Search Results (1,017)

Evaluating large language models (LLMs) critically depends on human judgment. This article reviews and develops a conceptual framework for human-centered LLM evaluation, synthesizing research across evaluation methodology, psychometrics, cognitive science, and domain-specific applications. Four primary challenges are identified that limit current human evaluation practice: imperfect gold standards, evaluator fatigue and overload, shared and unique bias structures across humans and LLM judges, and the routine omission of uncertainty and dispersion estimates. To address these gaps, the STEP-V design framework is proposed: Stakes, Task-type, Evaluator availability, Purpose, and Volume, for selecting human and/or automated LLM evaluation methods under real-world constraints. An evaluator failure mode taxonomy is also proposed that analyzes human and LLM judges within a common error framework, clarifying where hybrid pipelines can compensate for weaknesses and where they might compound them. The framework motivates a more rigorous science of LLM evaluation, one that treats human judgment as a necessary but fallible measurement requiring explicit design, calibration, and uncertainty quantification. Full article

In a global business environment marked by digital disruption, Small and Medium-sized Enterprises (SMEs) must integrate digital transformation with strategic agility and organizational resilience. This study addresses the fragmentation of the current management literature by developing an AI-driven meta-theory through a high-performance computational synthesis of 4811 academic publications from the OpenAlex database. Utilizing a theoretically grounded hybrid framework of lexical filtering (TF-IDF), semantic embedding (SciBERT), and a diverse ensemble of five Large Language Models (LLMs), we move beyond descriptive mapping to identify the ontological and integrative mechanisms of SME adaptation. The methodology is validated through a multi-stage expert audit of model reasoning traces to ensure theoretical alignment. Results reveal a clear dominance of Contingency Theory (20.5%) and Resource-Based View (14.1%), which are re-conceptualized here as Regulatory–Technical Brokerage and Internal Fortification. Through Social Network Analysis (SNA) and Aggregate Constraint metrics, the study identifies Innovation Frontiers that are operationally challenging to synthesize through traditional manual reviews at this scale. The research concludes by formulating four meta-theoretical propositions and an integrative synergetic mechanism, explaining how SME resilience emerges as an emergent property of cross-layer alignment between technical, cognitive, and structural logics. By providing this causal roadmap, the study establishes a robust, AI-augmented blueprint for SMEs to function as intelligent, self-regulating nodes within a Post-Normal digital ecosystem. Full article

Digital games have been increasingly recognized as promising tools for supporting meaningful learning in school contexts. This study examined the effects of Alien Health, an embodied video game designed to promote nutrition and healthy eating learning among fifth-grade students in Chile. A quasi-experimental repeated-measures design was conducted with 327 students from 10 public, subsidized-private, and private schools in the Province of Concepción. Using pre-existing fifth-grade classes, participants were organized into a control group, who received traditional teacher-led instruction and an experimental group, who engaged with the video game without teacher mediation. Learning outcomes were assessed using the Nutrition and Healthy Eating (NHE) test, a 10-item curriculum-aligned instrument developed for this study and reviewed by expert teachers. The test was administered at pretest, posttest, and delayed retest. Data were analyzed through repeated-measures ANOVA, considering total scores, curricular sub-objectives, and Bloom-based cognitive categories. Results showed a differentiated pattern over time. Control students tended to achieve higher scores at the immediate posttest, particularly in tasks associated with factual recall, whereas experimental students showed more stable performance at delayed retest and stronger outcomes in some higher-order tasks, especially food classification and integrative diet design. Differences in school type and gender were also observed, suggesting that the effects of the intervention varied across educational contexts. Overall, the findings indicate that embodied video games may serve as a valuable complement to traditional instruction by supporting longer-term knowledge retention and conceptual integration in primary education. The study contributes empirical evidence from a Latin American context to the literature on embodied learning, game-based education, and nutrition teaching. Full article

Financial reporting standards aim to increase transparency; however, the expansion in disclosure volume may also create an information overload paradox for investors, an issue that remains underexplored in the context of institutional investors. Excess information beyond mandatory requirements may complicate decision environments and create cognitive burden. When information exceeds cognitive processing capacities, attention may become fragmented, making it more difficult to distinguish signal from noise and potentially leading to analysis paralysis and changes in risk perception. Drawing on bounded rationality and cognitive load theory, this study conceptualizes information overload as a behavioral constraint associated with perceived limitations in decision quality and speed and, accordingly, examines its influence on institutional investors’ decision processes through a phenomenological approach. The study employs thematic analysis based on in-depth interviews with 19 professionals in institutional investment organizations in Türkiye. The findings suggest that information overload is experienced as cognitive strain that may prolong decision processes, may be associated with analysis paralysis and perceived changes in decision quality, and may be associated with increased uncertainty and potential challenges in interpreting risk. These findings provide exploratory insight into how information density may influence risk interpretation and portfolio assessment, and how institutional investors perceive decision-making efficiency. Full article

