Contemporary streaming platforms increasingly feature narratives with complex temporal structures that pose significant cognitive demands for audience comprehension. This study examines the narrative strategies employed to support cognitive processing in complex non-linear storytelling, using Netflix's "Dark" (Season 1) as a case study. The series presents a multi-timeline narrative spanning 1953, 1986, and 2019, with recurring characters across different ages, creating potential cognitive load challenges.

We conducted a quantitative content analysis of all eight Season 1 episodes, systematically coding 1,247 narrative segments for temporal characteristics, character appearances, scene transitions, and structural features. Statistical analyses included correlation tests, multiple regression, one-way ANOVA, and structural equation modeling to examine relationships between narrative complexity metrics and embedded cognitive support mechanisms.

Results revealed that despite high temporal fragmentation (mean temporal distance = 31.35 years, SD = 14.62), the narrative systematically embeds compensatory mechanisms to facilitate comprehension. Temporal anchors—visual and narrative cues establishing time period—appeared in 68.4% of segments, with their frequency significantly correlating with timeline complexity (r = .412, p < .001). Episodes with greater temporal fragmentation demonstrated increased use of establishing shots (r = .338, p < .001) and reduced scene complexity (β = -.284, p = .006). Structural equation modeling confirmed that these cognitive scaffolding strategies mediate the relationship between narrative complexity and potential cognitive load.

These findings illuminate how complex narratives incorporate external cognitive supports that may enable viewers to process information exceeding traditional working memory constraints. The study contributes to understanding how narrative design can scaffold cognitive processing and has implications for theories of distributed cognition, multimedia learning, and complex information architecture.

Cognitive ability remains a core construct in psychology and education, yet debates persist regarding the most relevant construct, methodologically rigorous approaches, and its measurement implications. This study aims to conduct a bibliometric study of cognitive measurement published from 2011 to 2025, focusing on global research trends. Using the Dimensions.ai database and Bibliometrix R package, 1,083 journal articles were fit with inclusion criteria, retrieved, and analyzed. Performance analysis revealed a very small, yet not significant, annual growth of publications over fifteen years and a significantly decreased citation rate per document. The analysis also shows that current studies were predominantly published by correspondence authors from German and Anglophone countries. Schulte-Körne emerged as the most productive author, Intelligence as the most impactful journal, and Nisbett’s paper, "Intelligence: New Findings and Theoretical Developments", as the most cited article. Meanwhile, science mapping based on keyword co-occurrence, multiple correspondence analysis, and thematic mapping showed psychology as the central hub connecting related fields. Research regarding cognitive ability measurement was conducted along the lifespan, with motor themes centered on humans and gender, basic themes related to cognition and adulthood, and niche themes including psychometrics and preschool assessment. Overall, cognitive measurement appears as a maturing, interconnected, yet concentrated research domain. Future research should continue to advance toward cross-cultural, cross-disciplinary, and interdisciplinary approaches that prioritize collaboration and the adoption of advanced technologies to foster continued innovation and scientific progress in this field.

The identification and development of high-potential talent constitutes a cornerstone of organizational success, yet evidence-based pathways for realizing this objective remain insufficiently articulated in the scientific literature. Traditional talent identification is often driven by biased assumptions, including the confusion of high performance with high potential (Chamorro-Premuzic, 2019; Kehoe, Collings, & Cascio, 2023; Mahadi, Thangaraj, Baskaran, & Mahadi, 2019; Schleu et al., 2024), the equation of confidence with competence (Anderson & Kilduff, 2009; Belotelova & Martin, 2025; Chamorro-Premuzic, 2019; Stewart et al., 2000), and the belief that dysfunctional personality traits are effective leadership qualities (Brunell et al., 2008; Diller et al., 2021). Corporate scandals (e.g., Weissner, 2024; Nossiter, 2019; Mollan, 2024) illustrate the severe consequences of inadequate leadership assessment and advancement, often revealing a critical lack of interrelational abilities among organizational leaders (McCallum & O’Connell, 2009). Existing frameworks frequently oversimplify cognitive abilities and fail to capture the complex nature of human potential due to conceptual limitations, for instance, the conflation of personality and intelligence (Church & Silzer, 2014; Hyde et al., 2020). This research aims to advance Talent Management by conceptualizing high-potential talent through a clear theoretical lens and offering a unique definition (Gallardo-Gallardo et al., 2013; Tansley, 2011). Building on Sternberg’s (1985) Triarchic Theory of Intelligence, the proposed model introduces a two-tiered triarchic framework. It integrates Individual Cognitive Abilities (analytical, practical, and creative intelligence) with Interrelational Cognitive Abilities (social, emotional, and cultural intelligence) in the cognitive evaluation of employees with global leadership potential. This enhanced categorization highlights interrelational qualities, as effective leadership is inherently tied to followership (Stern, 2021). High-potential talent is thus defined as an individual within an organization who possesses the cognitive abilities, both individual and interrelational, to grow and succeed, particularly in leadership. This framework addresses shortcomings in Talent Management and lays the groundwork for subsequent scale development and empirical testing.

