Search Results (178)

Gifted education is gaining traction in many non-Western contexts, including the United Arab Emirates (UAE), which has developed many policies to develop giftedness. However, the identification of giftedness relies heavily on instruments developed in Western contexts, which have the potential to derail efforts toward promoting gifted education in the UAE. This study aimed to present data on 999 grade 4 to 12 students who completed the UAE’s national gifted identification test, known as the Hamdan Gifted test. Guided by the Cattell–Horn–Carroll theory, this study reports data on ability tests (verbal ability, nonverbal ability and preknowledge of mathematics and science) completed by students across the UAE between 2018 and 2023. The results revealed that 53% of the participants demonstrated superior ability in science, whereas 19% reported superior ability in mathematics. The percentage of students who demonstrated superior ability in other domains was as follows: verbal ability (52%; word crossing), verbal ability (14; true/false) and nonverbal ability (29%). The study concludes with recommendations for teacher development to enhance the teaching of mathematics to gifted students in schools in the UAE and beyond. Full article

The aim of this study was to understand the female swimmers’ annual performance progression and stability between 10 and 18 years across swimming distances and techniques. Data from female Portuguese Top-50 rankings in the short-course pool was extracted from an open access database (swimrankings.net). Performances were grouped by distances (50-, 100- and 200 m) and techniques (freestyle, backstroke, breaststroke and butterfly), totalizing 12 events as performance metrics. A total of 343 swimmers and 3087 performances distributed by nine consecutive competitive seasons were retrospectively assessed. The mean and normative stability were computed for tracking performance trends, while reporting the year-to-year percentage improvement. The differences across distances and techniques were tested with a linear mixed-effects model using intraclass correlation coefficient (ICC). The performance progression was characterized by marked improvements during the early ages (up to 13% yearly) and an emerging plateau around the 15–16 years. The stability patterns varied between events, with the backstroke technique (ICC = 0.13) demonstrating greater consistency of individual differences on developmental trajectories, whereas shorter races (i.e., 50 m; ICC = 0.15) tended to be more stable than 100 m or 200 m (ICC = 0.12). It can be concluded that female swimmers’ performance stabilizes at the 15–16 years of age. Despite reduced differences, the backstroke technique and short distances seem to show a slightly more stable trend in progressing from childhood to adulthood. Full article

Background: Talent identification (TID) programmes aim to detect adolescents with high physical potential, yet the efficiency of finding high-performance talent across different testing environments in an Australian context is unknown. The current study aim was to calculate the likelihood of participants scoring at or above the 90th percentile in anthropometric or physical performance measures across different testing settings. Methods: We analysed retrospective, cross-sectional physical and performance data from 10,134 Australian adolescents aged 12–17 years (4427 girls; 5707 boys) tested in either schools (2992; 3500), advertised come-and-try TID “Select” sessions (1235; 1622), or community-based amateur sports clubs (200; 585). Standardised measures used across all settings included height, body mass, and five physical performance tests of strength, speed, agility, leg power and aerobic fitness. We used a threshold of “higher physical performance” or “physical talent” as an age- and sex-specific ≥90th percentile ranking in any of the performance tests when compared against our international normative database. Anthropometry measures were also compared using the same approach across settings. Results: Chi-square tests showed girls had significantly higher (p < 0.001) prevalence of ≥90th percentile scores in all performance results in Select, and all except speed in Sport settings compared to Schools testing. No differences were found for either height or body mass across settings (p = 0.078 and 0.17, respectively). Boys exhibited smaller differences, with Sport settings yielding significantly higher sprint and agility scores ≥90th percentile (p < 0.05), relative to both Schools and Select testing environments. Differences were found for height and body mass across settings (p < 0.001 for both analyses, respectively). Conclusions: Select environments enhance the identification of physically talented girls, while boys demonstrate broader distribution of performance talent across settings. Findings inform resource allocation for future TID programmes when the primary aim is to maximise the efficiency of finding higher-performance physical talent relative to the number of tests conducted. Full article