Neurodegenerative diseases are among the most consequential disorders of later life, not only because of their increasing prevalence, rising from approximately 1–2% at age 65 to over 30% by age 85, but also because they develop within the broader clinical context of ageing, multimorbidity, frailty, and polypharmacy. In older adults, these conditions rarely present as isolated and static diagnostic entities; rather, they unfold as dynamic clinical trajectories involving the progressive interaction of cognitive decline, behavioural-neuropsychiatric symptoms, and extrapyramidal-motor dysfunction. In this review, we propose a trajectory-based framework for the interpretation and management of major neurodegenerative disorders in later life, including Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease and Parkinson’s disease dementia, dementia with Lewy bodies, and vascular cognitive impairment. Building on a conceptual model organized around three major symptom spheres: cognitive, behavioural-neuropsychiatric, and extrapyramidal-motor, we argue that each disorder can be understood according to the relative predominance and temporal evolution of these domains. Alzheimer’s disease is typically cognition-led, frontotemporal dementia behaviour-led, and Parkinsonian syndromes motor-led, whereas dementia with Lewy bodies shows early multidomain convergence across all three spheres simultaneously. Vascular and mixed dementias follow more heterogeneous trajectories shaped by lesion burden, network disruption, and copathology. This framework has direct implications for diagnosis, prognostic stratification, and treatment selection, because interventions targeting one sphere may destabilize another and generate prescription cascades, delirium, or functional decline. We further discuss how biomarker-based diagnosis, disease-modifying therapies, non-pharmacological interventions, multidisciplinary care, deprescribing strategies, and palliative planning can be integrated within a trajectory-based approach. Interpreting neurodegeneration through clinical trajectories rather than diagnostic labels alone offers a more realistic and therapeutically useful model for precision geriatric neurology across the full course of disease. Full article

This study investigates the transition toward green transportation in Hanoi through a culture-centered perspective by integrating the Culture Tower (KAUC) framework with PLS-SEM analysis. Using survey data from 172 urban residents, the research examines how factors of knowledge, action, perceived utility, contribution, infrastructure, and social norms interact to shape green transport policy acceptance. The findings reveal that sustainable mobility functions as a layered cultural process rather than a simple behavioral sequence. Environmental awareness emerges as the central driver, exerting significant direct and indirect effects on contribution and policy acceptance, while green transportation infrastructure influences acceptance primarily through normative and cognitive pathways. The absence of strong experiential reinforcement between action, utility, and contribution suggests that behavioral engagement has not yet consolidated into stabilized cultural practice. By conceptualizing policy acceptance as the outcome of accumulated cultural layers rather than short-term cost–benefit evaluation, the study advances a systemic and culturally grounded approach to green transport governance. The results underscore the importance of reinforcing environmental knowledge, stabilizing social norms, ensuring reliable infrastructure, and fostering participatory contribution to achieve durable, green mobility transitions in rapidly urbanizing contexts. Full article

Industry 4.0 (I4.0) is transforming industrial systems through interconnected, data-driven technologies, raising questions about how these developments affect Occupational Health and Safety (OHS). This study investigates research trends, thematic structures, and knowledge gaps at the intersection of I4.0 and OHS using a multilevel bibliometric framework applied to Scopus records published from 2011 to 2025. The analysis moves from a broad overview of the I4.0 landscape to more focused examinations of specific I4.0–OHS publications, prevention-oriented studies, and emerging-risk research. The results show that OHS has limited visibility in the general I4.0 literature and is more prominent mainly in targeted subsets, where digital sensing, artificial intelligence, machine learning, and immersive technologies drive prevention-focused research. Conversely, emerging risks such as cognitive load, psychosocial stressors, and human–autonomy interaction appear in smaller, more dispersed clusters. Overall, the findings suggest that the relationship between I4.0 and OHS is unevenly developed, with established prevention mechanisms and early-stage conceptualization of new risks. Strengthening this field will require integrating human factors with digital indicators, better characterizing emerging risks, and ensuring that digital transformation supports SDG 8 by fostering safe and healthy working environments. Full article

