Search Results (252)

Social media platforms increasingly function as informal education systems for programming learning, yet the systemic support structures these environments provide remain poorly understood. We analyzed 40,004 comments from programming tutorial videos on a major social media platform (2016–April 2025) to identify patterns of learner support needs at scale. Using BERTopic, we identified twelve discussion themes. We then consolidated these themes into a learner-needs typology based on their dominant support functions: instructional-oriented needs, operational support needs, and knowledge-constructionneeds. We mapped this typology onto the Community of Inquiry (CoI) framework to assess its explanatory coverage. This mapping revealed a critical systemic gap. Operational support needs, covering environment configuration, tool integration, dependency management, and technical troubleshooting, constituted the largest category (44.53% of theme-level discourse), exceeding both knowledge-construction needs (28.42%) and instructional-oriented needs (26.95%). Learners repeatedly described these infrastructure-level challenges as disrupting their attempts to engage with content, execute code for testing ideas, and coordinate with peers, yet these operational readiness needs are not fully specified by CoI’s traditional presences. Social presence did not emerge as a standalone theme at the topic-modeling level; rather, social cues were often embedded within task-oriented troubleshooting. Based on these findings, we propose Technical Presence as a context-sensitive extension to the CoI framework, defined as the extent to which a learning community enables operational readiness through accessible infrastructure support and collaborative troubleshooting. As an infrastructural support condition, Technical Presence supports operational readiness within tool-dependent, practice-based learning: when learners report infrastructure failure, the conditions for enacting instructional design, cognitive inquiry, and peer collaboration are correspondingly weakened. These findings carry implications for content creators, platform developers, and education system designers seeking to strengthen the infrastructural foundations of technology-enhanced learning at scale. Full article

This study focuses on the design and development of instructional materials tailored for the subject fundamentals of food processing, with the primary objective of equipping students with foundational knowledge and practical competencies essential to understanding core concepts and principles within the discipline. The instructional content was purposefully crafted to align with established course learning outcomes and the broader curricular framework. Drawing upon contemporary research and pedagogical best practices, the materials were customized to address the specific academic needs, interests, and learning preferences of students. Emphasis was placed on interactivity and inclusivity, with the integration of varied media formats to support diverse learning styles and enhance accessibility. The expert’s evaluation of the instructional materials is based on the three criteria: content, organization and structure, and support for learning. Overall, the instructional material has a mean of 3.71, with a verbal interpretation of high evidence and a standard deviation of 0.11, indicating high reliability. The highest mean score is 3.79 for the content category. This indicates that the instructional material is highly effective in aligning with course requirements, currently accurate, and bias-free. The lowest mean score is 3.67 on organization structure and support for learning. These scores suggest that while these areas are well regarded, they have certain aspects that could be further improved. Moreover, the materials must exhibit flexibility and adaptability to accommodate various teaching methodologies. They should seamlessly integrate with various instructional strategies, including project-based learning, problem-based learning, and hands-on activities. This versatility ensures that educators can employ diverse approaches to cater to their students’ needs and learning preferences. Full article

Federal post-quantum cryptography migration is scoped around three categories of cryptographic assets: libraries, protocols, and key stores. We argue that this scoping is incomplete. Cryptographic functions and key material can be realized in the parameters of machine-learning models, and the current open-source serialization-focused scanners we evaluated do not detect them. We provide an existence proof: a 30-layer feed-forward ReLU network that realizes AES-128 exactly, with the master key and all eleven round keys resident directly in the layer bias vectors and recoverable by parsing. The construction validates bit-exactly against FIPS 197 and the NIST CAVP AESAVS known-answer subsets across 10⁴ random plaintext-key pairs, including under float32 quantization. We argue analytically—by a sizing analysis rather than empirical construction—that ML-KEM and ML-DSA private keys hide more comfortably in modern weight tensors than AES keys do. The basis is twofold: larger key sizes amortize the construction’s fixed parameter overhead, and the lattice arithmetic underlying these primitives admits more architectural variation than the rigid AES key schedule. Under the harvest-now-decrypt-later threat model, the consequence is direct: any long-lived cryptographic key embedded in an open-weights model artifact distributed today is recoverable by any future party with knowledge of the embedding scheme, with no quantum capability required. We propose an audit primitive—a parameter-space cryptographic recognizer—that screens model artifacts at ingestion through four stages: structural matching against cipher fingerprints, a parametric analysis for bias-and-sign coupling signatures, functional probing for cryptographic input–output behavior, and the integration with cryptographic bill-of-materials tooling as a parameter-resident cryptographic content emission class extending the MBOM-PQC schema. The recognizer is defense-in-depth: it closes the gap for known constructions and architectural fingerprints without claiming completeness against adaptive adversaries. We make no claim that any deployed model contains such an embedding; the contribution is the existence of the capability, the absence of detection in the scanners we evaluated, and the migration-scope consequence. Full article