This paper reports empirical findings from a convergent mixed-method action research study examining teachers’ perceptions of students’ attentional functioning in digitally mediated and hybrid learning environments. Data were collected from 356 in-service teachers through a validated 10-item Likert scale (α = .95) and an open-ended qualitative prompt, and data were analysed using descriptive statistics, Principal Component Analysis (PCA), multiple regression, and thematic analysis.

Results show a strong and homogeneous convergence across school levels and disciplines, with item means ranging from 4.17 to 4.30 (0–5 scale), indicating a widespread perception of significant attentional disruption. Teachers consistently report fragmented and intermittent attention, early cognitive fatigue, high sensitivity to digital stimuli, and rapid engagement–disengagement cycles. PCA identified two latent dimensions explaining 64% of total variance: (1) methodological alternation and cognitive sustainability (41%), highlighting the regulatory role of multimodal, segmented, and recursive instructional design and (2) attentional discontinuity and cognitive overload (23%), reflecting attentional patterns consistent with neurocognitive models of plastic adaptation in high-density digital environments. Regression analyses identify training in digital pedagogy and AI literacy as significant predictors of teachers’ sensitivity in recognising these emerging attentional patterns. Qualitative findings corroborate quantitative results, revealing micro-attentional cycles, embodied signs of overload, emotional–cognitive saturation, and the ambivalent role of technology depending on instructional design.

This study contributes an evidence-based, neuro-pedagogical account of attention as a situated and design-regulable process within onlife cognitive ecologies, empirically bridging teachers’ perceptions, neurocognitive theory, and instructional design. It advances current debates by demonstrating that attentional fragmentation is not merely a behavioural deficit but a structurally modulated phenomenon that can be mitigated through intentional pedagogical design.

Introduction: Middle school represents a critical stage for shaping future academic trajectories, particularly regarding STEM (Science, Technology, Engineering, Mathematics) participation. While cognitive abilities are known predictors of academic success, less is known about how they interact with affective-motivational factors and gender to influence school track choice over time. This longitudinal study investigated the specific contribution of gender, cognitive abilities (intelligence, working memory, and inhibitory control), and affective-motivational factors (math self-concept, interest, and anxiety) in predicting the choice between STEM and non-STEM high school tracks at the end of middle school.

Methods: Data were collected from a sample of 159 Italian students assessed longitudinally in the seventh and eighth grades. Participants completed standardized cognitive measures to assess general intelligence, working memory, and inhibitory control, alongside self-report questionnaires assessing their math anxiety, interest, and self-concept. Hierarchical logistic regression analyses were performed to determine the incremental contribution of each predictor to the likelihood of choosing a STEM curriculum.

Results: Findings indicated that gender and positive attitudes toward math were the strongest predictors of school choice. Boys were significantly more likely than girls to pursue STEM tracks. Notably, higher levels of math self-concept and interest significantly predicted the likelihood of choosing a STEM school. Crucially, the direct influence of actual cognitive performance was minimal and overshadowed by affective-motivational factors and gender in the final decision-making process.