This conceptual article introduces knowledge-centric recruitment (KCR) as a distinct dynamic capability that reframes recruitment and post-hire socialization as strategic knowledge-development activities. (1) Background: Unlike conventional vacancy-driven approaches, KCR is a proactive process through which firms deliberately access and import external organizational capabilities embodied in senior professionals—termed knowledge-hires—from rival organizations. These knowledge-hires embody tacit, socio-cognitive building blocks of capabilities developed through involvement in their prior employers’ routines and practices. (2) Methods: This article develops a micro-foundational model of KCR comprising four interrelated processes: external capability scanning and prioritization, identification of target capabilities and knowledge-hires, evaluation through the novel lens of contextual capability fit, and expectations of adaptation during onboarding. (3) Results: Contextual capability fit integrates complementary and supplementary quality with knowledge distance to enable firms to forecast both the strategic value of inbound capabilities and the hire’s expected socialization difficulty. (4) Conclusions: The primary theoretical contribution lies in advancing the learning-by-hiring literature by shifting the focus from passive knowledge diffusion to deliberate, calculative capability acquisition. By integrating insights from the knowledge-based view, person–organization fit, absorptive capacity, and strategic recruitment, the KCR model offers a coherent micro-foundational framework for transforming employee mobility into a source of sustained competitive advantage. Full article

Creativity relies on dynamic processing within the semantic network system; however, how this system varies under different cognitive strategies remains unclear. Grounded in the Associative Theory of Creativity, this study applied four cognitive strategies (application, analogy, abstraction, and combination) as distinct input constraints to the cognitive system. We tracked the N400 component using event-related potentials (ERPs), which capture brain activity time-locked to specific cognitive events. Specifically, the N400 serves as a reliable neural marker reflecting semantic mismatch and the integration of new information. Repeated-measures analysis of covariance (RM-ANCOVA) revealed that the abstraction strategy yielded the highest level of creativity, while the application strategy yielded the lowest. Neural data indicated that attenuated N400 amplitudes under the application strategy reflected minimal prediction errors within familiar conceptual spaces, whereas pronounced N400 amplitudes under abstraction and combination strategies represent substantial cognitive effort associated with feature extraction and concept integration. Subsequent linear mixed-effects model (LMM) analysis revealed that the N400 component exerted a significant negative moderating effect on individual creativity under the analogy strategy, establishing a boundary condition for transforming semantic updating into final creative output. By exploring associative processes through micro-neural mechanisms, this research provides practical insights for optimizing creative task design and evaluation structures. Full article

Ethno Sense is defined as a culturally mediated cognitive–perceptual capacity through which individuals discern, select, and interpret mathematically salient structures in socially situated practices. The increasing recognition of mathematics as a culturally situated practice has prompted growing interest in integrating cultural contexts into mathematics education. Approaches such as ethnomathematics and Realistic Mathematics Education emphasize the importance of culture and meaningful contexts; however, a critical gap remains in explaining how individuals perceive and recognize mathematical structures within culturally embedded experiences. This entry addresses this gap by introducing Ethno Sense as a novel conceptual construct. Conceptualized as a pre-formal layer of mathematical cognition, it explains how culturally conditioned perception, interpretive schemas, and value systems shape the recognition of mathematical meaning prior to formalization. It proposes a mechanism comprising contextual indexing, schema activation and selection, and value-informed interpretation. These processes operate dynamically to guide engagement with culturally meaningful phenomena and the identification of mathematical relevance. The entry further positions Ethno Sense as an epistemological foundation for Ethno-Realistic Mathematics Education, supporting authentic context selection and progressive mathematization. By foregrounding culturally mediated perception, it shifts attention from problem solving to recognizing situations as mathematically meaningful. This study contributes a unifying theoretical construct linking cultural experience and mathematical cognition, and outlines implications for practice and future research on culturally situated learning. Ultimately it offers a lens for understanding reciprocal relationships between culture and mathematics across educational contexts. Full article

The growing reliance on artificial intelligence (AI)-based recommendation systems is transforming e-commerce into a space where decision-making is increasingly co-constructed between users and intelligent systems. However, it remains insufficiently understood how the transparency of these systems influences users’ trust and purchasing decisions within human–AI collaboration contexts. Addressing this gap, the study develops a conceptual model that explains the role of cognitive mechanisms in the relationship between AI transparency and consumer behavior. Specifically, algorithmic understanding and fairness perception are conceptualized as cognitive processes through which users evaluate AI-generated recommendations, while perceived control is positioned as a key link between these evaluations and trust formation. The model is empirically tested using partial least squares structural equation modeling (PLS-SEM) based on data collected from 312 users of recommender systems. The results highlight the role of cognitive mechanisms and perceived control in explaining the effects of AI transparency on trust and, indirectly, on purchase intention. AI literacy also shapes how users interpret the information provided by the system. The present research provides an integrated perspective on human–AI collaboration in e-commerce, with relevant implications for the design of recommender systems and the optimization of user experience. Full article

