a theoretical framework centered on enhancing creativity through gaming, termed the Game-based Creativity Enhancement Framework (G-CEF). Rooted in experiential learning and game-based learning theories, the framework adopts an input–process–output paradigm: two inputs (personal attributes and game attributes), one process stage (learning situation), and outputs (learning improvements and acquisitions). Personal attributes take the form of conative dispositions and variables common to both creativity and games, which help explain why gaming habits and creativity are linked, particularly outside the laboratory. Six variables are identified and presented: playfulness, imagination, mind-wandering, mindfulness, psychological capital and motives. The second input corresponds to game attributes, which help explain why and how games can help improve creativity. Two forms of game attributes are presented: affordances and game mechanics. Eight types of affordances were identified: degree of flexibility, narrative, tools, environment, content creation, avatar, progression and replayability. Five types of game mechanics were also identified: originality, divergent thinking, convergent thinking, mental flexibility and creative dispositions. The learning situation within games represents a four-step cyclical experiential learning process: concrete experience, reflective observation, abstract conceptualization, and active experimentation. Lastly, the framework details enhancements in creativity due to gaming, supported by a literature review examining the impact of different game types on creativity.

Journal of Intelligence doi: 10.3390/jintelligence14020020

Authors: Ioannis G. Katsantonis Argyrios Katsantonis

Internationally, there are several studies that examined the relationship between core executive functions (working memory, inhibitory control, and cognitive flexibility) and mind wandering. These studies focused mostly on adult samples and there are fewer studies that examined this relationship with children and adolescent samples. Therefore, the current systematic review aims to identify and critically examine the existing peer-reviewed literature on the relationship between the core executive functions and mind wandering. Journal articles reporting quantitative results were identified through keyword searches in PsycINFO, Scopus, and PubMed. In total, 750 references were identified using the specified keywords. Among those, only ten studies were deemed to fit the inclusion criteria. The majority of the studies employed behavioural measures. The evidence on the relationship between the core executive functions and mind wandering was rather scarce and mixed. Most of the studies suggest that working memory capacity is critical for reduced mind wandering. The evidence regarding inhibitory control is rather mixed. Cognitive flexibility may underpin adaptive reallocation of attention between internal and external states, producing performance declines. The directional nature of the relationship between the three core executive functions and mind wandering is largely an unresolved matter, which requires further research.

Journal of Intelligence doi: 10.3390/jintelligence14020019

Authors: Rotem Berkovich Deanna M. Barch Nachshon Meiran Erin K. Moran

The prevalent method for measuring emotional experiences is self-report scales. However, this method is prone to bias, affected by retrospective errors, and limited in studying individual differences due to variability in how individuals interpret scale values. In the present study, we tested the convergent validity of an alternative approach, which infers emotional components from computational modeling as applied to binary pleasant/unpleasant reports about affective images. Reaction times and choices were modeled to estimate the drift rate (efficiency of emotional evidence accumulation) and the boundary (decision caution). Participants (N = 191) also completed five self-report questionnaires assessing affect, anhedonia, depressive symptoms, and pleasure. Only one correlation reached evidence level (Bayes Factor > 10): Higher consummatory pleasure was negatively associated with drift rate for unpleasant emotions (r(178) = −0.258). This suggests that individuals who typically experience greater in-the-moment pleasure accumulate evidence less efficiently toward unpleasant judgments. Other correlations were absent or inconclusive, potentially reflecting differences in temporal focus and in the specific facets of emotion for each measure. Overall, these results provide some initial support for the convergent and discriminant validity of the drift rate as an indirect measure of online emotional experience.

Journal of Intelligence doi: 10.3390/jintelligence14020018

Authors: Tingrui Yan Yaoqiong Jin

This study explored how mathematics teachers in Chinese special schools provide instructional support to primary-aged students with intellectual and developmental disabilities (IDD). The types, characteristics, and classroom implementation processes of such support were identified to address a gap in the literature regarding subject-specific instructional practices in special education settings. A qualitative research design using interpretative phenomenological analysis (IPA) was employed. Five mathematics teachers from special schools in Shanghai participated in the study. Data were collected through 15 video-recorded classroom observations and five semi-structured interviews. Thematic analysis was conducted to identify key patterns of instructional support. The analysis revealed five core domains of instructional support for students with IDD: (1) comprehension facilitation through simplified explanations, real-life connections, and visual scaffolding; (2) responding to tasks involving prompts, modeling, and hand-over-hand support; (3) maintaining attention using individual and collective cues; (4) sustaining motivation through praise, encouragement, and second-chance opportunities; and (5) regulating behavior such as verbal restraint, physical proximity, and attention redirection. The findings contribute to a deeper understanding of effective instructional support tailored to students with IDD.

Journal of Intelligence doi: 10.3390/jintelligence14020017

Authors: Renqing Zhao Zhiyuan Zhu Zihui Huang

This study aims to develop effective screening tools for cognitive impairment by integrating optimised speech classification features with various machine learning models. A total of 65 patients diagnosed with early-stage Mild Cognitive Impairment (MCI) and 55 healthy controls (HCs) were included. Audio data were collected through a picture description task and processed using the Python-based Librosa library for speech feature extraction. Three machine learning models were constructed: the Random Forest (RF) and Support Vector Machine (SVM) models utilised speech classification features optimised via the Sequential Forward Selection (SFS) algorithm, while the Extreme Gradient Boosting (XGBoost) model was trained on preprocessed speech data. After parameter tuning, the Librosa library successfully extracted 41 speech classification features from all participants. The application of the SFS optimisation strategy and the use of preprocessed data significantly improved identification accuracy. The SVM model achieved an accuracy of 0.825 (AUC: 0.91), the RF model reached 0.88 (AUC: 0.86), and the XGBoost model attained 0.92 (AUC: 0.91). These results suggest that speech-based machine learning models markedly improve the accuracy of distinguishing MCI patients from healthy older adults, providing reliable support for early cognitive deficit identification.

Journal of Intelligence doi: 10.3390/jintelligence14010016

Authors: Yu-Tung Kuo Yu-Chun Kuo

The use of open educational resources (OERs) is on the rise in higher education. Open pedagogy, as a learner-centered approach, provides students with opportunities to create, design, or adapt openly licensed materials or resources. With the potential of open pedagogy to enhance student learning, this study investigated the effect of an open pedagogy project on minority students’ motivation and perceived learning in the computer game programming course. An experimental design was implemented to compare minority students’ learning in programming through the open pedagogy approach versus the traditional approach. Participants were fifty-eight minority students enrolled in game courses from an institution in the southeastern United States. Thirty students received the instruction with open pedagogy, while twenty-eight students were in the traditional instruction. Quantitative approaches were performed to analyze the collected data. The results indicated that minority students in the open pedagogy group perceived significantly higher levels of motivation on the aspect of pressure/tension than those receiving the traditional approach. Minority students participating in the open pedagogy project had significantly higher levels of computational thinking and perceived learning performance in computer programming, compared to the students with the traditional instruction. Major findings and limitations of this study (i.e., short intervention period, small sample size, etc.) were reported and discussed.

Journal of Intelligence doi: 10.3390/jintelligence14010015

Authors: Xinxin Hao Jingxuan Lou Mengyun Jin Yihao Tian

This study leverages longitudinal data from the China Family Panel Studies (CFPS, 2012–2020) to examine the association between teacher support and cognitive ability among children aged 10–16 living in economically disadvantaged rural areas of China. Employing a difference-in-differences (DID) framework, we found that exposure to the Rural Teacher Support Program (RTSP) is associated with an improvement of about 0.19 standard deviations in students’ cognitive abilities after accounting for individual-, family-, and county-level characteristics. Two key mechanisms appear to underlie this association, reflected in increased teacher quantity and enhanced student satisfaction with teachers. Heterogeneity analyses further show that these benefits are more pronounced among female students and those from low-income households, suggesting that teacher-centered institutional improvements may help mitigate developmental disparities. Overall, the longitudinal results indicate that better teacher-related environments are likely to support children’s cognitive development, which in turn may help reduce educational inequality in under-resourced areas.

