Search Results (313)

Digital storytelling is widely used in education as a multimodal design practice that foregrounds creator agency and audience awareness. Generative AI (GenAI) expands the speed and range of story production but also raises questions about how educators retain pedagogical control over generated content. This exploratory qualitative study used cross-case workflow analysis to examine how 27 pre-service early childhood educators in Hong Kong designed GenAI-mediated mathematics storybooks. Data included video-recorded process presentations, records of interactions with ChatGPT (GPT-5) and Krea 2, and completed storybooks. Analysis traced participant decisions across planning, generation, curation, and integration, focusing on GenAI-related affordance uptake, recurring workflow patterns, and tensions among technical innovation, ethical accountability, and cultural impact. Findings show that participants commonly used GenAI to steer generation through pedagogical constraints; expand narrative and visual alternatives; and select, reject, or revise generated materials. Two recurring process patterns were identified: constraint-guided planning-to-generation, in which pedagogical requirements were established early and used to guide subsequent decisions, and exploration-to-selection, in which participants generated and compared alternatives before progressively stabilizing a preferred direction. Across both patterns, tensions were particularly evident during curation and integration, when participants balanced efficiency with sustained oversight, creative variation with pedagogical coherence, and generic outputs with local contextual fit. The findings show that GenAI-mediated storybook creation is not simply a process of generating text and images, but a pedagogical workflow in which pre-service teachers exercise agency through the critical selection, revision, and integration of AI-generated materials. Implications are discussed for teacher education, AI literacy, and the design of scalable support for teachers’ use of GenAI. Full article

Passenger car unit (PCU) values are an essential input for traffic capacity assessment (TCA) of intersections, as they allow different vehicle categories to be converted into a common unit. In the Slovak Republic, current technical guidelines use fixed equivalency factors for specific intersection types. However, international research shows that PCU values depend on local traffic conditions, vehicle composition, road geometry, and vehicle interactions. Incorrectly selected factors may therefore lead to inaccurate capacity calculations and misleading conclusions regarding intersection performance. This study analyses PCU values for different vehicle categories, with a focus on heavy vehicles (HV) at roundabouts and turbo roundabouts (TR). Traffic surveys were conducted at selected intersections near industrial areas, where a higher proportion of freight traffic was expected. Manual and semi-automatic turning-movement counts were combined with high-resolution video recordings and automatic traffic counters (ATC) to obtain data on traffic volumes, vehicle composition, travel times, speeds, vehicle lengths, and time headways. The results indicate that the behavior of trucks and HV combinations may differ from the assumptions reflected in static equivalency factors. In several cases, the measured travel times and time headways did not reach the values implied by the prescribed PCU coefficients. Based on these findings, a methodology for dynamically determining PCU values was proposed. The methodology is based on the time headway principle and uses commonly available measurement devices. The proposed approach enables PCU values to be determined for either a simplified two-category vehicle classification or a more detailed classification. It may serve as an alternative to static tabulated values, particularly under non-standard traffic composition, a high proportion of HV, or specific geometric conditions of intersections. Full article

This article presents a study that applies Laban’s Effort theory to detect a musician’s expressive intentions during performance. Laban Effort theory was chosen for its capacity to support the observation, description, and interpretation of expressive movement. The aim was to develop interactive musical systems that learn from the embodied expressivity musicians cultivate through practice. The study adopts a multidisciplinary approach, combining Laban Motion Analysis with interactive machine learning. Gesture data, audio, and video were recorded during a performance of Brahms’s Clarinet Sonata Op. 120 No. 2. The video was then analysed by an expert annotator observing Laban Efforts. The annotated video was then reviewed in collaboration with the performer to incorporate Effort Phrasing that reflects changes in intensity within Efforts. The annotations were then used as training data, together with motion data recorded during the performance, to train a regression model. The model was evaluated against expert annotations and through qualitative video analysis. Unlike the very linear notation of a Laban analyst, the model reflects the dynamism of human motion by capturing the almost humanly unobservable nuances in Effort variations. This points to the possibility of using machine learning models to reflect a performer’s expressive intentions in real-time. Full article