This study examines the role of artificial intelligence (AI) technologies in identifying and sustaining leadership talent within the educational sector in Oman, addressing the increasing demand for evidence-based and innovative approaches to leadership development. A qualitative phenomenological research design was employed to explore how AI experts and educational leaders perceive, evaluate, and conceptualize AI-driven tools for leadership talent identification and sustainability. In-depth semi-structured interviews were conducted with 25 participants from three major Omani educational institutions. Data were analyzed using thematic analysis, allowing systematic identification of recurring patterns, conceptual relationships, and shared professional insights. The findings indicate that AI applications—including big data analytics, behavioral assessment tools, competency identification platforms, and predictive analytics—provide effective mechanisms for early detection and assessment of leadership potential. Furthermore, integrating AI into personalized professional development programs and continuous performance evaluation contributes to the long-term sustainability and strategic utilization of leadership talent. This study underscores the potential of AI to enhance strategic leadership planning within educational institutions. The results expand our empirical understanding of AI-driven leadership development and offer practical insights for implementing AI-informed strategies in Oman and the broader Gulf region. Full article

This study aimed to identify distinct lactate kinetic phenotypes in professional soccer players using unsupervised machine learning and determine their relationship with maximal running velocity (V_max) through explainable artificial intelligence methods. A total of 361 professional male soccer players from the First Division participated in the study. Incremental treadmill tests measured lactate concentrations at five standardized velocities, alongside VO_2max, V_max, lactate threshold (LT), and anaerobic threshold (AT) parameters. Three distinct lactate kinetic phenotypes emerged: Economical Aerobic (n = 216), Balanced Metabolic (n = 19), and High Producer (n = 126). The Economical Aerobic phenotype demonstrated superior performance metrics compared to High Producer (V_max: 15.85 ± 0.85 km/h; VO_2max: 56.20 ± 4.26 mL/kg/min; p < 0.001). Initial multicollinearity assessment revealed notable collinearity among all 10 candidate predictors (VIF > 10; maximum VIF = 10.75 for V_AT), necessitating rigorous feature selection. Ridge regression with 4 selected features (V_AT, VO_2max, 9.5 km/h lactate, 14 km/h lactate) achieved moderate but statistically significant predictive performance: 10-fold cross-validation R²= 0.392 ± 0.147 (permutation test p = 0.001). Standardized coefficients identified V_AT (β = 0.399) as the dominant predictor, followed by VO_2max (β = 0.253), 9.5 km/h lactate (β = 0.107), and 14 km/h lactate (β = −0.066). Lactate kinetic phenotyping reveals position-independent metabolic profiles with potentially meaningful performance associations in professional soccer. The Economical Aerobic phenotype demonstrates performance advantages associated with superior anaerobic threshold capacity. These exploratory findings suggest that individualized training strategies based on metabolic phenotype rather than playing position alone warrant further investigation, with potential applications for talent identification, training periodization, and return-to-play protocols pending prospective validation. Full article

Children gifted for music are often described as possessing heightened perceptual and sensory abilities, yet little is known about how these abilities are understood within different family contexts or how giftedness is experienced as an identity. This mixed-methods study examined alignment between gifted children’s and parents’ perceptions of children’s mental–perceptual abilities, the role of parental musical background, and how giftedness is explained and emotionally negotiated. Twenty-two children identified as gifted for music and 25 parents completed a survey based on Gagné’s Differentiated Model of Giftedness and Talent assessing six mental–perceptual abilities, followed by semi-structured interviews. Quantitative analyses revealed a strong positive association between child and parent ratings, alongside a consistent tendency for parents to provide higher evaluations. Parental professional musical background did not significantly moderate alignment but was associated with greater variability in both children’s and parents’ ratings. Qualitative findings indicated shared experiential understandings of ability across families, alongside systematic differences in evaluative frameworks: musician parents more frequently drew on technical, comparative, and training-based standards, whereas non-musician parents relied on affective and everyday observations. Children across contexts often expressed modesty or ambivalence toward being labeled gifted, while parents balanced pride with concern about pressure. Overall, perceptions of mental–perceptual ability emerged as relationally constructed within family environments that shape how musical giftedness is recognized and supported. Full article