Humankind is facing the enormous challenge of ensuring a sustainable future for new generations. A key guide to addressing this challenge is the Sustainable Development Goals (SDGs), which aim to promote economic and social development and environmental preservation. Despite the good intentions embedded in the SDGs, current performance worldwide remains below expectations. To be effective, the progress on the SDGs depends on the creation of new scientific knowledge. In this context, universities and research institutes should play a fundamental role in generating new scientific knowledge. Although recent models have been developed to assess universities’ knowledge creation to advance the SDGs, it remains necessary to develop new models that can more effectively evaluate and detail this capability. The goal of this article is to introduce a three-level framework for identifying SDG science at the country level across universities and research institutes. This model is validated through a documentary study based on SciVal-Elsevier data, on Brazilian universities, and a research institute in the context of SDG 2 research—zero hunger—between 2015 and 2024. As the main results, the framework provides three levels of knowledge mapping based on subject areas, knowledge categories, and cluster names, whereas the first and the last are used in the Scopus database, and the third is proposed in this study. As a result, this framework consists of a practical instrument for the mapping of the effective issues addressed in each SDG, and for comparing the effective content of SDG science between research institutions. As the main contribution, this article introduces a practical instrument for the assessment of the contribution of universities and research institutes in SDG science. Theoretically, this framework provides a practical process for rapidly identifying the current SDG science performance in research institutions at the country level. For practical purposes, this study can be used by universities, research institutes, and policymakers to understand the current state of SDG science in a country or region and to develop new research programmes and strategies for SDG science and innovation. Full article

A shift towards Industry 5.0 with a focus on sustainability, human centricity, and resilience requires the implementation of sustainable manufacturing (SM). Implementing SM is challenging as it requires commitment to sustainable practices at all organizational levels. Leadership is a crucial success factor but is largely neglected in the literature on SM. To address this gap, we introduce a novel approach focusing on multiple leadership dimensions. The aim is to develop effective leadership perspectives by integrating sustainable leadership (SL) theory into SM. A systematic literature review and qualitative content analysis are used to identify and analyze 79 peer-reviewed articles from the Scopus and Web of Science databases. SL serves as a frame of reference to identify relevant aspects for sustainable leaders in the scientific discourse on SM. The findings are summarized in 24 categories for integrated SM. They form a conceptual framework comprising three levels: context; systems and processes; and leadership and social aspects. Examining these aspects with interrelationships enriches the SM discourse and sheds a new, human-centered light on it. The findings can support training and knowledge transfer, thereby enabling leaders to navigate operational complexity. Furthermore, the categorization provides a foundation for developing socio-technical models and assessments for Industry 5.0 from a systemic perspective. Full article