Conclusions: These results highlight that students’ perceptions of their competence and their interest in the subject may outweigh their actual cognitive performance when determining educational pathways. To promote equitable access to STEM and reduce the persistent gender gap, educational interventions should focus not only on cognitive skill enhancement but also on fostering positive self-concepts and enthusiasm for mathematics during early adolescence.

The modern educational environment requires primary school students to acquire not only academic knowledge, but also the ability to understand themselves and others, to cooperate, make decisions, and build successful relationships. The educational environment emphasizes the development of socio-emotional intelligence, but the context of its development—​​the cultural environment and culture—is not emphasized. Personal cultural competence is based on five emotional intelligence skills: mindfulness, empathy, goal-setting, self-regulation, and communication. The aim of this study is to investigate the role of social–emotional intelligence in the development of personal cultural competence of primary school students in the learning process. The case study used a quantitative survey method of 246 students and 8 teachers, comparing the results in one Latvian and one Lithuanian general education school. Students in grades 4, 6, and 8 were surveyed. The questionnaires assessed the students' ability to be aware of their strengths and weaknesses, understand their emotions, and cooperate in situations of cultural understanding and expression in the learning process. Interviews with teachers allowed us to analyze the impact of their pedagogical methods and choices on the development of students' emotional intelligence skills in the context of cultural competence. Two different education systems from different countries were selected. The Lithuanian education system includes general cultural competence, with its content developed in detail, but that of Latvia does not. The results revealed that students with a higher level of awareness and greater involvement in cultural processes at school and outside it are also more empathetic, able to communicate better, and take responsibility for their decisions in organizing their self-expression. The conclusions confirm that social and emotional intelligence is an integral part of the cultural competence of a person. Students who develop these five emotional intelligence skills are also able to show better assessed academic learning results.

Human intelligence is often described as an individual ability, yet research in education shows that children think and learn through the support of different forms of mediation that appear in their everyday activity (Vygotsky, 1978). In mathematics education, studies have highlighted how gestures, materials and representations help children construct and communicate meaning (Bartolini Buss & Mariotti, 2008; Bartolini Bussi & Baccaglini-Frank, 2015). Building on findings from the Norwegian projects DiCoTe and VERDI, we propose that children’s intelligent behaviour is shaped by a broader range of mediational processes than those traditionally considered in semiotic theories.

The study is based on 21 video observations (15 from one project and 6 from the other), each lasting on average about 40 minutes, complemented by detailed field notes. Children engaged in mathematical exploration and technological play, and the material was interpreted through an inclusive research approach (Johnson & Walmsley, 2003) in which teachers, students and co-researchers with Intellectual and Developmental Disabilities (IDD) work together (Granone et al., 2023; Granone, 2025). This approach made it possible to identify how children use not only signs and representations, but also bodily movement, spatial orientation, touch, rhythm, dialogue and technological tools to test ideas, solve problems and explain their thinking.

Across the two projects, these multiple mediations were visible in children’s problem-solving with coding toys (Granone & Reikerås, 2023), their spatial reasoning during activities with digital and physical artefacts (Granone & Knudsen, 2024), and in the ways they interacted with adults in supportive and dialogic environments (Granone & Pollarolo, 2025). These observations suggest that intelligent behaviour does not emerge only from internal cognitive processes but from participation in rich, multimodal and relational situations.

We discuss that supporting human intelligence requires recognising and valuing these layered forms of mediation. Expanding the concept of mediation helps us better understand how children think and offers new directions for designing inclusive and cognitively supportive learning environments in early childhood education.

Understanding human intelligence requires integrating cognitive theories with the neurobiological architectures that sustain reasoning, working memory, information updating, and adaptive learning. Contemporary evidence positions intelligence as an emergent property of coordinated neural systems, including the prefrontal cortex, central to executive control and working memory, the parietal cortex, which supports abstract problem-solving, visuospatial computations, and mathematical reasoning, and the hippocampus, which enables relational encoding and flexible memory retrieval. Large-scale network connectivity further underpins efficient information processing, linking these regions into a dynamic architecture of intelligent behavior.