Traditional talent identification systems often rely on static assessments and overlook the dynamic nature of long-term development. To address this limitation, this study proposes a biomimetic predictive framework inspired by crayfish behavioral ecology. The Crayfish Optimization Algorithm (COA), derived from adaptive foraging and competition mechanisms observed in crayfish, is enhanced through a Thinking Innovation Strategy (TIS) to form TISCOA for hyperparameter optimization of a Gradient Boosting Decision Tree model. Using a five-year longitudinal dataset of 160 elite mathematical students, the framework models Professional Achievement in Mathematics (PAM) from multidimensional baseline indicators. Comparative experiments with multiple metaheuristic optimizers show that the proposed approach achieves stable generalization performance within the examined cohort. Feature attribution analysis indicates that non-cognitive factors, particularly Emotion Regulation, contribute substantially to long-term outcomes, while temporal variables such as the Latency Period further shape developmental trajectories. Residual analysis highlights heterogeneous patterns that may reflect unobserved contextual influences. Overall, the study demonstrates how a biologically inspired optimization mechanism can support interpretable and stability-oriented longitudinal prediction in small-sample educational settings. Full article

Background: This cross-sectional observational study aimed to describe the position-specific kinanthropometric characteristics of Mexican professional American football players competing in the 2019–2020 seasons of the Liga de Fútbol Americano. Methods: A total of 189 athletes were assessed following International Society for the Advancement of Kinanthropometry standards. Twenty-six anthropometric variables were measured to estimate body composition (five-way fractionation), somatotype, proportionality indices, and tissue-specific masses. Positional differences were examined using ANOVA or Kruskal–Wallis tests with corresponding effect sizes (η² or ε²). An exploratory stepwise discriminant analysis identified the anthropometric dimensions contributing most to positional differentiation, and classification accuracy was calculated. Results: Offensive and defensive linemen showed the greatest absolute size and higher adipose, muscle, and bone mass compared with other positions. The overall somatotype corresponded to a balanced endomorphic mesomorph (3.8–7.0–0.8), with wide receivers and defensive backs presenting lower endomorphy. The discriminant model identified arm relaxed girth, biiliocristal breadth, and sitting height as the variables contributing most to positional differentiation, achieving a classification accuracy of 57.7%. Given its exploratory nature and the absence of cross-validation, the discriminatory capacity of the model should be interpreted with caution. Somatotype Attitudinal Mean indicated greater interpositional heterogeneity among linemen. Conclusions: This study provides population-specific reference data for Mexican professional American football players, highlighting clear positional morphological characteristics. These findings may support talent identification and positional profiling; however, the exploratory discriminant model and league-specific sample limit generalization to other populations. Full article

Handgrip strength (HGS) has been considered as an indicator of muscle strength and overall physical fitness, with increasing relevance in sports science for talent identification and performance monitoring. However, no bibliometric study has been conducted to map the HGS research landscape in athletic contexts. A bibliometric analysis was conducted in the Web of Science Core Collection database, retrieving 229 publications. Typical bibliometric laws (i.e., Price’s, Bradford’s, Lotka’s, and Zipf’s) were employed to analyze publication trends, core journals, influential authors, country contributions, and keyword co-occurrences. Annual publications increased exponentially, especially after 2019, reaching 37 documents in 2024. The Journal of Strength and Conditioning Research and Journal of Sports Medicine and Physical Fitness were the most prominent journals. The United States and Spain led in productivity and impact. Key research themes included strength, performance, body composition, and physical fitness, with HGS demonstrating significant associations with sport tasks such as throwing, racquet sports, and weightlifting. HGS constitutes an accessible and valuable tool for assessing and predicting athletic performance, especially in sports requiring upper body strength and coordination. Future research should aim to expand database inclusion and address identified gaps, such as the relationship between HGS training and sport-specific outcomes. Full article

