LGBTQI+ Allyship in Postgraduate Surgical Education: A Scoping Review.

Association between post-traumatic stress disorder and non-suicidal self-injury in adolescents: Exploring the role of internet addiction and sleep disturbances.

Recent advancements in digital technologies and the integration of artificial intelligence (AI) with software systems have introduced new challenges in cybersecurity. Traditional frameworks such as MITRE ATT&CK have proven expressive enough for the analysis of software threats, yet they are limited in accommodating the vulnerabilities of ML systems. In response, MITRE ATLAS was developed to extend the threat analysis specifically to AI and machine learning (ML) environments, providing a structured taxonomy for adversarial tactics and techniques attempting to compromise them. In this paper, we extend the conversation by reviewing papers related to adversarial attacks and examining their categorization, their theoretical foundations, and their advancements compared to prior work. Specifically, we analyze a total of 63 papers across the entire AI attack spectrum and further delve into their objectives, threat models, scientific advancements, and evaluation. Our contributions include the first, to-date analysis of attack vectors following the MITRE ATLAS paradigm, a synthesis of recent advancements, and a discussion on the limitations in the current body of knowledge. We hope that our analysis clarifies the present challenges and serves as a foundation for future research towards securing AI systems. • Structured analysis using MITRE ATLAS to classify AI threats across six attack families, mapping tactics and techniques. • Systematic analysis of 63 methods across domains, evaluating theory, threat models, datasets, and results. • Actionable defense strategies mapping 24 mitigation mechanisms to MITRE ATLAS techniques as a practical guide for practitioners. • Synthesis of findings highlighting research gaps, future directions, and proposed enhancements to the MITRE ATLAS framework.

Artificial intelligence-enhanced virtual reality for pathology education.

Empowering the Youth Voice: Medical Students' Reflections on Adolescent Psychosocial History Taking.

The career choices of nursing students after the COVID-19 pandemic: A scoping review.

Contemporary strategies for active learning in oral and maxillofacial surgery education.

Sustainable acoustic treatment using agricultural waste valorization through eco-friendly pomegranate peel-clay composites.

This study aimed to analyze the implementation of interactive media in social studies learning to support the development of the Pancasila Student Profile in elementary schools. Previous studies have highlighted the lack of student engagement in traditional social studies learning, yet few have explored the integration of interactive media specifically targeted at the Pancasila Student Profile dimensions. To fill this gap, this research utilized a qualitative descriptive approach conducted at an elementary school involving 25 fourth-grade students. Data were collected systematically through classroom observation, semi-structured interviews with teachers and students, and learning documentation. The results showed that the use of interactive media—such as animated learning videos, digital quizzes, and interactive educational applications—significantly improved students' engagement and conceptual understanding. Active student participation increased from 36% to 72%, and learning mastery improved from 40% to 68%. Furthermore, the implementation strongly supported key dimensions of the Pancasila Student Profile, specifically critical thinking, creativity, collaboration, and global diversity awareness. The study concludes that integrating interactive media in social studies learning effectively enhances learning quality, transforms passive learning environments into active ones, and successfully supports holistic curriculum goals in elementary education.

Students' motivation towards traditional versus online academic learning.

Children are ecological learners; they adapt their information search strategies to fit the structure of their immediate learning environment. In two studies, we explore whether this search behavior is impacted by the potential for later information gain. In Experiment 1, 60 5-9-year-olds were presented with a population of different colored balls with a hidden property and a sample that was either representative or unrepresentative of that population. Children were asked to select a tool that would allow them to learn about the hidden property: one tool yielded more information from the local set of sampled items, while the other yielded more information about the global population. We find that, regardless of age, children consistently choose the most effective tool to support global information gain. In Experiment 2, we assessed whether this choice was truly motivated by the tool's potential to support learning that goes beyond the immediate sample (i.e., global yield), or due to children's reliance on another strategy (i.e., tool versatility or set ratios). To test this, we included 151 7-14-year-olds and 34 adults. In all conditions, participants were presented with a choice between learning tools that pitted global yield against an alternate strategy. We found that both children and adults consider global yield when selecting a tool, a tendency that increases with age. Children also consider the versatility of the tool when planning for downstream learning opportunities. We discuss the implications of these findings for understanding how learners develop strategies for prioritizing the acquisition of generalizable knowledge. SUMMARY: Children choose information-gathering tools by balancing immediate usefulness with the potential for broadly informative learning. By age five, children use sample representativeness to guide prospective choices about how to learn. Younger children often rely on tool versatility, whereas older learners increasingly prioritize tools that support broader inference. Development reflects shifts in epistemic strategy use rather than convergence on a single optimal approach to information search.