Implementation remains a central challenge in urban policy, yet the knowledge formats designed to bridge the gap between policy goals and on-the-ground delivery remain under-examined. This study treats 250 UN-Habitat Best Practice reports not as proof of effectiveness but as a standardized genre through which local interventions are narrated, compressed, and made portable for replication. We extract three focal sections, namely Results, Lessons Learned, and Transferability, apply systematic thematic coding with 906 open codes consolidated into axial categories, and compute co-occurrence networks using Jaccard similarity and Lift to detect thematic bundles, holes, and silos within and across sections. Three findings emerge. First, the reporting repertoire narrows progressively, as mean thematic richness declines by 28.2% from Results to Transfers while concentration increases 4.2 times, with substantive dimensions such as governance, equity, sustainability, and evidence losing prevalence to circulation-oriented themes. Second, formal bundle detection yields zero qualifying pairs across all six matrices, indicating a loosely coupled reporting grammar anchored by generic silos rather than integrated implementation packages. Third, structural holes concentrate at the pipeline’s end, where infrastructure transfer and sustainability as transferable value are the most systematically disconnected themes. These patterns reveal a portability paradox in which the reporting format achieves institutional legibility, making practices comparable within a shared vocabulary, but progressively filters out the physical, evidentiary, and context-sensitive content that operational reproduction would require. Full article

Digital tectonics is often discussed through design–production integration, computational form generation, and digital fabrication, yet frameworks that systematically explain how architectural knowledge is constituted in process remain limited. This study addresses that gap by approaching digital tectonics not as an instrumental or formal design approach, but as a knowledge regime. Methodologically, it combines a conceptual–genealogical approach with an onto-methodological reading strategy grounded in Deleuze’s ontology of becoming and De Landa’s assemblage methodology and develops a core reading matrix. The study shows that knowledge in digital tectonics intensifies across potential setup, the productive threshold, behavioral stability, and feedback. Within this model, architectural making knowledge is understood not as a fixed content represented in advance, but as an operative process that concentrates decision-making within production and is reorganized through feedback. The article concludes by proposing an analytical reading model that redefines digital tectonics not merely as a technical or formal category, but as an onto-methodological problem field in which architectural knowledge is constituted in process. Full article

Ocean Literacy (OL), introduced in the early 2000s, refers to the essential knowledge individuals should acquire about the ocean by the end of formal education. Over time, the concept has expanded beyond cognitive understanding to include affective and behavioral dimensions that support attitudes and actions. Among these, emotional connections emerged as a significant driver of environmentally friendly behavior and represent a potential lever for educational practices. In this context, we conducted an informal survey involving 313 students (aged 8–12 and 14–15) living in a coastal area of northeastern Italy by means of a single open-ended question: “What is the sea to you?” Responses were analyzed through qualitative content analysis. Emotion-related expressions were the most frequent category (60.1%), followed by descriptive comments (42.8%), references to uses of the marine environment (35.8%), and statements identifying the ocean as a source of life (21.1%). Mentions of personal memories and references to the need for ocean conservation were less frequent. These findings suggest that, in our sample, frequent exposure to coastal environments may have fostered emotional connections with the ocean. Use of alternative teaching approaches (including technology-mediated ones) and further investigations into youths’ ocean connections could enhance the diffusion of OL in education settings. Full article

Background/Context: Creating instructional materials that authentically meet the needs of marginalized learner groups such as student veterans, multilingual adult learners, and first-generation doctoral students demands consistent application of Universal Design for Learning (UDL) principles coupled with meaningful content expertise about those learners’ traits, access needs, and lived experiences. Faculty at teaching-intensive institutions face persistent constraints of time, knowledge, and course load that make systematic UDL implementation difficult. Objective: This practitioner-scholar case study examines whether HAIST-structured agentic LLM-assisted instructional design can produce UDL-aligned materials for student veterans and multilingual learners at a quality level and time frame realistic for under-resourced faculty. Methodology: Drawing from the Human-AI Symbiotic Theory (HAIST) and UDL guidelines, we document four AI-assisted cycles of instructional design at a Hispanic-Serving Institution. Outcomes related to UDL alignment were measured using a rubric adapted from CAST Guidelines 2.2. Results: Across four materials, initial AI generation averaged 61.4% UDL alignment (SD = 8.7%); following iterative calibration, this rose to 84.2% (SD = 5.3%). The largest gains occurred in the Engagement category. Conclusions: These descriptive findings, interpreted as exploratory rather than inferential given the single-site case study design and n = 4 materials, suggest that HAIST-structured AI-assisted design has the potential to produce accessible materials for underserved learner populations in time frames feasible for working faculty. Learner outcome data were not collected in this study; future quasi-experimental work is needed to assess the effectiveness of these materials with target learner populations. Full article