Journal of Intelligence doi: 10.3390/jintelligence14010014

Authors: Stefan Stieger Selina Volsa David Lewetz David Willinger

Spatial cognition refers to the mental processing, perception, and interpretation of spatial information. It is often operationalized through self-assessments like sense of direction and mental rotation ability or field-based real-world tasks like pointing to a specific building and wayfinding; however, the former and latter entail unclear ecological validity and high participant burdens, respectively. Since the advent of smartphones, this repertoire has been extended substantially through the use of sensors or apps. This study used a large longitudinal experience sampling method (ESM) in two different countries (Canada and Australia, N = 217) and analyzed spatial cognition both conventionally (i.e., sense of direction and speeded mental rotation test) and through new techniques like self-rated and objectively assessed daily Google Maps usage, movement patterns throughout the 14-day assessment phase (using H3 tiles for geolocation), and a Point North task. The Point North task objectively assessed deviation from the celestial direction, North, by using smartphone compass sensors. In both countries, spatial orientation was found to be associated only with the Point North task, while no significant associations were found for daily Google Maps usage (subjectively and objectively measured) and moving distance throughout the assessment phase. Although further validation is required, the Point North task shows promise as an objective, ecologically valid, and easily employable smartphone-based measure for assessing spatial cognition in real-world contexts.

Journal of Intelligence doi: 10.3390/jintelligence14010013

Authors: Fang Fang Yaru Meng Lingjie Tang Yu Cui

Against the backdrop of rapid technological development, informal English learning has become increasingly prominent in language education, particularly among digital natives. However, limited research has examined how digital nativity influences learners’ emotions and their intentions to engage in such learning. This study investigates the relationships among digital nativity, desire, engagement, online learning self-efficacy (OLSE), and learners’ intentions toward informal digital English learning (IDLE). Data were collected from 1458 English learners and analyzed using a structural modeling approach. The results show that desire, engagement, and online learning self-efficacy play significant mediating roles in the relationship between digital nativity and learning intention, while digital nativity also exerts a direct effect on intention. These findings highlight the central role of affective and motivational factors in shaping digital natives’ learning behavior and provide empirical support for the educational value of informal digital English learning in contemporary digital environments.

Journal of Intelligence doi: 10.3390/jintelligence14010012

Authors: Marco Balducci Waseem Haider

The underrepresentation of women in science, technology, engineering, and mathematics (STEM) fields has been a longstanding issue. Traditionally, research on sex differences in cognitive abilities has focused on mean scores, which are often trivial and do not appear to explain sex disparities in STEM participation. Recently, intraindividual strengths have been proposed as a more relevant factor; they reflect an individual’s relative advantage in one skill (e.g., literacy) compared with a set of related skills (literacy, numeracy, and problem-solving). Previous studies have primarily examined younger cohorts, and intraindividual strengths remain unexplored across the lifespan. In this study, we employed data from the second cycle of the Programme for the International Assessment of Adult Competencies (PIAAC) including 157,525 individuals from 30 countries to assess sex differences in literacy, numeracy, and problem-solving as intraindividual strengths across five age groups (16–24, 25–34, 35–44, 45–54, and 55+ years). Consistent with previous research, women outperformed men in literacy, while men outperformed women in numeracy. These patterns were observed universally across countries and age groups. In contrast, no sex differences were observed in problem-solving. Future research should move beyond mean scores to focus on intraindividual strengths, as they may be more relevant for understanding sex disparities in STEM.

Journal of Intelligence doi: 10.3390/jintelligence14010011

Authors: Aiping Zhao Fangzhu Chen Xiang Li

Research on second language (L2) writing has primarily focused on linguistic skills, with limited attention to higher-order cognitive skills such as inference making. This study expands prior research by examining both concurrent and longitudinal effects of linguistic skills (vocabulary, grammatical knowledge, and morphological awareness) and inference making on L2 English writing quality among 135 Chinese high school English learners. Students’ linguistic skills, inference making, and writing were assessed in Grade 10 and Grade 11. Regression analyses showed that, in Grade 10, vocabulary, grammatical knowledge, and inference making significantly predicted writing quality, whereas in Grade 11, morphological awareness, grammatical knowledge, and inference making were significant predictors. Longitudinally, Grade 10 morphological awareness uniquely contributed to L2 writing quality in Grade 11 after controlling for the autoregressive effect of L2 writing quality in Grade 10. These findings highlight the key role of inference making in writing development and reveal that linguistic skills contribute to writing differently across grades. Pedagogically, the results underscore the importance of targeting grade-specific skills to support higher-quality English writing.

Journal of Intelligence doi: 10.3390/jintelligence14010010

Authors: Daniela Molina-Mateo Ivo Leiva-Cisterna Paulo Barraza

Preschool teaching is a highly demanding profession that requires constant socio-emotional attunement and the ability to engage in reflective reasoning. Despite the central role of these skills in effective early childhood education, little is known about whether preschool teachers’ socio-affective and cognitive capacities vary as a function of accumulated professional experience. To address this knowledge gap, we compared the performance of 30 professional preschool teachers with a matched control group of 30 non-teachers on tests measuring emotion recognition, active-empathic listening, interpersonal reactivity, and abstract reasoning. We found that preschool teachers were significantly better on all dimensions of active-empathic listening (sensing, processing, and responding) and better in emotional self-regulation than controls. Moreover, years of preschool teaching experience were positively correlated with emotion recognition, improved listening skills, and more deliberate abstract reasoning strategies. Notably, socio-affective competencies were correlated with abstract reasoning performance within the preschool teacher group. According to these results, long-term professional involvement in preschool teaching enhances socio-affective skills and integrates them with higher-order cognitive processes, both of which are essential for responsive teaching, efficient classroom management, and the development of children’s social and cognitive abilities.

Journal of Intelligence doi: 10.3390/jintelligence14010009

Authors: Leire Aperribai Elena Rodríguez-Naveiras Triana Aguirre Teresa González-Pérez África Borges

Students with high ability (HA), due to their differential characteristics, need to receive a specific educational response for the adequate development of their potential. Thus, they must be detected and then identified, but many of these students (around 9.5%, based on prevalences of domain-specific definitions) remain unidentified, especially among girls. The low detection of highly able students raises the need to establish more objective and efficient criteria. Thus, the objective of this study is to analyze whether the use of objective tests in the procedure increases the number of male and female students detected with HA. To detect students with HA, the general intelligence assessment instrument Matrices-TAI has been applied to students from the first to the third year of Compulsory Secondary Education in different educational centers in the Community of the Canary Islands (N = 1216). The results show that in official data, only 1.17% of HA students (0.89% of girls and 1.44% of boys) have been identified, while 9.21% (8.10% of girls and 10.35% of boys) have a higher intelligence in this convenience sample, coinciding with the percentages of talent found in the literature. In conclusion, in our sample, universal screening with a rigorous intelligence test identified a substantially larger proportion of students, including girls, than current nomination-based procedures appear to capture in administrative statistics, suggesting that such screening may reduce gender disparities in identification.

Journal of Intelligence doi: 10.3390/jintelligence14010008

Authors: Yunze Li Damian Patrick Birney

Working memory (WM) and fluid intelligence (Gf) are highly correlated, which provides the basis for the claim that they share common cognitive processes. Attentional Control Theory and the Relational Integration Hypothesis are two process theories linking WM and Gf. Additionally, both have empirical evidence to support them; the strength of this evidence can be limited by the experimental manipulations used and the operationalisation of performance metrics. To investigate the cognitive processes related to Gf, levels of relational integration and attentional control in the relation monitoring task (RMT) were manipulated. Study 1 (N = 39) focused on calibrating RMT response time windows for different levels of relational integration to strengthen validity claims by reducing possible ceiling effects in RMT performance observed in prior research. Study 2 (N = 146) examined how Gf was related to manipulations of relational integration and attentional control. The research extends previous studies by (a) using experimental manipulations that align more closely to underlying process accounts, and (b) contrasting simple-composite scores, a common operationalisation of performance, with a variance decomposition approach that statistically isolates the hypothetical processes aligned with the experimental manipulations. Results suggest that the way performance is operationalised matters, and that neither relational integration nor attentional control processes alone relate to Gf; instead, predictive utility is greatest when they are operationalised together.

