Search Results (502)

Integration of computer-based testing (CBT) in higher education has gained momentum globally, particularly in response to increasing demands for efficiency, scalability, and technological innovation in assessments. However, limited research explores how lecturers experience and make sense of CBT adoption, especially within resource-constrained educational systems. Grounded in the technology acceptance model (TAM), we employed a phenomenological approach to investigate lecturers’ perceptions of CBT. Eight lecturers from the largest university in Sub-Saharan Africa were purposively selected and individually interviewed. Thematic analysis, supported by human-AI collaboration, revealed diverse perspectives. The results show that lecturers perceived CBT as useful for improving efficiency, feedback speed, and assessment management, though concerns remained about infrastructure, authenticity, and equity. Ease of use strongly shaped these perceptions, with digitally skilled lecturers reporting a more positive experience. Attitudes toward CBT varied by discipline and pedagogical beliefs while influencing lecturers’ intention to adopt CBT. Thus, lecturers showed cautious but positive behavioural intention, particularly where CBT aligned with assessment needs and institutional support was adequate. The study contributes theoretically by extending the applicability of TAM to qualitative inquiry and practically by informing institutional strategies for improvement. Full article

A key requirement of associative learning studies is the ability to motivate the subject to acquire memory of the conditioned stimulus–unconditioned stimulus (CS–US) association. Although zebrafish have been found capable of acquiring CS–US associative memory, in many studies, the fish failed to learn. One reason for the failure, I argue in this perspective article, is that we do not yet know how to motivate zebrafish. I illustrate this problem using examples, and offer some solutions, based upon results obtained in my own laboratory for appetitive associative learning tasks for zebrafish. I highlight the value of considering the ethology and ecology of the zebrafish. I discuss why food may have been an ineffective US for zebrafish. I provide examples for how to improve the rewarding properties of food based upon the foraging behaviour of zebrafish in nature. I discuss the efforts to identify alternative USs, including the sight of conspecifics or the presence of other ecologically relevant stimuli. I theorize about conflicting motivators in zebrafish learning studies, including the effect of human handling versus that of experimenter-controlled USs. I conclude that systematic analyses of different USs are needed, along with detailed studies on how they may be optimized for the analysis of learning and memory in zebrafish. Full article

This article examines the role of Human Resource Management (HRM) in shaping employees’ green behaviour and its contribution to organisational environmental performance through an original bibliometric analysis of the international literature. The analysis is based on 105 scientific publications retrieved from the Scopus database for the period 2009–2025. Bibliometric techniques were applied using Bibliometrix and VOSviewer to map publication trends, co-authorship networks, thematic clusters, and the maturity of research themes. The results indicate a strong increase in research output after 2019, combined with high levels of international collaboration and a geographical concentration of studies in Asian economies. Keyword co-occurrence analysis identifies Green Human Resource Management (GHRM) and organisational environmental performance as the core conceptual pillars of the field, while employees’ green behaviour emerges as a key mediating mechanism linking HR practices to environmental outcomes. Thematic mapping based on centrality and density suggests that the field has entered a phase of theoretical consolidation, with emerging research directions focusing on behavioural, strategic, and social dimensions of sustainability. Overall, the study provides a structured overview of the GHRM research landscape and highlights important gaps related to causal mechanisms, economic performance, and cross-sectoral and cross-country evidence. The findings also indicate that sectoral applications beyond tourism and hospitality, cross-country comparative studies, and the integration of economic performance indicators with GHRM remain underexplored, highlighting specific directions for future research. The study adopts a bibliometric research design and does not aim to provide a systematic review of empirical findings. Full article

Classical developmental psychology treats childhood animism—attributing life or mind to inanimate things—as a transient phase that recedes with schooling and the onset of concrete operations. The contemporary spread of lifelike AI has altered that background assumption, with particular implications for children and adolescents whose agency-detection systems and reality-testing capacities are still calibrating. Across interfaces, voices, avatars, and social robots, modern systems routinely exhibit contingent, context-sensitive behaviour that recruits developing social-cognitive systems during sensitive periods of identity formation and relational learning. Drawing on developmental psychology, cognitive science, human–AI interaction research, clinical psychiatry, and technology ethics, we: (1) present a mechanistic “hourglass model” showing how interactive AI engages animistic cognition with heightened effects during childhood and adolescence, including a developmental timing analysis of how differential maturation of agency detection, Theory of Mind (ToM), and prefrontal reality-testing creates windows of particular vulnerability; (2) disaggregate five distinct phenomena along an anthropomorphism-to-delusion trajectory with operational boundary criteria; (3) specify a graded psychopathology continuum with a fourth, orthogonal zone addressing adversarial design—itself disaggregated into three tiers with distinct regulatory implications; (4) identify conditions under which anthropomorphic engagement may be beneficial, including for youth; and (5) advance cognitive safety–inspired design with developmentally appropriate protections for minors. We introduce the IDAQ-CF-Tech, a twelve-item screener for AI-specific mind attribution offered as a provisional instrument for validation across age groups, and close with a phased research agenda emphasising longitudinal developmental outcomes, impacts on adolescent identity formation, and cross-cultural variation in techno-animism. Full article