With the ongoing reform of higher education, the University Practice Education Community (UPEC) has become a crucial platform for advancing collaborative education and innovating talent cultivation models. However, research remains insufficient on the influencing factors of UPEC’s sustainable development and, in particular, on how these factors interact with one another. From a complex systems perspective, this study conceptualizes UPEC as a dynamic and interconnected system in which multiple factors jointly shape sustainability outcomes. Accordingly, the overall objective is to (i) identify key influencing factors, (ii) model and quantify their interrelationships, and (iii) pinpoint critical factors and interaction pathways that structure UPEC sustainability. Adopting this holistic view, we integrate literature review, expert interviews, questionnaire surveys, and social network analysis (SNA) to systematically identify and analyze twenty influencing factors. SNA, as a systems-oriented analytical tool, enables the mapping of structural relationships and interaction pathways among factors, revealing how these interdependencies collectively form the governance ecosystem of UPEC. The results identify eight key factors—including willingness for multi-stakeholder collaboration, stability of cooperation mechanisms, policy and institutional support, effectiveness of communication and coordination mechanisms, feedback and improvement mechanisms, enthusiasm of industry and enterprise participation, local government support, and influence of public opinion—along with five critical paths linking subsystems through chain effects. Based on this diagnostic evidence, this study further outlines strategy implications to support practice-oriented improvement, while the primary contribution remains the identification of key factors and critical interaction structures underlying UPEC sustainability. Full article

Artificial intelligence (AI) is a scientific and engineering discipline that involves designing systems capable of autonomously replicating the cognitive functions typically associated with human intelligence. Current AI uses data to extract patterns, supports decision-making, and enhances analytical reasoning across diverse domains, including sports performance or strategic claims, and assists in clinical applications. In sports, AI enables robotic systems to assist in training, object tracking, performance monitoring, strategy development, and talent identification. In medicine and rehabilitation, AI facilitates robotic surgery, rehabilitation training, and decision-support systems. Machine learning and deep learning techniques, combined with computer vision, enable estimation of human posture and movement in 2D or 3D from video recordings, providing objective, quantitative, and markerless movement analysis. For instance, human pose estimation systems, including open-source and framework tools, have been applied for multi-athlete and individual tracking, performance assessment, and injury prevention. Additionally, AI-powered systems and generative AI for data simulation enhance strategy planning and training efficiency. This review provides a comprehensive overview of AI applications in human movement assessment, highlighting methodological approaches, practical implementations, and emerging technologies. Understanding the capabilities and limitations of these systems helps optimize human movement assessment and support data-driven decisions. Full article

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. Full article

Students with autism spectrum disorder (ASD) represent a growing population in U.S. higher education, including those with academic talents and gifts. Our research team has studied these academically talented students with ASD, along with their teachers, parents, counselors, and disability service providers at highly competitive colleges and universities in the United States. Using qualitative methodology and thematic analysis, this study examined factors and experiences relating to how self-perceptions of identification as twice exceptional contributed to academic success among 40 students with ASD attending highly competitive colleges. A focus of this research was the role that participants’ perception of their talents, disabilities, and learning experiences played in their academic success. Findings indicate that slightly under half of the participants believed they had a clear understanding of their academic talents and their ASD during college. Their self-perceptions of ability varied over time and based on various academic and social challenges, but most believed an understanding of their twice-exceptionality was necessary for their academic success. Over time, particularly during their college years, participants learned to better understand their talents and disabilities and to identify which strength-based experiences helped to shape their success. Students’ positive experiences, such as success in advanced, accelerated, and interest-based classes as well as enjoyable extracurricular activities, positively enhanced their self-perceptions of academic abilities and promoted confidence in future educational and career paths. Full article