Journal of Intelligence doi: 10.3390/jintelligence14010006

Authors: Shuang Wang An Hu Lu Yuan Wei Tian Tao Xin

Scientific inquiry is fundamental to science education, encompassing the processes through which students construct scientific knowledge and develop thinking skills. However, the unfolding of these inquiry processes and their relation to performance remain underexplored. Drawing on process data from a structured simulation-based assessment task, this study investigated the inquiry processes of 259 fourth-grade students. We applied a multi-analytic approach including sequential pattern mining, entropy analysis, and process mining to capture macro- and micro-level behavioral patterns and examine their associations with task performance operationalized by effectiveness and efficiency. Macro-level analyses revealed that effective students generally organized their inquiry processes into more iterative cycles of evidence collection, demonstrating a more dedicated approach before committing to a final response. Micro-level analyses further indicated that effective and efficient students showed better strategic coordination during experimentation. Together, these findings provide a multi-level characterization of elementary students’ scientific inquiry processes and link inquiry patterns to task effectiveness and efficiency. The study also underscores the potential of process data from simulation-based assessments for diagnosing inquiry skills and informing the design of personalized scaffolds in elementary science education.

Journal of Intelligence doi: 10.3390/jintelligence14010007

Authors: Paul Shing-fong Chan Mantak Yuen Jiahong Zhang

Understanding the factors that promote positive affect and achievement in gifted students is essential for supporting their holistic development and success. This study aimed to explore the relationship among meaning in life (presence and search), character strengths (creativity, perseverance, social intelligence), social connectedness, positive/negative affect, and perceived academic achievement among gifted students in Hong Kong, China. A total of 348 gifted students participated in this study, comprising 196 males and 152 females, aged 10 to 18 years. The students completed a cross-sectional online survey in August and September 2024. Mediation analyses were conducted using structural equation modeling with bootstrapping to estimate indirect effects. The results indicated significant indirect effects of meaning in life (presence and search) and character strengths (creativity, perseverance, social intelligence) on positive affect (β = 0.15 to 0.32, p < 0.05) and negative affect (β = −0.15 to −0.26, p < 0.05) via social connectedness, with small-to-moderate effect sizes. Additionally, significant indirect effects were observed for meaning in life and character strengths on perceived academic achievement via social connectedness (β = 0.13 to 0.20, p < 0.05), with small-to-moderate effect sizes. This research highlights the significant role of character strengths, meaning in life, and social connectedness in enhancing positive affect and perceived academic achievement, and reducing negative affect among gifted students.

Journal of Intelligence doi: 10.3390/jintelligence14010005

Authors: Alberto Ruiz-Ariza José Enrique Moral-García Alba Rusillo-Magdaleno Jose Luis Solas-Martínez

This study aimed to analyze the relationship between moderate to vigorous physical activity (MVPA) and dimensions of emotional intelligence (EI) in Spanish adolescents aged 12 to 16 years, controlling for variables such as gender, age, and body mass index (BMI). A total of 171 students (92 boys; mean age = 13.73 ± 1.34 years) were analyzed, measuring MVPA using the PACE + Adolescent PA Measure and EI using the TEIQue-SF, which includes well-being, self-control, emotionality, and sociability. Physically active adolescents (>4 days/week with ≥60 min of MVPA) showed significantly higher scores in well-being and sociability compared to their inactive peers (p < 0.05), with no differences in emotionality or self-control. Regression analyses confirmed that weekly MVPA was positively associated with well-being and sociability, independent of gender, age, and BMI. These findings suggest that regular MVPA is associated with emotional balance and social competence in adolescents, highlighting the importance of integrating structured PA programs in and out of school. Furthermore, the study underscores the potential of digital and gamified interventions, such as exergames and mobile apps, as promising tools to support the emotional and social correlates of PA by promoting motivation, social interaction, and emotional regulation, offering innovative approaches to support adolescents’ social-emotional development.

Journal of Intelligence doi: 10.3390/jintelligence14010004

Authors: Davide Apicerni Paolo Stievano James Dawe Sergio Melogno Lina Pezzuti

Early identification of cognitive precursors to literacy and numeracy is essential for promoting school readiness and preventing later learning difficulties. Digital assessment tools using touchscreen technology offer advantages of engagement, standardization, and efficiency. This study reports preliminary findings on the Digital Assessment for Preschoolers—Tool (DAP-T), a touchscreen-based battery for preschool children. A sample of 105 children (M = 61.43 months, SD = 10.38; age range = 38–72) completed eight tasks assessing visuomotor integration, literacy (letter knowledge, phonological awareness, notational awareness, Rapid Automatized Naming), and numeracy (non-symbolic quantity comparison, quantity recognition, counting, cardinality). A subsample (n = 47–61, depending on the measure) also completed the paper-based criterion tasks used for concurrent validity analyses. Item difficulty and discrimination, internal consistency (McDonald’s ω), concurrent validity, and factorial structure (SEM) were assessed. Results showed medium-to-low difficulty, age-related performance increases, and good discrimination in most tasks. Reliability was high (ω = 0.713–0.966), and correlations with criterion measures ranged from ρ = 0.52 to 0.95. The DAP-T showed promising psychometric properties as a rapid, standardized tool to detect early difficulties and guide targeted interventions.

Journal of Intelligence doi: 10.3390/jintelligence14010003

Authors: Maria Pilar Agustín Llach

This study explores how adolescent learners conceptualize the emotion of love in their first language (Spanish) and in English as a foreign language (EFL), comparing monolingual Spanish speakers and Spanish–Arabic bilinguals. A total of 66 participants (33 per group), all with A2 proficiency in English, completed a semantic fluency task in both Spanish and English, producing as many words as possible in relation to the prompts Amor and Love. The data were analyzed using graph theory to capture the organization of participants’ emotion lexicons. The results show that love is a highly productive and cohesive semantic field, eliciting significantly more responses in L1 than in L2, for both Spanish-only (t = −8.866, p < 0.001) and Spanish–Arabic (W = 101.0, p = 0.001) participants. The differences between the two learner cohorts were not significant in Spanish nor in English. The results from the graph analyses revealed that learners displayed rich and strongly connected networks in Spanish, with learners with a migration origin showing slightly more fragmented networks. In English, both groups performed similarly, with responses probably mediated by L1 translation equivalents and metaphorical associations (e.g., heart, flower, and red). The findings suggest that emotional lexicons are better developed and more efficiently organized in the L1, whereas FL representations are shaped by proficiency, context of learning, and reliance on L1 conceptual structures. This study contributes novel insights into bilingual and heritage learners’ emotional conceptualization and highlights the value of graph analysis for examining the structure of emotion words.

Journal of Intelligence doi: 10.3390/jintelligence14010002

Authors: Yanbin Guo Guoxiu Tian

Teacher certification is strongly correlated with student development. Many studies have documented the effect of teacher certification on student achievement. However, there are inconsistent conclusions about this issue. Moreover, few studies have examined the mechanisms by which teacher certification promotes student achievement. To fill these gaps, this paper examines the effect of teacher certification on student achievement and the underlying mechanisms. We analyzed the data from the TALIS 2018 Türkiye teacher data and the PISA 2018 Türkiye student data using path analysis and PROCESS Model 6. It was found that the rise in entry requirements for teacher certification was positively associated with teachers’ sense of efficacy and pedagogical innovation in the Turkish context. It was also indicated that teacher certification was positively associated with student achievement through the serial mediation of teachers’ sense of efficacy and pedagogical innovation. The practical and theoretical implications of this paper were discussed.