The postnatal period involves significant emotional and relational shifts that can challenge early mother–infant interactions, particularly under conditions of psychosocial vulnerability (e.g., maternal anxiety/depression) or infant-related risk (e.g., preterm birth). Maternal mentalization, operationalized as Parental Reflective Functioning (PRF), is a key protective factor for sensitive caregiving and dyadic regulation. Objectives: This protocol describes a multicenter, open-label, single-arm feasibility study evaluating a brief, fully online, mentalization-based video-feedback intervention (VFI-RF). The study is designed to assess the feasibility and acceptability of the intervention, rather than its efficacy. We aim to recruit 48 mothers, 24 in each of two risk groups, through socio-health services and neonatal intensive care units. Risk Group 1 will include mothers with clinically significant depressive and/or anxiety symptoms, defined as EPDS > 9 and/or GAD-7 ≥ 10, whereas Risk Group 2 will include mothers of preterm infants, defined as infants born before 37 weeks of gestation. Methods: The intervention consists of 8 + 2 synchronous online sessions over approximately 5 months. Mothers record brief everyday caregiving interactions (~5 min) to review with a trained clinician, focusing on the infant’s internal states and reflective meaning-making. Assessments occur at baseline (T0, infant age ~3 months), post-intervention (T1, ~8 months), and follow-up (T2, ~12 months). Primary feasibility outcomes include recruitment/referral metrics, uptake, retention, assessment completion, missing data, and participant-reported acceptability. Secondary exploratory clinical outcomes include maternal PRF, symptoms, parenting stress, social support, and mother–infant attachment, evaluated via validated self-report questionnaires. Results: The study is designed to evaluate referral and recruitment patterns, intervention uptake, and participant retention, as well as the acceptability and suitability of study procedures and outcome measures for a future controlled trial. Preliminary trajectories of change in maternal reflective functioning and early relational indicators will be examined descriptively and exploratorily. Conclusions: Findings will inform the feasibility and refinement of a brief online mentalization-based video-feedback intervention to support at-risk mother–infant dyads during the first postnatal year. Trial registration: Registered on Open Science Framework, osf.io/6g9ja, date of registration 4th March 2026. Full article

Shelter dogs may experience long-term environmental and social stressors that can affect their behaviour and welfare. Some individuals show reduced activity, low responsiveness to environmental stimuli, and limited interaction with their surroundings. This pilot study investigated behavioural patterns and allopregnanolone concentrations in shelter dogs exhibiting these behavioural characteristics. Ten shelter dogs were enrolled and divided into two groups: five dogs showing depression-like patterns and five matched control dogs. Each dog wore a three-axis accelerometer for 30 days to quantify activity levels. Behavioural observations were conducted using video recordings, and hair samples were collected at baseline and after 30 days to assess allopregnanolone concentrations as a potential stress marker. Dogs in the case group showed significantly longer resting time than controls (p ≤ 0.05), indicating reduced activity levels. Trends toward lower levels of exploratory and social behaviours were also observed, although the differences were not statistically significant. Allopregnanolone concentrations ranged from 0.6 to 4.6 pg/mg and showed considerable inter-individual variability, with no significant differences detected between groups. These findings provide preliminary evidence of behavioural and physiological alterations in shelter dogs displaying depression-like patterns. However, further studies with larger populations are needed to validate these findings and improve welfare assessment in shelter environments. Full article

Drone-based shark surveillance has been implemented as a non-lethal mitigation method to minimise the risk of human–shark interactions along beaches of New South Wales (NSW), Australia. However, real-time misidentification remains problematic, often triggering unnecessary countermeasures due to marine animals that pose little to no risk to humans. We investigated shark misidentification in drone surveys by comparing real-time identification with post-flight verification across 900 flights. Post-flight analyses revealed false-positive detection rates of 53%, 79%, and 100% for bull (Carcharhinus leucas), white (Carcharodon carcharias), and tiger (Galeocerdo cuvier) sharks, respectively, which collectively are the ‘target’ sharks of mitigation measures in NSW. Of the 269 flights in which sharks were identified in real time as target sharks, 62% were confirmed post-flight as other sharks (i.e., whaler species, grey nurse, leopard, or wobbegong), sharks that could not be identified (unknown sharks), or non-shark species (i.e., guitarfish). Conversely, 25% of flights with target sharks identified post-flight were recorded in real time as ‘other’ or ‘unknown’ sharks. Overall, real-time classification overestimated the presence of target sharks, with an apparent prevalence approximately twice the true prevalence. Countermeasure activations based on real-time classification of target sharks were accurate in only 36% of instances. Non-shark species (i.e., guitarfish or gamefish) also triggered 39 countermeasures, including 28 water evacuations. Integrating artificial intelligence or other advances (e.g., higher-resolution video on larger screens) may enhance the effectiveness of drone-based surveillance by assisting pilots with real-time shark detection and identification. Full article