In massively multiplayer online games (MMOGs), complex social environments exist in which cooperation is central not only to playing the game but also to experiencing it as an individual player. The growth of multiplayer games that emphasise cooperative activities in computer-based environments has sparked academic interest in collaboration and its role in the field, engaging scholars from domains such as human–computer interaction and digital entertainment. This paper presents a systematic literature review (SLR) and bibliometric analysis of 70 peer-reviewed journal papers published between 2015 and 2024. This data is derived from the Web of Science and Scopus databases. This literature review contributes to the understanding of collaborative factors in MMOGs, which include task interdependence, communication, trust, leadership, and player behaviour. The review is in the field using bibliometrics. To present the findings, we construct an input–process–output (IPO) model that links game features (inputs) and interaction dynamics (processes) to team performance and player experience (outputs) in MMOGs. This review maps the field’s dominant factors (task interdependence, communication, trust, leadership, and player behaviour), pinpoints methodological priorities, and sets a concrete agenda for future research on team collaboration in MMOGs. Full article

As the first domesticated species, dogs have been shaped by human needs, values, and social structures, resulting in culturally specific expectations of their behaviour. While much of the existing research on companion animal preferences (referred to as ideal traits) has focused on Western contexts, rapidly increasing companion dog populations in Eastern countries mean that preferences in diverse cultures are important to investigate. Considering owner satisfaction is influenced by the match between dogs’ traits and owners’ culturally specific ideals, understanding ideal dog traits may help minimise welfare concerns, including relinquishment and maltreatment of companion dogs. A sample of 312 Vietnamese adults (M age = 27.31, SD = 6.65) were recruited via convenience sampling through Facebook and Instagram. Participants completed translated versions of the 44-item Ideal Dog Scale. Exploratory factor analysis identified four dimensions of ideal dog traits in Vietnam: ‘Calmness’, ‘Energy/Capability’, ‘Affection/Health’, and ‘Cleanliness’. This differs from Australia, where the ideal dog is ‘calm/compliant’, ‘sociable/healthy’, ‘energetic/faithful/protective’, ‘socially acceptable’, and ‘non-aggressive’, and from Italy, where the ideal dog is ‘calm’, ‘sociable and healthy’, ‘well trained and adaptable’, ‘energetic’, and ‘easy to manage‘. For participants with a current dog, most owned a non-desexed, mixed breed male dog. This study deepens psychological insight into how socioecological contexts may shape perceptions of ideal companion animals. It also allows Vietnamese individuals to understand traits that would lead to the best dog–owner ‘match’, improving dog owner wellbeing and dog welfare. Full article

Quantitative gait analysis is essential for assessing motor function, as altered walking patterns are linked to functional decline and increased fall risk. Although recent advances in markerless motion analysis and human pose estimation enable gait feature extraction from low-cost video systems compared to expensive motion analysis laboratories, clinical translation remains limited by fragmented descriptors or approaches that directly regress clinical scores, often reducing interpretability and generalizability. We propose the Gait Alteration Index (GAI), an interpretable index that quantifies gait abnormality as a functional deviation from typical walking patterns, independently of specific pathologies. The GAI is computed from a small set of gait parameters and integrates three complementary domains: spatio-temporal characteristics, surrogates of dynamic stability, and arm swing behaviour, providing both a global index and domain-specific sub-indices. Preliminary evaluation on a heterogeneous cohort using clinician-derived assessments showed that the GAI captures clinically meaningful gait alterations (Spearman’s $\rho =0.65$), with the strongest agreement for spatio-temporal features ($\rho =0.77$). These results suggest that the GAI is a promising low-cost, and interpretable tool for objective gait assessment, screening, and longitudinal monitoring. Full article