Journal of Intelligence doi: 10.3390/jintelligence14010001

Authors: Huanhua Lu Yawen Zhao Zaina Jianaer Ruihan Chen

Parental overprotection before adulthood can have enduring consequences for offspring, yet the mechanisms underlying its association with adult physical health are not fully understood. This study proposes trait emotional intelligence (trait-EI) as a pivotal mediating factor in this relationship. A sample of 459 university students (mean age = 22.42 years, SD = 1.43; 50.3% female, 49.7% male) completed measures assessing their recalled parental overprotection, trait-EI and physical health. Results from regression and mediation analyses revealed that parental overprotection was significantly negatively associated with both overall trait-EI and physical health. Critically, trait-EI was found to be a significant mediator, indicating that overprotective parenting impedes the development of trait-EI, which in turn translates into poorer health outcomes. Further analysis of the facets of trait-EI demonstrated that the intrapersonal and stress management dimensions were unique contributors to physical health, whereas interpersonal and adaptability skills were not. What’s more, a moderated mediation analysis showed that gender significantly moderated the pathway from parental overprotection to trait-EI, with the negative effect of overprotection on trait-EI being substantially stronger for male than for female offspring. These findings underscore the role of trait-EI as a central psychological mechanism translating early parenting experiences into long-term physical health and point to the need for gender-sensitive approaches in preventive health interventions.

Journal of Intelligence doi: 10.3390/jintelligence13120165

Authors: Roberto Araya Pablo González-Vicente

Emotional intelligence (EI), specifically the capacity to recognize and understand one’s own emotions and those of others, is pivotal for developing the interpersonal skills that foster effective collaboration. This is especially crucial for developing trust in others, which serves as the necessary foundation for functioning in our increasingly impersonal contemporary society. Although extensive research has been conducted on trust in adults, empirical evidence for children remains limited. Quantifying the extent to which trust exists in young children, whether it differs from trust in adults, and how it changes with age, gender, and various psychological and school culture factors is essential for understanding how educational environments can foster its development. In this article, we analyze trust among almost 3000 fourth-grade children from 135 schools, measured based on behaviors exhibited during a Public Goods Game. The results align with other studies, showing that trust is substantially higher towards the in-group (classmates) than the out-group. A notable gender effect was observed, with boys exhibiting significantly higher levels of trust than girls. Trust was also higher in municipal schools compared to state-subsidized private schools. Personality traits, measured via the Big Five model using the Pictorial Personality Traits Questionnaire for Children (PPTQ-C), also emerged as influential. Specifically, elevated levels of Agreeableness and Conscientiousness predicted increased trust in both in-groups and out-groups. Extraversion and Openness to Experience also played a role, although to a lesser extent.

Journal of Intelligence doi: 10.3390/jintelligence13120164

Authors: Ji Liu Millicent Aziku Dahman Tahri

Prior studies have examined associations between early childhood education and care (ECEC) and cognitive performance in later adolescence. However, little is known about the role of non-cognitive skills development and truancy in this link. To address this gap, the current study investigates how non-cognitive skills and truancy mediate the link between ECEC and cognitive performance among 15-year-old students (N = 550,818), leveraging the Programme for International Student Assessment (PISA) 2022 dataset. Findings indicate that ECEC directly and positively influences non-cognitive skills development and cognitive performance. Non-cognitive skills development is negatively associated with truancy and positively influences cognitive performance. An inverse relationship was found between truancy and cognitive performance. Analyzing this relationship based on gender, it was observed that female students benefited more from ECEC compared to their male counterparts. These results imply that the provision of ECEC may reap substantial social equity benefits.

Journal of Intelligence doi: 10.3390/jintelligence13120163

Authors: Jennifer Balade Cristina Rodríguez Juan E. Jiménez

This study investigates the developmental trajectories of transcription and oral language skills in kindergarten students over the course of an academic year, with a focus on the influence of executive functions (EF) and home literacy practices (HLP). Hierarchical linear modeling (HLM) analyses revealed significant growth in transcription skills, with both EF and independent home literacy practices positively influencing baseline transcription scores. The interaction between independent home literacy practices and formal literacy practices at home further enhanced transcription skill development. In contrast, oral language skills were not influenced by either HLP or EF. These results suggest that EF plays a more prominent role in transcription development than oral language skills in early childhood, especially in transparent orthographic systems. The findings highlight the importance of cognitive and environmental factors in early literacy development, suggesting implications for educational practices, particularly in fostering effective home literacy environments

Journal of Intelligence doi: 10.3390/jintelligence13120162

Authors: Yinghui Wang Mengqi Zhang Huasen Zhang Xin Shan Xiaofei Du

Metacognition and self-regulated learning (SRL) are widely recognized as key mechanisms for academic achievement and skill development, yet in music education they have rarely been examined through explicit instructional interventions to enable causal testing and effect evaluation. To address this gap, this study followed PRISMA guidelines and conducted a systematic review of 31 studies (including seven for meta-analysis) to identify intervention types and mechanisms, and to quantify their overall effects and moderating factors. Results indicate the following: (1) the intervention ecology is grounded in structured learning support (SLS), frequently combined with strategy teaching (ST) or technology-enhanced interventions (TEI), with full integration concentrated at the university level. (2) The mechanisms operate primarily along four pathways: structure facilitates a “plan–practice–reflection” loop, strategy instruction makes tacit experience explicit, technological feedback provides a third-person perspective, and teacher support stabilizes motivation. (3) The meta-analysis revealed a significant positive medium effect overall. (4) Intervention structure moderated outcomes, though not as a single or stable determinant. (5) Effects followed a U-shaped pattern across educational stages, strongest in secondary school, followed by university, and weaker in preschool and primary. Future research should employ proximal, task-aligned measures, conduct parallel multi-indicator assessments within the same stage, and expand evidence for multi-mechanism integration in primary and secondary school contexts. Experimental designs manipulating levels of SLS are needed to test whether ST + TEI remain effective under low-structure conditions, thereby identifying the minimum structural threshold. Extending samples to informal and professional music learners would further enhance robustness and generalizability.

Journal of Intelligence doi: 10.3390/jintelligence13120161

Authors: Urszula Sajewicz-Radtke Ariadna Beata Łada-Maśko Paweł Jurek Michał Olech Bartosz Mikołaj Radtke

Individuals with mild nonspecific intellectual disability (NSID) often exhibit delayed literacy development. Unfortunately, how cognitive–linguistic processing profiles influence literacy in this population lacks clarity. This study investigated literacy development in this population, considering the cognitive–linguistic mechanisms. The Specialist Battery for the Diagnosis of Cognitive Abilities and School Skills was used to assess cognitive–linguistic abilities and literacy-related skills in 122 participants. Fuzzy C-means clustering was used to identify processing profiles. Developmental age equivalents in literacy were estimated using local regression models and matched comparisons with typically developing peers. Two cognitive–linguistic profiles emerged: globally weaker and moderately developed. Those with NSID performed significantly lower than their peers in all domains. Their literacy skills aligned with those of children 2–4 years younger, and plateaued after age 15. Cognitive–linguistic heterogeneity in students with NSID should guide targeted literacy interventions. The findings inform ICD-11 educational expectations for individuals with mild NSID.