Background/Objectives: Cerebral palsy (CP) is the most prevalent physical disability in the pediatric population, resulting in functional limitations and restrictions in participation, with higher prevalence rates in low- and middle-income countries. Caregivers of children and adolescents with CP face both physical and emotional challenges, and their perceptions of the body may act as contextual and cultural indicators shaping children’s participation, care practices, and well-being within the family environment. This study aimed to understand the perceptions, values, and cultural beliefs of family caregivers about the bodies of children and adolescents with CP. Methods: A qualitative study was conducted using six focus groups with 22 mothers and grandmothers of children and adolescents with CP. Participants were recruited from rehabilitation services. Discussions were audio-recorded, transcribed verbatim, and analyzed using content analysis. The analytical process involved systematic coding, categorization, and thematic interpretation to identify recurring meanings and patterns across narratives. Results: Three thematic categories emerged: (1) perceptions of the body within social interactions; (2) viewing the body as capable of performing activities independently when stimulated/taught; and (3) viewing the body as dependent, requiring constant supervision and support. Conclusions: The findings highlight the need to expand family caregivers’ knowledge about CP to promote children’s participation and mitigate beliefs related to limitations, dependence, fragility, and vulnerability. Full article

Patents are essential carriers of technological innovation, and their efficient transfer is critical for accelerating technological iteration in the lithium battery industry and supporting sustainability in the new energy sector. However, existing patent recommendation methods lack frameworks for handling heterogeneous enterprise demands, which limits the accuracy of supply–demand matching. This study proposes a knowledge graph-based differentiated patent recommendation framework for enterprise technological demands in the lithium battery domain. A five-element content framework—material, method, efficacy, product, and application—is constructed from both the supply and demand sides. Enterprise demands are classified into complete and incomplete types based on element coverage, and patent supply knowledge graphs are built for potentially relevant patents. Two differentiated recommendation methods are then developed. For complete demands, the Precision Recommendation Method for Complete Technological Demands integrates BERT-based semantic encoding, TransE-based structural modeling, and RAG-based constraint retrieval to achieve precise matching under full element coverage. For incomplete demands, the Fuzzy Recommendation Method for Incomplete Technological Demands incorporates multi-source enterprise data to enrich demand categories and constructs augmented query contexts to generate diversified candidate patent sets. Empirical validation based on 25 demand-driven patent transfer cases shows that the PR-CTD method exactly identifies the actual transferred patents in three cases. The FR-ITD method ranks 6 out of 14 actual transferred patents within the Top-5 results, while the remaining cases are all within the Top 13. These results demonstrate the effectiveness of the proposed framework in real-world patent transfer scenarios. This study provides a novel theoretical perspective for the structured modeling of heterogeneous technological demands and supply–demand semantic matching. It also offers practical value by improving the efficiency of patent retrieval and matching, thereby supporting patent technology transfer in the lithium battery industry. Full article

The momentum to reduce global reliance on a few staple food crops has been growing in recent years, partly fuelled by a belief that the situation is precarious and the world is at risk of a major food crisis. In this context, the perspective paper poses the overarching question: “Are alternative crops needed for future sustainable food production?” In responding to the question, it critically analyses the following: the risk of reliance on a few staple food crops; the importance of widely grown, preferred crops that are not considered global staple food crops; the confusion surrounding the term “alternative crops” and other crop categories; the positive and negative characteristics of some candidate alternative crops compared to staple and commonly grown crops; the dangers of promoting indigenous crops as alternative crops; the current and expanding knowledge base of the three most important staple food crops for stress tolerances and nutritional content to support future food production; and research needs for developing alternative crops in a declining funding scenario for agricultural research and development. The emphasis is on the Global South, where future needs are likely to be greater. It concludes that unless the existing staple and widely grown food crops face catastrophic limitations to future food and nutritional security under changing climates or other known risks, with current limited available funding for research, emphasis should be given to further improvement of staple and widely grown crops to cope with stresses. Alternative crops with useful additional traits could be available to complement staple crops rather than replacing them. Difficult choices may need to be made. Choices are likely to be country or regionally based, and cropping system-specific. It will be essential to consult with all actors—especially farmers—on the degree to which alternative crops have a role to play in contributing to future sustainable food production. Full article