Biology educators increasingly teach in classrooms shaped by digital devices, projected media, bright artificial lighting, dense visual displays, and frequent movement between lecture, laboratory, and online learning tasks. These conditions are often treated as background features rather than as factors that may affect attention, engagement, and cognitive access. Cognitive load theory has helped educators analyze how instructional design can support or overload working memory; however, science educators have fewer practical frameworks for examining the combined sensory, physical, and technological demands of the learning environment. This Perspective uses the term environmental load to describe task-irrelevant cognitive demand produced by the physical, sensory, spatial, and technological conditions of biology learning environments, including lighting, noise, temperature, visual clutter, screen exposure, device interruptions, room arrangement, and limited opportunities for movement. The article situates this concept within prior work on cognitive load, student engagement, classroom design, lighting, and educational technology. It then argues that environmental load is particularly relevant in biology and laboratory learning because students must coordinate terminology, diagrams, models, procedures, safety expectations, and abstract systems while managing the physical space around them. Practical next steps include classroom environment audits, intentional screen breaks, reduced visual complexity during cognitively demanding tasks, research on sensory conditions in science classrooms, and professional development that treats cognitive access as both an instructional and environmental concern.

The effect of L2 grit on willingness to communicate: The mediating role of foreign language enjoyment in blended learning.

The rapid growth of virtual education in higher education necessitates an examination of its ethical and psychological implications. This study examines the impact of students' attitudes toward e-learning on their commitment to ethical behavior and stress levels within virtual learning environments in southern Iran. A cross-sectional, correlational study involved 256 students from Bushehr University of Medical Sciences from October 2022 to March 2023. Participants were selected through quota sampling and completed validated tools, including the Student E-Learning Attitude Questionnaire, Cohen's Perceived Stress Scale, and a researcher-designed Ethics in Virtual Education Questionnaire. Data analysis was performed using SPSS v20, with a significance level set at p < 0.05. The mean (±SD) scores were 79.60 ± 11.16 for e-learning attitudes, 28.04 ± 8.15 for perceived stress, and 149.74 ± 16.87 for ethical practice. Attitudes toward e-learning significantly predicted ethical practice in virtual education (β = 0.167, 95% CI: 0.077 to 0.429, p = 0.005), while no significant relationship was observed between e-learning attitudes and perceived stress (p > 0.05). Positive attitudes toward e-learning foster students' adherence to ethical standards in virtual education but do not directly impact perceived stress levels. These findings underscore the importance of fostering constructive perceptions of virtual education and promoting ethical literacy to enhance educational quality and student well-being.

Expressions of learner agency in virtual inquiry: Linking agency and evidence-centered game design

Early learning takes place within complex, multimodal environments where curiosity plays a critical role in guiding exploratory behaviors and supporting cognitive development. While trait curiosity shapes children's early learning experiences, state curiosity is context-dependent fostering early learning, in-part, through information seeking behaviors. Here, we explore whether state-induced curiosity can influence exploratory behaviors and facilitate word-learning within a multimodal search task that mirrors real-world learning environments. Children (2.5- to 4-year-olds) will be introduced to novel objects and labels via a storybook. After exposure to each novel object, participants will locate the target object (i.e., a sticker depicting the novel object), hidden within one of ten boxes uniformly distributed across a real-world space. Unbeknownst to participants, the target will only be hidden within a single hemispace. In the "High-Curiosity" condition, the storybook should elicit greater curiosity, whereas the "Low-Curiosity" condition will present novel words in a context that should invoke lower levels of curiosity. Following the search task, participants will complete a forced-choice word learning task. Findings will provide insights into whether and how curiosity facilitates word learning in rich, multimodal contexts and how this relationship can be impacted by children's explorative strategies, including their sensitivity to environmental statistics. SUMMARY: Curiosity drives early development, but the extent to which it facilitates learning within a multimodal environment remains underexplored. The study examines how high versus low induced curiosity states influence toddlers' exploratory behavior, including search efficiency and adaptation to spatial probability cues. The study assesses whether higher state-induced curiosity leads to stronger retention and recognition of novel word-object mappings compared to the lower curiosity condition. The study examines how curiosity-driven search strategies relate to novel word learning and whether learning is moderated by how children choose to search for information.

This study examines school dropout as a multidimensional and process-oriented phenomenon by focusing on its underlying causes, emotional meanings, and prevention-oriented implications. Using an interpretative phenomenological design within a qualitative research framework, the study involved 24 participants with school dropout experience who varied in age, gender, educational level, dropout stage, occupation, place of residence, and income level. Data were collected through a semi-structured interview form developed by the researcher, reviewed through expert feedback, and refined after pilot implementation. The data were analyzed with the support of MAXQDA, drawing on Yin’s qualitative analysis cycle and Braun and Clarke’s stages of thematic analysis. The findings indicate that school dropout is shaped by the interaction of individual, familial, environmental, and structural factors. Economic hardship, work and family responsibilities, lack of institutional support, academic difficulties, negative peer influence, gender-based barriers, and limited rural opportunities emerged as prominent determinants. Participants interpreted dropout primarily in terms of sadness, disappointment, regret, and incompleteness, although some regarded it as a necessary decision under existing conditions. The results further suggest that dropout prevention requires integrated early warning systems, academic and psychosocial support, family-school collaboration, inclusive learning environments, career guidance, and flexible policies sensitive to socioeconomic inequalities. Overall, the study suggests that school dropout cannot be reduced to individual choice; rather, it should be addressed through student-centered, equity-oriented, and multi-stakeholder interventions.

The relationship between challenge and feedback mechanisms in gamified learning experiences and learning engagement: The mediating role of flow.

On-call simulation in diagnostic radiology; an underused medical education tool.

Clinical training challenges in critical care units for nursing students: A qualitative content analysis.