Journal of Intelligence doi: 10.3390/jintelligence13120160

Authors: Yan Zhao Yuhe Yue Zhonghua Sun Qiang Jiang Gangsheng Li

The widespread application of Generative Artificial Intelligence (Gen-AI) is transforming educational practices and driving pedagogical innovation. While cultivating higher-order thinking (HOT) represents a central educational goal, its achievement remains an ongoing challenge. Current evidence regarding the impact of Gen-AI on HOT is relatively fragmented, lacking systematic integration, particularly in the analysis of moderating variables. To address this gap, a meta-analysis approach was employed, integrating data from 29 experimental and quasi-experimental studies to quantitatively assess the overall impact of Gen-AI on learners’ HOT and to examine potential moderating factors. The analysis revealed that Gen-AI exerts a moderate positive effect on HOT, with the most significant improvement observed in problem-solving abilities, followed by critical thinking, while its effect on creativity is relatively limited. Moderation analyses further indicated that the impact of Gen-AI is significantly influenced by experimental duration and learners’ self-regulated learning (SRL) abilities: effects were strongest when interventions lasted 8–16 weeks, and learners with higher SRL capacities benefited more substantially. Based on the research findings, this study proposed that Gen-AI should be systematically integrated as a targeted instructional tool to foster HOT. Medium- to long-term interventions (8–16 weeks) are recommended to enhance learners’ problem-solving and critical thinking abilities. At the same time, effective approaches should also be explored to promote creative thinking through Gen-AI within existing pedagogical frameworks. Furthermore, individual learner differences should be accounted for by adopting dynamic and personalized scaffolding strategies to foster SRL, thereby maximizing the educational potential of Gen-AI in cultivating innovative talents.

Journal of Intelligence doi: 10.3390/jintelligence13120159

Authors: Ashutosh Pandey Jasmeet Singh Maninder Kaur

Conversational interactions, rich in both linguistic and vocal cues, provide a natural context for studying these processes. In this work, we propose an explainable multimodal transformer framework that integrates textual semantics (via RoBERTa) and acoustic prosody (via WavLM) to advance emotion understanding. By projecting both modalities into a shared latent space, our model captures the complementary contributions of language and speech to affective communication, achieving an 0.83 accuracy value across five emotion categories. Crucially, we embed explainable AI (XAI) techniques including Integrated Gradients and Occlusion to attribute predictions to specific linguistic tokens and prosodic patterns, thereby aligning computational mechanisms with human cognitive processes of emotion perception. Beyond performance gains, this work demonstrates how multimodal AI systems can support transparent, human-centered emotion recognition.

Journal of Intelligence doi: 10.3390/jintelligence13120158

Authors: Olena Kostiv Antonio F. Rodríguez-Hernández Jonathan Delgado Hernández

This study introduces and validates the construct of Teacher Emotional Commitment (CED), understood as the conative–behavioral dimension that characterizes the emotional bond that teachers establish with their students. To this end, two complementary studies were conducted in the Autonomous Community of the Canary Islands (Spain), with the aim of: to empirically isolate the factorial structure of CED and differentiating it from related constructs, such as empathy; to analyze its presence in both active teachers and those in initial training; and to test the theoretical model’s validity by expanding the sample and enlarging the response scale. Study 1 involved 854 practicing teachers and 701 teachers in training, following a validation process that included exploratory and confirmatory factor analysis, as well as item response theory models. The results showed a four-factor structure: loving proactivity, teacher compassion, instructional commitment, and communicative affectivity, with adequate reliability and discriminant validity indices with respect to empathy. Study 2, with an expanded sample of 2096 participants, confirmed the robustness of the model. The findings allow us to consider CED as a psychological competence that can be trained, with relevant implications for improving the educational relationship, student learning, and the emotional well-being of teachers.

Journal of Intelligence doi: 10.3390/jintelligence13120157

Authors: Jin Zhang Yaxin Wu Yimin Ning Yafei Shi

This study reviews 33 meta-analyses and systematic reviews on Computational Thinking (CT), focusing on research quality, intervention effectiveness, and content. Quality assessment of included studies was conducted using the AMSTAR 2 tool. The meta-analysis achieved an average score of 10.9 (a total of 16 points), while systematic reviews scored an average of 6.1 (a total of 11 points). The 15 meta-analyses showed diverse intervention strategies. Project-based learning, text-based programming, and game-based learning demonstrate more pronounced effects in terms of effect size and practical outcomes. Curricular integration, robotics programming, and unplugged strategies offered additional value in certain contexts. Gender and disciplinary background were stable moderators, while grade level and educational stage had more conditional effects. Intervention duration, sample size, instructional tools, and assessment methods were also significant moderators in several studies. The 18 systematic reviews used a five-layer framework based on ecological systems theory, covering educational context (microsystem), tools and strategies (mesosystem), social support (exosystem), macro-level characteristics (macrosystem), and CT development (chronosystem). Future research should focus on standardizing meta-analyses, unifying effect size indicators, and strengthening longitudinal studies with cognitive network analysis. Additionally, systematic reviews should improve evidence credibility by integrating textual synthesis and data-driven reasoning to reduce redundancy and homogeneity.

Journal of Intelligence doi: 10.3390/jintelligence13120156

Authors: Daisuke Akiba

This theoretical paper introduces the Verbal–Cognitive Scaffold (VCS) Model, a cognitively inclusive framework which proposes the cognitive architectures underlying computational thinking (CT). Moving beyond monolithic theories of cognition (e.g., executive-function and metacognitive control models), the VCS Model posits inner speech (InSp) as the predominant cognitive pathway supporting CT operations in neurotypical populations. Synthesizing interdisciplinary scholarship across cognitive science, computational theory, neurodiversity research, and others, this framework articulates distinct mechanisms through which InSp supports CT. The model specifies four primary pathways linking InSp to CT components: verbal working memory supporting decomposition, symbolic representation facilitating pattern recognition and abstraction, sequential processing enabling algorithmic thinking, and dialogic self-questioning enhancing debugging processes. Crucially, the model posits these verbally mediated pathways as modal rather than universal. Although non-verbal architectures are acknowledged as possible alternative routes, their precise mechanisms remain underspecified in the existing literature and, therefore, are not the focus of the current theoretical exploration. Given this context, this manuscript focuses on the well-documented verbal support provided by InSp. The VCS Model’s theoretical contributions include the following: (1) specification of nuanced cognitive support systems where distinct InSp functions selectively enable particular CT operations; (2) generation of empirically testable predictions regarding aptitude–pathway interactions in computational training and performance; and (3) compatibility with future empirical efforts to inquire into neurodivergent strategies that may diverge from verbal architectures, while acknowledging that these alternatives remain underexplored. Individual variations in InSp phenomenology are theorized to predict distinctive patterns of CT engagement. This comprehensive framework, thus, elaborates and extends existing verbal mediation theories by specifying how InSp supports and enables CT, while laying the groundwork for possible future inquiry into alternative, non-verbal cognitive pathways.

Journal of Intelligence doi: 10.3390/jintelligence13120155

Authors: Muhammet Baştuğ

This study examined the psychometric properties of the Pre-Literacy Test, developed to measure the literacy readiness skills of children who have completed preschool education. Using a quantitative, multistage design, the study was conducted with a total of 5966 children aged 6–7 who were about to enter elementary school in the 2024–2025 academic year (N1 = 1911; N2 = 1644; N3 = 2411). Exploratory Factor Analysis revealed a three-factor structure—Reading Skills, Writing Skills (Dictation), and Writing Skills (Copying)—which explained 82.38% of the total variance. Confirmatory Factor Analysis demonstrated that this structure showed an acceptable model fit (CFI = 0.997, TLI = 0.997, SRMR = 0.030, RMSEA = 0.111). The internal consistency coefficients (α = 0.891–0.962; ω = 0.912–0.983) and convergent validity values (AVE = 0.867–0.949) of the PLT were found to be high. Discriminant validity was confirmed according to the Fornell–Larcker criterion, and measurement invariance across gender was supported through Multigroup Confirmatory Factor Analysis. Item analyses indicated that most test items were of moderate difficulty (mean difficulty = 0.409) and high discrimination (mean discrimination = 0.516). In conclusion, the PLT was determined to be a psychometrically robust, valid, and reliable instrument for assessing basic literacy skills prior to elementary school entry. These findings suggest that the test can be confidently used in early literacy research and school readiness assessments.