Background/Objectives: Swimming requires precise motor control, sustained attention, and optimal cognitive–motor integration, making it an ideal model for investigating neural efficiency—the phenomenon whereby expert performers achieve optimal outcomes with reduced neural resource expenditure, operationalized as lower activation, sparser connectivity, and enhanced functional integration. This systematic review examined cognitive performance and neural adaptations in swimming athletes, investigating neuroimaging and behavioral outcomes distinguishing swimmers from non-athletes across performance levels. Methods: Following PRISMA 2020 guidelines, seven databases were searched (1999–2024) for studies examining cognitive/neural outcomes in swimmers using neuroimaging or validated assessments. A total of 24 studies (neuroimaging: n = 9; behavioral: n = 15) met the inclusion criteria. Risk of bias assessment used adapted Cochrane RoB2 and Newcastle–Ottawa Scale criteria. Results: Neuroimaging modalities included EEG (n = 4), fMRI (n = 2), TMS (n = 1), and ERP (n = 2). Key associations identified included the following: (1) Neural Efficiency: elite swimmers showed sparser upper beta connectivity (35% fewer connections, d = 0.76, p = 0.040) and enhanced alpha rhythm intensity (p ≤ 0.01); (2) Cognitive Performance: superior attention, working memory, and executive control correlated with expertise (d = 0.69–1.31), with thalamo-sensorimotor functional connectivity explaining 41% of world ranking variance (r² = 0.41, p < 0.001); (3) Attention: external focus strategies improved performance in intermediate swimmers but showed inconsistent effects in experts; (4) Mental Fatigue: impaired performance in young adult swimmers (1.2% decrement, d = 0.13) but not master swimmers (p = 0.49); (5) Genetics: COMT Val158Met polymorphism associated with performance differences (p = 0.026). Effect sizes ranged from small to large, with Cohen’s d = 0.13–1.31. Conclusions: Swimming expertise is associated with specific neural and cognitive characteristics, including efficient brain connectivity and enhanced cognitive control. However, cross-sectional designs (88% of studies) and small samples (median n = 36; all studies underpowered) preclude causal inference. The lack of spatially quantitative synthesis and visualization of neuroimaging findings represents a methodological limitation of this review and the field. The findings suggest potential applications for talent identification, training optimization, and mental health promotion through swimming but require longitudinal validation and development of standardized swimmer brain atlases before definitive recommendations. Full article

Background: Rowing performance in youth athletes is strongly influenced by anthropometric characteristics, body composition, and limb proportions; however, the combined contribution of these factors across developmental stages remains insufficiently understood. This study investigated the relationships between key anthropometric variables and ergometer performance in a multinational cohort of young rowers. Methods: A total of 194 athletes (48 females, 146 males) from ten countries participated. Based on age and sex, participants were categorized into junior female (JF), junior male (JM), adult female (AF), and adult male (AM) groups. Body height, body mass, body fat (F%), relative muscle mass (M%), limb lengths, and body surface area (BSA) were measured. Rowing performance was assessed via maximal 2000 m ergometer trials. Results: Males outperformed females across all age groups (p < 0.001). Performance showed strong positive correlations with body height (r = 0.673, p = 0.003), body mass (r = 0.724, p = 0.005), arm span (r = 0.681, p = 0.002), lower-limb length (r = 0.394, p = 0.004), relative muscle mass (39.9 ± 5.2%; r = 0.531, p < 0.001), and especially BSA (1.94 ± 0.19 m²; r = 0.739, p < 0.001). Relative body fat was negatively associated with performance (17.6 ± 6.9%; r = −0.465, p < 0.001). Conclusions: Findings indicate that rowing performance in youth athletes reflects multidimensional anthropometric configurations rather than isolated traits, characterized primarily by the combined contribution of body surface area, relative muscle mass, and segmental body dimensions. From a practical perspective, higher-performing athletes typically exhibited body surface area values approaching or exceeding ~1.90 m² and relative muscle mass above ~40%, suggesting these ranges as indicative reference benchmarks rather than fixed selection thresholds. Integrating anthropometric profiling with physiological assessment may enhance early talent identification and support individualized training strategies in competitive youth rowing. Full article