This research focuses on the analysis of the viscoelastic (VE) behaviour of panel paintings (PPs), which are artworks made of various materials. Each PP is different from others because of their unique assembly, the changes due to the passage of time and human interventions. Thus, a thorough understanding of the hygro-mechanical behaviour of PPs is needed for their conservation. This study analyses the VE behaviour of an original PP from the 16th century, taking it both as a global structure and as a bilayer system. The PP was tested under constant climatic conditions and subjected to a constant load for at least 3 days, followed by a recovery period. The experimental results show that the PP exhibited VE behaviour and that the deformation was recoverable. The PP was loaded at two stress levels, and the results were consistent with the linear VE behaviour expected for moderately loaded wood. The bilayer approach allowed us to separate the contributions of wood and the paint layer, assuming that the latter behaved elastically. Full article

The Sacred Ibis Threskiornis aethiopicus is an invasive alien species (IAS) that has become established in many European countries. Because of its invasive status and its frequent interactions with native species, understanding the behavioural tolerance of this species to human disturbance is relevant for both conservation and management. Here, we analysed Flight Initiation Distances (FID) of T. aethiopicus recorded between 2012 and 2025 across the northern Adriatic coast. The dataset (n = 72) included approaches on foot and by boat in six habitat types (artificial saltmarshes, farmlands, brackish ponds, freshwater wetlands, saltmarshes, tidal flats). Mean FID was 41 m (SD = ± 24); it was affected mainly by group size, whereas habitat, season and approach mode had no clear effect. A cross-species analysis of mean FID versus body mass indicated that, for its size, T. aethiopicus has a much shorter FID than expected from the allometric relationship observed in 20 other waterbirds species for which FID was also collected (n = 1505) at the same sites. The results suggest partial habituation to anthropized environments and a limited flight response compared to native species. These findings may support management actions aimed at monitoring and controlling the expansion of the species while mitigating disturbance to native assemblages. Full article

Suburban residential streets have long been criticised for their multiple short-comings, including traffic-related injury, increased stormwater runoff, and lack of aesthetic values. Research suggests that Integrated Green-Grey Infrastructure (IGGI) is likely to play a role in mitigating these problems. IGGI refers to infrastructure that consists of both natural materials (such as plants, soil) and human-made structures (such as concrete, pipes). However, IGGI’s definition remains vague, and little is known about its implementation in suburban street retrofitting, and how effective it is. Using a systematic literature review method, this paper analyses peer-reviewed journal articles published over a period of ten years between 2014 and 2023. The objective was to understand IGGI’s definition, integration, and effectiveness in implemented residential street retrofitting projects. Through a rigorous screening process, 15 papers were selected for qualitative analysis. Clusters developed in analysing the results consist of IGGI’s concepts, components, integration and effectiveness. The most notable subject area is system-scale integration, shared by 14 papers. Findings regarding the effectiveness of IGGI suggest strong empirical evidence related to stormwater management and road user behavioural change; however, there were mixed perceptions toward the aesthetic values of rain gardens. Full article

Level 2 driving automation requires continuous driver supervision, yet common attention metrics often capture gaze allocation rather than the structure of supervisory scanning. This study proposes a quantitative approach for describing supervisory gaze organisation using first-order Markov chain analysis of gaze transitions. Forty-three licensed drivers ($N=43$) completed a simulator drive with Level 2 automation for either 5 or 15 min (between-subjects), representing typical Japanese expressway intervals between service areas. Supervisory behaviour was analysed at the scenario level, without introducing secondary tasks, allowing attentional drift to emerge naturally under automation. Eye-tracking data were manually annotated frame-by-frame at 60 Hz and modelled as transition probability matrices across key Areas of Interest (AOIs): road centre, mirrors, periphery, and the human–machine interface. Compared with the 5 min condition, the 15 min condition showed fewer mirror-to-road-centre recovery transitions and slower System-Recognised Reaction Time (SRRT) at the takeover request. These patterns suggest a gradual weakening of supervisory gaze organisation rather than a simple loss of attention. The proposed framework offers a reproducible way to calibrate driver monitoring and evaluate human–machine interfaces by linking gaze transition probabilities to takeover readiness. By quantifying how supervisory behaviour reorganises under extended automation in realistic driving scenarios, this study provides a practical basis for the development of safety-relevant driver monitoring indicators in Level 2 driver assistance systems. Full article