Journal of Intelligence doi: 10.3390/jintelligence13120154

Authors: Stephanie Ruth Young Jiwon Kim Kiley McKee Danielle Rothschild Doyle Miriam A. Novack William Revelle Richard Gershon Elizabeth M. Dworak

Standardized cognitive assessments are essential in research but often limited by proprietary restrictions and methodological constraints. This study evaluates the psychometric properties of two public-domain International Cognitive Ability Resource (ICAR) measures implemented in the Mobile Toolbox (MTB) assessment library: Puzzle Completion and Block Rotation. Using a sample of 100 adults (18–82 years), we assessed internal consistency, test–retest reliability, and construct validity compared to gold-standard measures. Results demonstrated acceptable reliability for both Puzzle Completion and Block Rotation. Each measure showed moderate to strong correlations with respective gold-standard assessments: Puzzle Completion correlated with Raven’s Progressive Matrices (r = 0.40), and Block Rotation with Mental Rotation Test (r = 0.46). Practice effects were non-significant. Both demonstrated the ability to discriminate between verbal and nonverbal abilities. Findings were consistent with previous ICAR validations, suggesting MTB provides a viable option for remote self-administration while preserving measurement integrity. This enables larger sample collection and ecological assessment of cognitive abilities outside of laboratory settings.

Journal of Intelligence doi: 10.3390/jintelligence13120153

Authors: Siamak Mirzaei Hooman Nikmehr Sisi Liu Fernando Marmolejo-Ramos

Creativity is increasingly recognized as an essential 21st-century skill, critical for innovation, problem-solving, and personal growth. Educational systems have responded by prioritizing creative thinking, prompting researchers to explore the potential of Learning Analytics (LA) to support and enhance creativity. This systematic review synthesizes empirical studies, theoretical frameworks, and methodological innovations from databases such as Web of Science, Scopus, ERIC, ProQuest, and Google Scholar, examining how creativity is operationalized within LA contexts. The review identifies diverse assessment frameworks, encompassing divergent thinking tests, product-based evaluations, behavioral metrics, and process-oriented assessments, often underpinned by the “4 Ps of Creativity” framework (Person, Process, Product, Press). Tools such as automated scoring systems, multimodal analytics, and AI-enhanced assessments demonstrate the potential to objectively and reliably capture creative processes and outcomes. However, significant challenges remain, including definitional ambiguity, inconsistent metrics, scalability issues, and ethical concerns related to data privacy. This review underscores the transformative capacity of LA to foster creativity in education while highlighting the critical need for standardized, robust methodologies and inclusive frameworks. By addressing identified gaps, future research can advance innovative approaches to assess and cultivate creativity using LA.

Journal of Intelligence doi: 10.3390/jintelligence13120152

Authors: Marco Villalta-Paucar Jéssica Rebolledo-Etchepare Juan Pablo Hernández-Ramos

Although numerous studies address inclusive education, especially in Latin America, research analyzing the overall life satisfaction of teachers in schools that implement inclusion policies are scarce. The purpose of this study is to analyze the relationship between Life Satisfaction, Optimism, Culture, and the Inclusive Practice of primary school teachers from Chile. A descriptive quantitative method was employed, with an ex post facto design including 246 primary teachers from urban and rural schools in Chile. The teachers completed four questionnaires: Inclusive Culture (IC), Inclusive Practice (IP) Satisfaction with Life Scale (SWSL), and Life Orientation Test Revised (LOT-R). The results show that these instruments present acceptable reliability. In addition, a significant correlation was found between Classroom Experience Time (CET) and SWSL (r = 0.201, p < .01), as well as between SWSL, and LOT-R (r = 0.411, p < .01), and IC and IP (r = 0.838, p < .01). The regression model is statistically significant [F (4, 241) = 139.572, p < .001]. The findings indicate that IC and SWSL predict IP directly, whereas CET is an inverse predictor. There is a statistically significant relationship between Life Satisfaction, Classroom Experience Time, Culture, and Inclusive Practice, with the three first variables being predictors of Inclusive Practice.

Journal of Intelligence doi: 10.3390/jintelligence13110151

Authors: Francesca Latino Francesco Tafuri Mariam Maisuradze Maria Giovanna Tafuri

Complex motor tasks that integrate cognitive demands may particularly enhance executive functions, which support school success. Yet few school-based trials have tested structured interventions combining motor complexity and cognitive challenge in early adolescence. Purpose: This study examined the effects of a gamified “Dual-Challenge Circuit” (DCC), integrating motor patterns with cognitive tasks, on executive functions, academic performance, motor skills, and physical fitness among middle school students. Secondary aims were to explore whether executive functions mediated academic gains and whether a dose–response relationship emerged. Method: A cluster-randomized controlled trial was conducted in four middle schools in Southern Italy with sixth- and seventh-grade students. Participants were assigned to either the DCC program or traditional physical education. The 12-week intervention included two weekly 60 min sessions. Outcomes were executive functions (Stroop, Digit Span backward, Trail Making Test-B), academic achievement (grades, MT tests), motor coordination (KTK), physical fitness (PACER, long jump, sit-and-reach), and adherence/fidelity. Results: The DCC group showed significantly greater improvements in all executive function measures and in mathematics and language grades (medium-to-large effects). Mediation analyses confirmed executive functions predicted academic improvements. Motor coordination and fitness also improved, with large effects in aerobic capacity and strength. Conclusions: The DCC effectively enhanced executive functions, academic outcomes, and fitness. Gamified, cognitively demanding physical education formats appear feasible and beneficial in real-world school settings.

Journal of Intelligence doi: 10.3390/jintelligence13110150

Authors: Selina Weiss Lara S. Elmdust Benjamin Goecke

In psychology, small sample sizes are a frequent challenge—particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers—as they reduce statistical power, bias results, and limit generalizability. They also hinder the use of frequentist confirmatory factor analysis (CFA), which depends on larger samples for reliable estimation. Problems such as non-convergence, inadmissible parameters, and poor model fit are more likely. In contrast, Bayesian methods offer a robust alternative, being less sensitive to sample size and allowing the integration of prior knowledge through parameter priors. In the present study, we introduce small-sample-size structural equation modeling to creativity research by investigating the relationship between creative fluency and nested creative cleverness with right-wing authoritarianism, starting with a sample size of N = 198. We compare the stability of results in frequentist and Bayesian SEM while gradually reducing the sample by n = 25. We find that common frequentist fit indexes degrade below N = 100, while Bayesian multivariate Rhat values indicate stable convergence down to N = 50. Standard errors for fluency loadings inflate 40–50% faster in frequentist SEM compared to Bayesian estimation, and regression coefficients linking RWA to cleverness remain significant across all reductions. Based on these findings, we discuss (1) the critical role of Bayesian priors in stabilizing small-sample SEM, (2) the robustness of the RWA-cleverness relationship despite sample constraints, and (3) practical guidelines for minimum sample sizes in bifactor modeling.

Journal of Intelligence doi: 10.3390/jintelligence13110149

Authors: Onciu Oana Prisacaru Flavia

This article presents and validates the Metacognitive Knowledge Intervention for Thinking (MKIT)—an educational framework designed to assess and develop domain-general metacognitive knowledge (MK) in children aged 5 to 9. Moving beyond traditional approaches that examine metacognition within isolated subject areas, this research reconceptualizes MK as a transferable learning resource across content domains and developmental stages. Moreover, by employing a stepped-wedge design—a rigorous but rarely used approach in education—the study introduces a methodological advancement. Simultaneously, MK is operationalized through an ecologically valid and developmentally appropriate format, using visually engaging stories, illustrated scenarios, and interactive tasks integrated within classroom routines. These adaptations enabled young learners to engage meaningfully with abstract metacognitive concepts. Therefore, across three interconnected studies (N = 458), the MKIT provided strong psychometric evidence supporting valid inferences about metacognitive knowledge, age-invariant effects, and substantial gains among children with initially low MK levels. In addition, qualitative data indicated MK transfer across contexts. Thus, these findings position MKIT as a scalable tool, supported by multiple strands of validity evidence, that makes metacognitive knowledge teachable across domains—offering a practical approach to strengthening learning, reducing early achievement gaps, and supporting the development of core components of intelligence.