Body size is a key determinant of agonistic interactions in swimming crabs. This study quantified agonistic interactions during pairwise contests among different size classes. Four size classes of male juveniles, Portunus trituberculatus, were examined (extra-large: 70.16 ± 1.12 g; large: 45.07 ± 1.15 g; medium: 25.30 ± 1.19 g; small: 15.08 ± 1.73 g; n = 12 per size class). The frequency and duration of agonistic behaviors and fighting intensity were recorded by a video recording system and analyzed. Larger crabs initiated more frequent and intense aggressive interactions, whereas smaller crabs exhibited mainly avoidance and submissive responses, particularly against larger opponents. The most intense and prolonged contests occurred between opponents with relatively small size differences. Conversely, highly size-mismatched pairs exhibited shorter, less intense interactions. These agonistic interactions were strongly size-dependent, consistent with Resource Holding Potential theory and size-contest dynamics. These behavioral patterns provide insights into social dynamics and inform aquaculture management practices. Full article

There is a pressing need for education regarding sustainability and previous research has focused more on students and less on teachers. This article explores teachers’ understandings of using the game Climate Call, which covers carbon dioxide content, in the General Science classroom to teach sustainability. This case study involved four teachers and six upper secondary classes in Sweden, from whom data was collected through fieldnotes, video recordings and interviews. The data has been analysed through the framework of the didactical tetrahedron, modelling the interactions between teacher, student, sustainability and the game in teaching and learning. The results indicate that teachers recognise new opportunities for teaching sustainability and for using the game’s content to highlight other aspects of the subject. The game also creates new interaction opportunities between students and teachers, though not all interactions were without obstacles. Full article

The inclusion of children’s perspectives is increasingly emphasised in educational research; however, autistic children remain underrepresented as active participants, particularly in early educational contexts. This study synthesises methodological insights from two mixed-methods studies conducted in Swedish preschool and primary school settings to examine the conditions under which autistic children participate as contributors to research. A retrospective and reflexive methodological synthesis was employed, drawing on methodological documentation, video-recorded data, and researcher reflections from the original studies. The analysis examined how participation was designed, negotiated, and interpreted across contexts. The findings indicate that participation is not a binary feature of research design, but a graded, situated, and relational process shaped by accessibility, mediation, and contextual conditions. Accessibility functioned as an epistemic condition influencing what could be expressed and recognised as knowledge, while participation was continuously negotiated through interaction among children, adults, and research settings. Adult mediation both enabled and shaped participation, revealing inherent epistemic and ethical tensions. The study concludes that participation is more accurately understood as a methodological and relational accomplishment rather than an individual capacity, underscoring the need for flexible, reflexive research approaches that support diverse forms of expression while maintaining methodological quality and ethical integrity. Full article

Presently, video communities such as YouTube, bilibili and TikTok have emerged as core fields for information dissemination and public opinion generation. Their embedded user dynamic interaction data support research on public cognitive behavior and content dissemination laws. This study used web crawling technology to construct a complete dataset including 367 video metadata and 2.39 million comment records from Luo Xiang Speaks on Criminal Law—a prominent legal popularization account on the bilibili platform—and systematically explored the temporal evolution patterns of comment interactions in video communities. By establishing a four-dimensional feature system alongside the k-means++ clustering algorithm, this study successfully identified three distinct comment growth patterns (p < 0.001): the burst–decay, the multi-wave oscillation, and the delayed peak. The results of non-parametric tests showed that these three patterns have significant differences in core features (e.g., peak delay time, skewness) and are systematically related to user grade structure, content interaction depth, and release timing. In addition, the user interaction networks of different videos demonstrate significant structural heterogeneity and disassortative mixing, characterized by a highly active minority dominating the discourse, while peripheral nodes gravitate toward high-profile hubs. These findings offer researchers deeper insights into the micro-mechanisms of information dissemination. Full article

Background: Understanding the benefits of psychedelic-assisted therapy (PAT) will require scientific attention to the causal interaction between the therapeutic context and process. Measuring what actually happens during PAT in large-scale studies will be an essential component of this work. Objective: We aim to develop and preliminarily evaluate the feasibility and reliability of a direct observation coding system for narrations of awe experiences during PAT, one hypothesized therapeutic mechanism. Methods: We analyzed 32 PAT clinical trial encounter recordings involving eight participants from a Phase 2 clinical trial study of psilocybin-assisted therapy in advanced cancer. Using a conceptually grounded structured codebook, two human coders independently identified start and stop times for moments exhibiting definitional characteristics of awe narration, including expressions of vastness, need for accommodation and ineffability. We used coder agreement and degree of confidence to refine the coding system. Results: During 16,760 total minutes of video, coders collectively recorded 246 moments of awe narration. Of those moments, 42% (104/246) were identified by one coder and 58% (142/246) by two coders. Coders felt substantially more confident in their judgments about a moment of awe when vastness was present compared to when vastness was absent (OR: 4.3; 95% CI: 2.4, 7.8). Iterative refinement of the coding system led to accommodation being operationalized as two distinct components: an initial cognitive disruption followed by variable engagement in the process of accommodation. Conclusions: Awe narration is directly observable using explicit definitional criteria. This work provides the empirical foundation for scalable coding systems of awe narration during PAT. Full article