To illustrate how these mechanisms manifest under pathological conditions, we examined intelligence-related cognitive processes in the 5xFAD transgenic model of Alzheimer’s disease, characterized by early impairments in mnemonic integration, attentional regulation, and cognitive flexibility. Six bioactive extracts derived from Rubus fruticosus were administered via oral gavage for seven days and prior to behavioral testing. Cognitive performance was assessed using validated animal analogues of core components of fluid intelligence: the Radial Arm Maze for working and reference memory, Y-Maze spontaneous alternation for spatial updating and cognitive flexibility, Novel Object Recognition for encoding efficiency, and Open Field-based metrics for exploratory attention. Galantamine served as the positive control.

Extract-specific enhancements were observed across working memory accuracy, alternation behavior, and recognition indices, with several compounds approaching or surpassing galantamine’s performance. Preliminary neurobiological analyses suggest reductions in amyloid burden and inflammatory markers, pointing toward synaptic and circuit-level mechanisms supporting cognitive resilience.

By bridging neurobiological theory with behavioral evidence from a transgenic model, this contribution refines our understanding of how core cognitive processes underlying intelligence deteriorate and may be partially restored under neurodegenerative conditions. These findings position Rubus fruticosus bioactives as promising modulators of intelligence-related cognitive architecture.

Many studies have already highlighted the impact of education on human intelligence. Ritchie (2018) in a conducted meta-analysis of142 studies and over 600,000 subjects identified consistent evidence about the beneficial effects of education on cognitive abilities (even stating an approximately 1 to 5 IQ points for each additional year of education), effects that persisted across the life span and were evidenced across all broad categories of cognitive ability studied. Thus, the author considers education to be 'the most consistent, robust, and durable method yet to be identified for raising intelligence'.

School is the framework through which education produces its shaping effects.

Like human diversity, each school has its own organizational specificity. Therefore, through our proposal, we will illustrate the process of building a model based on the application of Universal Design for Learning in the Romanian school context (preschool and primary classes).

This case study illustrates the internal development solution identified within the IncluzivEduHub project by applying a specific Quality deployment methodology (Voice of the beneficiary, Affinity Matrix, Problem/Solution Tree) based on identifying the needs of the beneficiaries, addressing students at risk of academic difficulties and also those with high abilities. Starting from the needs of the beneficiaries, we ensure optimal cognitive adaptive evolution through Universal Design for Learning and educational therapeutic interventions for 226 students.

Supported by a specific inclusive intervention model, we introduced screening and coteaching and also peer mediation, collaborative learning, art and somatic therapy. The proposed model is proof that the school must assume social functions to identify and support the development potential of each individual student, showing the significant results obtained by stimulating creativity, teamwork, and the joy of learning in specific ways directly addressed to their known developmental needs. Every child matters!

Previous research on reasoning tests has revealed relatively consistent evidence for an item-position effect (IPE). To explain this effect, the learning hypothesis has been put forward, positing that learning the rules underlying the items leads to increasing individual differences from the first to the last item of a reasoning test. For a better understanding of the type of learning contributing to the IPE, the current study examined whether implicit learning was associated with the IPE in a reasoning test. For this purpose, 193 participants completed a Figural Analogies Test with 21 items, which were not ordered according to their difficulty, and a Serial Reaction Time (SRT) task comprising 2x8 blocks of ten 10-trial sequences each. Using bifactor modeling, a latent reasoning and a latent IPE variable could be identified in the reasoning test, with the latter characterized by monotonically increasing factor loadings. Implicit learning was evidenced by a significant reduction in response times across the blocks of the SRT task, where the same 10-trial series was always repeated (experimental condition), but not in the eight blocks of the control condition. From the response times in the experimental condition, two latent variables were extracted. Factor loadings of the first latent variable were fixed at the same value; factor loadings of the second latent variable increased strictly monotonically across the learning blocks, representing individual differences in the continuous (implicit) learning process. Latent reasoning ability was significantly but weakly related to implicit learning, whereas the correlation between the IPE and implicit learning just failed to reach statistical significance. Therefore, the present results supported the assumption of an association between reasoning ability and implicit learning. The IPE in the reasoning test, however, was unrelated to implicit learning, suggesting that it does not rely on implicit learning.