Background: The delivery of nursing care based on available evidence and centered on the individuals who require it and has a positive impact on the quality of professional interventions, leading to health benefits for the population across all core domains of nursing practice, as well as contributing to the advancement of the profession. Objective: To analyze nurses’ perspectives on the effects of their participation in evidence implementation programs in clinical nursing. Methods: In the Qualitative Descriptive Study, the study participants were nurses who took part in the “Safe Transition” project, a collaborative initiative involving three institutions: a nursing school, a hospital, and a network of primary healthcare institutions. The data were collected through semi-structured interviews that were analyzed by two researchers using content analysis techniques, with the support of the qualitative data analysis software. Results: From the content analysis of semi-structured interviews conducted with 17 nurses involved in knowledge implementation projects in clinical practice, the following categories emerged: Cultivating a spirit of inquiry and an evidence-based practice culture; Critically appraising established practices and evidence-based recommendations; and Integrating evidence into clinical expertise to drive change, improve outcomes, and enhance the quality of care. Conclusions: Effective communication and structured opportunities for knowledge sharing emerged as central to the critical examination of clinical practice and to the development of professionals’ competencies in evidence use. Evidence implementation was further motivated by professionals’ recognition that it can generate tangible benefits for healthcare service users. Collectively, these findings inform recommendations for clinical practice, nursing education, and future nursing research. Full article

Adolescent tobacco use remains a critical public health challenge, requiring innovative early prevention strategies. This study participatively evaluated a medium-fidelity prototype of the No le entres app, designed to prevent tobacco use among adolescents. The prototype was developed based on user-centered design and gamification frameworks, with the aim of ensuring cultural relevance and active user engagement. Qualitative design with content analysis was employed. Four focus groups were conducted in Xalapa, Veracruz: two with health professionals from Medical Specialty Units—Community Mental Health and Addiction Centers (UNEME CECOSAMA), and two with secondary school students. Nineteen professionals and twenty-two adolescents participated. Data were analyzed using MAXQDA 2022, applying both a priori and emergent categories. Professionals valued the app’s innovative approach but recommended improvements in navigation speed, visual design, message clarity, and cultural validation. Adolescents emphasized the need for more engaging features, such as music, rewards, team competitions, and updated graphics. Both groups highlighted the importance of interactivity, personalization, and contextualized content. Findings underscore the value of participatory methods in designing digital health interventions and confirm that involving end users enhances usability and acceptability. The app demonstrates potential for integration into school settings as a preventive tool, with implications for influencing adolescent knowledge, attitudes, and behaviors regarding tobacco use. Full article

Pull request templates are used to reduce inconsistencies in information included in submitted pull requests in GitHub. A few studies have explored the effectiveness of employing pull request template. However, there is still a lack of how to evolve PR templates during software development. Knowledge is crucial to efficiently manage PR templates. To address this gap, we conducted a study on the organisation and evolution of pull request template initial content. For the study, 2689 target PR template files from 2614 public GitHub repositories were collected and 7 PR content categories including Description, Checklist, Reference, Test, Type, Additional Info, and Other were manually defined from the target files. Based on the defined categories, a pull request content classifier was built. By using the target dataset and the classifier, initial content organisation and its evolution were investigated. The results showed that 68% of target pull request templates organise their initial content with only two or fewer categories, and the initial content organisation remains in 71% of the entire pull request templates. Full article