Journal of Intelligence doi: 10.3390/jintelligence13110148

Authors: Maria Tsakeni Stephen C. Nwafor Moeketsi Mosia Felix O. Egara

This study comprehensively analyses how AI tools scaffold and share metacognitive processes, thereby facilitating students’ learning in STEM classrooms through a mixed-method research synthesis combining bibliometric analysis and systematic review. Using a convergent parallel mixed-methods design, the study draws on 135 peer-reviewed articles published between 2005 and 2025 to map publication trends, author and journal productivity, keyword patterns, and theoretical frameworks. Data were retrieved from Scopus and Web of Science using structured Boolean searches and analysed using Biblioshiny and VOSviewer. Guided by PRISMA 2020 protocols, 24 studies were selected for in-depth qualitative review. Findings show that while most research remains grounded in human-centred conceptualisations of metacognition, there are emerging indications of posthumanist framings, where AI systems are positioned as co-regulators of learning. Tools like learning analytics, intelligent tutoring systems, and generative AI platforms have shifted the discourse from individual reflection to system-level regulation and distributed cognition. The study is anchored in Flavell’s theory of metacognition, General Systems Theory, and posthumanist perspectives to interpret this evolution. Educational implications highlight the need to reconceptualise pedagogical roles, integrate AI literacy in teacher preparation, and prioritise ethical, reflective AI design. The review provides a structured synthesis of theoretical, empirical, and conceptual trends, offering insights into how human–machine collaboration is reshaping learning by scaffolding and co-regulating students’ metacognitive development in STEM education.

Journal of Intelligence doi: 10.3390/jintelligence13110147

Authors: José H. Lozano Susan E. Embretson Javier Revuelta

The present study aimed to investigate individual differences in practice effects during progressive matrices based on Carpenter et al.’s taxonomy of abstract rules. To this end, data from a non-verbal reasoning test, the Abstract Reasoning Test (ART), were used. Because the ART was developed from Carpenter et al.’s theory, the impact of extraneous factors unrelated to the theoretical model is minimized, thereby allowing for a more precise identification of practice effects. The sample consisted of 765 military recruits who responded to 34 items on the ART. Analyses were conducted using a random weights operation-specific learning model (RWOSLM), in which practice parameters were treated as random effects allowed to vary across individuals. The model measures within-test practice effects specific to each examinee, allowing the hypothesis of rule learning during the ART to be assessed at the individual level. Correlations between practice effects and external measures associated with intelligence were examined to investigate the nature of the practice effects. The results suggest individual differences in rule learning within the ART. Decreases in difficulty were observed for both pairwise progression and figure addition or subtraction, although between-person variability was evident only for the latter. Additionally, the results revealed between-person variability in decreases in difficulty associated with one of the items’ figural properties, which suggests the existence of individual differences in the process of increasing familiarity with this feature throughout the test. Individual differences in practice effects during the ART significantly correlated with external measures of abilities and intellect, suggesting that practice effects during progressive matrices are conceptually tied to intelligence.

Journal of Intelligence doi: 10.3390/jintelligence13110146

Authors: Qingshu Xu Huaqing Hong

This study examined the associations among emotional intelligence (EI), grit, motivation, and second language (L2) learning performance, with particular attention to the mediating roles of grit and motivation. A sample of 801 Chinese university students completed validated measures of EI, grit, and motivation, and their English test scores were collected as an indicator of performance. Using structural equation modeling (SEM), EI was positively associated with grit (β = 0.574, p < .001) and motivation (β = 0.426, p < .001), while grit was also positively related to motivation (β = 0.515, p < .001). In relation to performance, significant positive associations were observed with motivation (β = 0.635, p < .001), EI (β = 0.185, p < .001), and grit (β = 0.165, p < .001). Bootstrap analyses confirmed robust indirect associations of EI with performance through grit (β = 0.095), through motivation (β = 0.271), and via the sequential chain EI → grit → motivation → performance (β = 0.188). The model accounted for 33% of the variance in grit, 55% in motivation, and 79% in performance. These findings indicate that EI, grit, and motivation are closely interrelated constructs that jointly contribute to L2 performance, highlighting the importance of socio-emotional and motivational resources in second language learning.

Journal of Intelligence doi: 10.3390/jintelligence13110145

Authors: Tongtong Guan Liqiang Zhang Xingshu Ji Yuze He Yonghe Zheng

Computational thinking (CT) is recognized as a core competency for the 21st century, and its development is shaped by multiple factors, including students’ individual characteristics and their use of information and communication technology (ICT). Drawing on large-scale international data from the 2023 cycle of the International Computer and Information Literacy Study (ICILS), this study analyzes a sample of 81,871 Grade 8 students from 23 countries and one regional education system who completed the CT assessment. This study is the first to apply a predictive modeling framework that integrates two machine learning techniques to systematically identify and explain the key variables that predict CT and their nonlinear effects. The results reveal that various student-level predictors—such as educational expectations and the number of books at home—as well as ICT usage across different contexts, demonstrate significant nonlinear patterns in the model, including U-shaped, inverted U-shaped, and monotonic trends. Compared with traditional linear models, the SHapley Additive exPlanations (SHAP)-based approach facilitates the interpretation of the complex nonlinear effects that shape CT development. Methodologically, this study expands the integration of educational data mining and explainable artificial intelligence (XAI). Practically, it provides actionable insights for ICT-integrated instructional design and targeted educational interventions. Future research can incorporate longitudinal data to explore the developmental trajectories and causal mechanisms of students’ CT over time.

Journal of Intelligence doi: 10.3390/jintelligence13110144

Authors: Bartosz M. Radtke Ariadna Łada-Maśko Paweł Jurek Michał Olech Shally Novita Urszula Sajewicz-Radtke

Dyslexia, a heterogeneous neurodevelopmental disorder, is characterized by persistent reading and spelling difficulties despite average intellectual potential. Although intellectual functioning in dyslexia is often described as average, emerging evidence suggests meaningful within-group variability. This study examined whether children and adolescents with dyslexia exhibited distinct intellectual profiles based on the Stanford-Binet Intelligence Scales, Fifth Edition (SB5). Data were obtained from a large, diagnostically verified sample of 3458 individuals aged 10–19 years assessed in psychological-pedagogical counseling centers across Poland. We used latent profile analysis (LPA) of all 10 SB5 subtests and compared models that specified 2–6 latent classes. The optimal solution identified two profiles: (a) a small subgroup (5%) with globally reduced intellectual functioning and a profound deficit in verbal working memory (>3 standard deviations below the norm) and (b) the predominant subgroup (95%) with broadly average intellectual functioning and relatively preserved reasoning abilities. Profile membership was associated with socioeconomic status; the low-functioning subgroup was associated with lower parental education and age, as younger participants were more likely to belong to this group. These findings highlight the dimensional nature of intellectual heterogeneity in dyslexia and underscore the diagnostic value of profile-based approaches over global intelligence quotient (IQ) scores.