Dementia care research has been largely shaped by Western biomedical and cognitive paradigms that privilege verbal, linear, and memory-dependent methods of data collection. While these approaches have generated valuable insights, they also reproduce epistemic and ethical limitations, particularly in cross-cultural contexts. Linguistic dominance, culturally mismatched diagnostic and care frameworks, and reliance on caregivers as proxy informants can marginalize culturally and linguistically diverse communities and risk pathologizing cultural difference as cognitive deficit. In response, this conceptual paper advances a participatory arts-based framework for cross-cultural dementia care research that centers multiple ways of knowing beyond language. Drawing on principles of co-creation, shared decision-making, reflexivity, power-sharing, and relational ethics, the framework positions people living with dementia as collaborators rather than subjects. It articulates five interrelated dimensions: (1) modes of expression (visual, embodied, sensory, and performative); (2) forms of participation (co-design, co-creation, and co-analysis); (3) cultural situatedness of meaning-making; (4) relational ethics, including ongoing assent, trust, and reciprocity; and (5) intersectionality across culture, gender, migration, class, and caregiving roles. The paper illustrates how participatory arts-based methods, such as photovoice, body mapping, collaborative art-making, and sensory storytelling, can enable culturally resonant engagement across stages of dementia while addressing power asymmetries inherent in conventional research designs. By foregrounding embodied, sensory, and culturally grounded forms of expression, this framework offers a critical reorientation of dementia care research toward more inclusive, ethical, and culturally responsive knowledge production in diverse care contexts. Full article

Introductory Java programming requires learners to reason about abstract computational concepts such as program state, control flow, and execution order, which often present substantial difficulties for novice programmers. These challenges may be further intensified for collegiate student athletes when programming instruction remains disconnected from the domain knowledge that shapes their prior experiences. This paper proposes a wrestling-inspired, state-based pedagogical framework that leverages the rule system of National Collegiate Athletic Association (NCAA) wrestling as an analogical knowledge domain for introducing foundational Java programming concepts. Within this framework, wrestling match states and scoring actions are systematically mapped to core programming constructs, which include variable assignment, conditional branching, loops, method invocation, and program termination. This paper is positioned as a conceptual and pedagogical framework study rather than an empirical intervention study. It focuses on the theoretical rationale, conceptual alignment, instructional mappings, and classroom implementation possibilities of a wrestling-inspired approach. This paper does not report participant data, learning assessments, or comparative outcome measures. Instead, it illustrates how sport-specific mental models can be transformed into structured instructional representations that may support learners’ reasoning about program execution. By integrating domain-aligned cognitive schemas with programming instruction, the proposed framework offers a structured knowledge scaffolding approach that is designed to support novice understanding of computational processes in introductory programming education. Full article

Elastic Patterns are presented as a novel approach to prototype-based pattern classification that integrates concepts from cognitive psychology, fuzzy logic, and physics. Traditional prototypes are revisited through their different formulations: psychological prototypes as central category elements, Fuzzy Prototypes addressing vagueness, and Deformable Prototypes incorporating elasticity to adapt to data variability. Elastic Patterns extend these ideas by representing each parameter as an independent elastic component, conceptualized as springs, which deform to fit new cases while minimizing deformation energy. Elastic Patterns operate at two levels: parameter-level deformation, measured through axial strain, and pattern-level deformation, expressed as cumulative deformation energy. This structure enables a transparent and adaptive recognition process, where classification is achieved by selecting the pattern requiring the least energy to deform. A case study on the MNIST dataset validates the proposal, achieving approximately 80% accuracy and reducing the need for extensive preprocessing. These results indicate that Elastic Patterns offer a promising alternative to conventional methods, combining interpretability, adaptability, and physical grounding in pattern recognition tasks. Full article

Virtual reality (VR) has emerged as a versatile technology for cognitive and professional training, enabling the simulation of complex environments that promote engagement, motivation, and adaptive learning. This study presents the design and development of a VR-based training system composed of three serious games aimed at strengthening executive functions (EFs), cognitive flexibility, inhibitory control, working memory, planning and logical reasoning, within the framework of continuous improvement methodologies in industrial contexts. The system was developed using the Game Development Software Engineering (GDSE) model combined with a Design-Based Research (DBR) approach, following iterative cycles of analysis, design, and heuristic validation by experts in engineering, design, and cognitive psychology. The results show that the final version of the system achieved high usability, cognitive coherence, and visual immersion, with game mechanics accurately reflecting the targeted EFs. Each game integrates progressive difficulty, multimodal feedback, and realistic industrial scenarios to ensure ecological validity and potential transfer to real workplace behaviors. The findings demonstrate the technical and conceptual feasibility of applying immersive environments for executive function training in adults and suggest that VR can support the development of cognitive and behavioral competencies essential for sustaining continuous improvement programs in organizational settings. Full article