Public emergencies are increasingly shared and discussed on short-video platforms, where videos, user interactions, and timing influence how social risks become visible and spread. This study examines a major short-video platform in China and proposes a Multimodal Information Risk Flow (MIRF) framework to understand how risk signals appear, are categorized, and evolve over time during emergencies. We analysed 250,100 anonymized video–comment records collected between 2022 and 2024, combining text, images, audio, user behavior, and author information to study patterns of risk representation and amplification. Our results show that social risk spreads unevenly over time and is strongly influenced by the type of content, with toxic comments leading to faster and larger cascades. General engagement metrics play a smaller role, and shorter times to peak activity are consistently linked to larger risk cascades. These findings highlight that social risk on short-video platforms is multimodal and temporally concentrated, and caution is needed when generalizing results beyond similar platforms and regulatory contexts. Full article

Social media platforms have become central sites of identity construction, where visibility and legitimacy are shaped through algorithmic systems, aesthetic conventions, and platform economies. This paper approaches online personas through the lens of illusionary selves, understood here as online personas experienced as authentic while being shaped by sociotechnical processes, examining how they are produced through sociotechnical processes entangling design practices, generative artificial intelligence(AI), and cultural expectations. We present an AI-mediated critical design inquiry into how generative systems translate and normalize visual patterns of online self-imaging. Using a pix2pix-based model trained on 630 internet celebrity selfies, facial images are abstracted into dot-based representations and aggregated across selfie angles, foregrounding repetition and normalization. An interactive design installation links bodily orientation and numerical parameters to generative output in real time, introducing perceptual friction in self-imaging. A total of 30 participants engaged with the system in situated contexts, and their experiences were documented through observation, video recording, and a 5-point Likert questionnaire across three dimensions: perceptual friction, awareness of algorithmic mediation, and reflective responses to self-presentation. Results indicate high levels of perceptual friction (mean [M] = 4.21), strong awareness of algorithmic mediation (M = 4.29), and consistent reflective unease (M = 4.07). Through situated use, the system renders algorithmic mediation tangible and positions AI as an implicated actor in identity construction. This work contributes a conceptual framing of AI-mediated critical design, showing how generative and interactive systems operate as epistemic devices interrogating online persona construction. Full article

Gastrotrichs (Phylum Gastrotricha) are widespread and species-rich components of benthic and periphytic communities, where they are thought to contribute substantially to food-web functioning by linking the microbial loop to higher trophic levels through their feeding on detritus, bacteria, microalgae, and fungi, and serve as prey for larger animals. Despite the well-recognized role as primary consumers, their position as potential prey remains largely unresolved, with documented predators so far restricted to carnivorous protists. Here, we report the first documented case of metazoan predation on a freshwater gastrotrich, in which a cyclopoid copepod actively captures and partially consumes a chaetonotid species. The interaction was first detected under minimally disturbed conditions and subsequently replicated in controlled experimental settings. Predation was documented through in vivo video recordings and supported by species-level identification of both predator and prey. These findings expand the currently recognized trophic interactions involving freshwater gastrotrichs and provide new insight into their ecological role within aquatic food webs. Full article

This article reconceptualizes the notion of diverse texts in literacy education by extending it beyond traditional print-based materials to include online multimodal texts that integrate images, videos, and written language to engage students with social issues. Drawing on a case study of four sixth-grade students in South Korea, this study examines how elementary readers make meaning from multimodal online texts about child labor that contain visuals, videos, and written words. Multiple data sources including verbal protocols, screen-recorded reader–computer interactions, retrospective interviews, and written pre- and post-knowledge reports were analyzed to capture students’ strategic and civic engagement processes. Findings indicate that students employed a range of online multimodal reading strategies to comprehend texts while also demonstrating shifts in civic orientations, moving from personally responsible perspectives toward more participatory and justice-oriented stances. Although their reading paths differed, students grappled with issues of justice and inequality, suggesting that online multimodal reading can serve as a space for developing civic literacy practices. These findings position multimodal texts, which consist of more than one mode of representation, as a form of diverse texts that not only support comprehension but also foster civic learning, engagement, and children’s emerging civic agency in navigating complex social issues in digital environments. Full article