Journal of Intelligence doi: 10.3390/jintelligence13110143

Authors: Juliane Völker Katja Schlegel Marcello Mortillaro

Previous studies suggested that people have stable conflict management styles which relate to their personality traits. However, recent research indicates that conflict management requires flexibility to switch between strategies and that this flexibility may relate to cognitive abilities. The interplay between stable preferences and a flexible performance in conflict management is a novel research avenue. We analyzed data from four studies (N = 1104) using a situational judgment test on emotional intelligence that presents conflict situations in the workplace. We tested whether preferences (selecting one’s typical behavior) mainly relate to personality traits and performance (selecting the ideal behavior) to cognitive abilities. We found that preferences akin to conflict management styles emerged between individuals; however, these preferences did not reflect tangible differences in personality traits. Considering performance, cognitive abilities were consistently conducive to solving conflicts, while the contribution of personality traits varied across situations, with the possibility that some traits may even hinder conflict resolution in some situations. We provide preliminary evidence on the contributions of both traits and abilities to conflict management, arguing that conflict management research needs to adopt a holistic view that combines both a person’s traits and abilities to explain their conflict behavior.

Journal of Intelligence doi: 10.3390/jintelligence13110142

Authors: Felix M. Schweitzer Nele M. Lindenberg Monika Fleischhauer Sören Enge

In this preregistered multi-level meta-analysis, we aim to clarify the association of need for cognition (NFC) and typical intellectual engagement (TIE) with intelligence and executive functions. Multi-level models with robust variance estimation were specified and risk of bias was assessed with the adapted Risk of Bias Utilized for Surveys Tool. NFC/TIE was associated with fluid intelligence (Gf; r = 0.18, p < .001, N = 25,367), crystallized intelligence (Gc; r = 0.26, p < .001, N = 14,651), general intelligence (r = 0.23, p < .001, N = 8479), and working memory (WM) capacity (r = 0.15, p < .001, N = 5921). Associations with WM updating (r = 0.08, p = .111, N = 1084), inhibition (r = 0.04, p = .077, N = 2895), and shifting (r = 0.01, p = 0.642, N = 1727) were non-significant. NFC (r = 0.19) was more strongly related to Gf than TIE (r = 0.12; F(1, 12.10) = 5.04, p = .045) whereas TIE (r = 0.35) was more strongly associated with Gc than NFC (r = 0.24; F(1, 13.10) = 10.70, p = .006). Correlations with Gc significantly declined over time (b1 = −0.006, β1 = −0.04, p = .010). Results provide strong evidence for small-to-moderate associations of NFC and TIE with Gf, Gc, general intelligence, and WM capacity, and at best small associations with core executive functions.

Journal of Intelligence doi: 10.3390/jintelligence13110141

Authors: Nesip Demirbilek

This study examined the relationships among shared leadership, organizational attractiveness, and organizational identification among teachers in Malatya, Türkiye. Using a relational design and structural equation modeling, the research explored how these variables interact. Data were collected via validated scales, revealing positive and significant associations among shared leadership, organizational attractiveness, and organizational identification. Shared leadership and organizational identification were found to significantly predict organizational attractiveness, explaining a substantial portion of its variance. The model demonstrated a good fit, supporting theoretical frameworks related to social identity and shared leadership. Findings highlight that participative leadership is positively associated with teachers’ perceptions of their organizations within a centralized education system. This study offers valuable implications for school leaders and policymakers seeking to enhance teacher engagement and organizational culture. Limitations include the study’s regional focus and cross-sectional design, underscoring the need for broader, longitudinal research to deepen understanding in diverse contexts.

Journal of Intelligence doi: 10.3390/jintelligence13110140

Authors: Fei Wang Zhaosheng Luo Ying Miao Shuting Zhou Lang Zheng

To meet the growing demands for competency-based and personalized instruction in high school English reading, this study investigates a quantitative approach to modeling learning pathways and progressions. Traditional assessments often fail to capture students’ fine-grained cognitive differences and provide limited guidance for individualized teaching. Based on cognitive diagnostic theory, this study analyzes large-scale empirical data to construct a progression framework reflecting both the sequencing of cognitive skill development and the hierarchical structure of reading abilities. A Q-matrix was calibrated through expert consensus. A hybrid cognitive diagnostic model was used to infer students’ knowledge states, followed by cluster analysis and item response theory to define progression levels, which were mapped to national curriculum standards. The findings reveal that students’ mastery of cognitive attributes follows a stepwise developmental pattern, with dominant learning trajectories. The constructed learning progression aligns well with curriculum-based academic quality levels, while uncovering potential misalignments in the positioning of some skill levels. Students with identical scores also showed significant variation in cognitive structures. The proposed model provides a data-informed foundation for adaptive instruction and offers new tools for personalized learning in English reading comprehension.

Journal of Intelligence doi: 10.3390/jintelligence13110139

Authors: Dzenita Kijamet Rachel Wollschläger Ulrich Keller Sonja Ugen

Nonverbal tests assess cognitive ability in multicultural and multilingual children, but language-based instructions disadvantage non-proficient children. This is a growing concern worldwide due to the increasing number of multilingual classrooms. The tablet-based FLUX (Fluid Intelligence Luxembourg) test was developed within a highly multicultural and multilingual educational context to offer not only nonverbal test content but also language-fair animated video instructions. A total of 703 third graders (Mage = 8.85, SD = 0.66; 48.8% females, 51.1% males, 0.1% with no gender specified) were included in the standardisation sample and were assessed with tasks measuring figural fluid intelligence, quantitative fluid intelligence, visual processing and short-term memory. The test proved sufficiently reliable (FLUX Full-scale: McDonald’s Omega = 0.94; split-half = 0.95). Test fairness was ensured by analysing each item for Differential Item Functioning (DIF) on children’s background characteristics (language spoken at home, socioeconomic status, gender). Its factorial structure was confirmed using Confirmatory Factor Analysis (CFA). Further validity evidence was provided by determining its concurrent and criterion-related validity (correlations with a test of cognitive ability and educational achievement scores). Research implications and future prospects in promoting equal opportunities in a heterogeneous multilingual educational context are discussed.

Journal of Intelligence doi: 10.3390/jintelligence13110138

Authors: Daniela Fiedler Samantha Barton Ulrike Kipman

The relationship between cognitive abilities and students’ achievement in math is well documented. However, theoretical views on the chronological development of cognitive ability and math success remain controversial. Empirically, mutual effects between these concepts amongst primary school children have not yet been adequately addressed, because longitudinal data have mostly been limited to two measurement time points. The present study aims to fill this gap by investigating whether cognitive abilities can predict math success across time (unidirectional effect) or whether a reciprocal effect according to the theory of mutualism is more in line with longitudinal data. It also provides information on the stability of intelligence and mathematics achievement in primary school children. Taking into account four measurement occasions, cognitive ability, and achievement in math, N = 1726 primary school students were annually examined. We analyzed construct-specific latent variables and cross-lagged effects over four years. Results indicate a unidirectional cross-lagged relationship pattern rather than a mutual effect between reasoning ability and math achievement. However, over time, the influence of math achievement on cognitive ability increases slightly, which stresses the importance of knowledge acquisition in math for cognitive development over time, and a fairly high stability of cognitive ability and mathematics achievement in primary school age.

Journal of Intelligence doi: 10.3390/jintelligence13110137

Authors: Zhengyu Liu Lu Jiao

The present study employed immersive virtual reality (iVR) technology to create a multimodal enriched learning environment and investigated the effects of pre-training on sleep-dependent consolidation of novel word learning. Native Chinese speakers were randomly assigned to either a pre-training group or a control group. Both groups learned two sets of novel words, one on Day 1 and the other on Day 2. All participants completed an explicit recognition task and an implicit semantic priming task on Day 2. The results reveal the sleep-dependent consolidation effects in the implicit measures, with enhanced semantic priming observed for words learned on the previous day following a sleep interval. Moreover, the pre-training yielded additional benefits for sleep-dependent consolidation, as evidenced by the improved sleep-dependent consolidation effects of the pre-training group as compared with the control group. However, no sleep-dependent consolidation and pre-training effects were observed in the explicit recognition task. These findings suggested that pre-training serves as an effective strategy to reduce cognitive load and facilitate novel word learning in iVR environments. This study provides new evidence for the pre-training principle of cognitive load theory from the perspective of sleep-dependent consolidation.