Slope stability is a critical and extensively researched topic that is important in structural design, especially when slopes are located near residential or civil engineering structures, as human lives are at risk. This paper presents a detailed analysis and evaluation of slope stability, synthesizing current understanding of slope behaviour, soil shear strength parameters, and the methodologies applied in stability assessment. In the conducted parametric study, the stability of slopes composed of fine-grained soils was investigated using both the limit equilibrium method (LEM) and the finite element method (FEM). The principal objective of the research was to assess the influence of soil shear strength parameters on the resulting factor of safety (FoS), while also accounting for variations in slope height. The results of the study show that an increase in soil shear strength parameters leads to a linear increase in FoS, with this relationship being more pronounced for changes in soil cohesion than for changes in the angle of internal friction. The effect of shear strength variations on stability is more pronounced in slopes of smaller height. Furthermore, the comparative analysis indicates that LEM provides more conservative estimates of slope stability in comparison with FEM. Full article

This study assesses the innovation performance and convergence dynamics across 237 European regions (NUTS 2 level) from 2016 to 2023, explicitly accounting for the structural and behavioural changes triggered by the COVID-19 pandemic. The article provides a novel regional-level assessment of how an unprecedented external shock reshaped innovation trajectories before and after the pandemic. To this end, the analysis combines Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), sigma-convergence measures, and a Difference-in-Differences (DiD) framework within an integrated multi-method empirical approach to evaluate shifts in regional innovation patterns over time. The results reveal a highly uneven distribution of innovation activities, with increasing polarization in the post-pandemic period. Northern and Western European regions strengthened their competitive advantage through robust digital infrastructure, strong human capital, and substantial R&D investments. In contrast, many Southern and Eastern European regions faced heightened structural barriers, leading to a widening innovation gap. Nevertheless, several regions exhibited notable resilience and achieved significant innovation catch-up, providing new empirical evidence on heterogeneous regional adaptive dynamics supported by targeted regional policies and improved local capabilities. The sigma-convergence analysis indicates a general increase in overall disparities, as reflected by rising dispersion in the Regional Innovation Index (RII) during 2020–2023. However, according to the DiD estimation, regions most severely affected by COVID-19 experienced a statistically significant relative increase (approximately 2.17%) in innovation performance, highlighting the pandemic’s role as a catalyst for accelerated digital transformation and innovation adjustment at the regional level. Full article

The shift toward Industry 5.0 places human-centred and digitally integrated metrology at the core of modern manufacturing, particularly in the automotive sector, where portable Laser Line Triangulation (LLT) systems must combine accuracy with operator usability. This study addresses the challenge of operator-induced variability by evaluating how algorithmic strategies and mechanical support features jointly influence the performance of a portable LLT device derived from the G3F sensor. A comprehensive Measurement System Analysis was performed to compare three feature extraction algorithms—GC, FIR, and Steger—and to assess the effect of a masking device designed to improve mechanical alignment during manual measurements. The results highlight distinct algorithm-dependent behaviours in terms of repeatability, reproducibility, and computational efficiency. More sophisticated algorithms demonstrate improved sensitivity and feature localisation under controlled conditions, whereas simpler gradient-based strategies provide more stable performance and shorter processing times when measurement conditions deviate from the ideal. These differences indicate a trade-off between algorithmic complexity and operational robustness that is particularly relevant for portable, operator-assisted metrology. The presence of mechanical alignment aids was found to contribute to improved measurement consistency across all algorithms. Overall, the findings highlight the need for an integrated co-design of algorithms, calibration procedures, and ergonomic aids to enhance repeatability and support operator-friendly LLT systems aligned with Industry 5.0 principles. Full article

Dogs increasingly function as relational beings, shaping their guardians’ emotional well-being and daily routines. Consequently, dog owner education has expanded beyond behaviour-focused training toward integrative approaches that address the emotional, relational, and cognitive dimensions of the human–dog relationship. Despite this shift, international comparative research on the organisation and institutionalisation of dog owner education remains limited. The study applies a qualitative exploratory comparative case study to examine systems in the United States, the United Kingdom, Germany, Japan, and Australia, identifying national patterns and shared components to inform context-appropriate frameworks, particularly in South Korea. The study examines legal and policy documents, institutional guidelines, and standardised education programmes that function as national or de facto standards using document and content analysis. It integrates within- and cross-case comparisons and interprets findings through a framework drawing on human–animal interaction, attachment, canine behaviour, and cognitive–behavioural coaching theories. The analysis reveals five shared components of behaviour change: guardian responsibility and animal welfare, science-based positive reinforcement, early socialisation and prevention, a balance between standardisation and individualisation, and guardians’ emotional and relational engagement. These findings suggest that dog owner education functions as an integrated system that supports responsible guardianship and stable human–dog relationships across sociocultural contexts. Full article