Arts and Humanities

Abstract: Paradoxically, whilst historic Environment, Culture, Heritage, and Arts (ECHA) organisations curate knowledge for the public, thousands of them lack the required operational knowledge to manage their rapidly changeable and demanding operations. Their management requires extensive up-to-date knowledge, in accessible recorded formats (knowledge artefacts) interacting with human experience. For decades, the ECHA ecosystem, ECHAsystem [EE-kah-siss-tuhm], has been in a protracted crisis resulting in reduction of service for, and closures of, thousands of these organisations. The purpose of this cross-sectional, parallel mixed methods applied research was to develop a beneficial operational knowledge curating design to improve the ECHAsystem’s organisational sustainability. The findings demonstrated that accessible and up-to-date knowledge significantly improves processes and organisational sustainability performance. It also showed that a wise, allied development of knowledge resources, and allied application of available organisational resources, produces the greatest results. The research proposed the Athena [ah-thee-NAH] de-sign: a Knowledge Alliance coordinating the Operational Wisdom Library (OWL), in-formed by 31 networks across the ECHAsystem’s habitats and operations. The design can help individuals to grow professionally, organisations to thrive, and the ECHAsystem to achieve its aspirations. The research advocates a unified ECHAsystem benefiting from collaborative application of knowledge to deliver its public-good, intergenerational, organisational sustainability objectives.

Abstract: The rapid adoption of generative artificial intelligence (AI) in higher education has created new opportunities for learning while raising concerns about cognitive offloading, reduced mental effort, and the erosion of foundational academic skills. Although existing research highlights both the benefits and risks of AI, it provides limited guidance for instructors making practical decisions about when AI should be encouraged or constrained in instructional design.This conceptual article introduces the Bloom-Aligned AI Integration Model (BAIM), a pedagogical framework that serves as a decision-making model for AI use by aligning AI integration with the cognitive categories of Bloom’s Revised Taxonomy. The model distinguishes between independent (AI-constrained) and AI-collaborative learning activities and assessments across all levels of cognition. Bridging learning science and AI integration, BAIM draws on research related to cognitive effort, metacognition, and skill development to position AI as a variable that must be calibrated according to instructional goals. In doing so, it offers actionable instructional design guidance by linking cognitive objectives to decisions about AI use, enabling instructors to support both independent student learning and responsible engagement with AI in higher education.

Abstract: Reflectance Transformation Imaging (RTI) has long been employed across multiple re-search domains to document surface textures, inscriptions, and fine morphological features, including in paleontology. However, RTI requires specialized equipment and controlled acquisition protocols that are often impractical in fieldwork or heterogeneous documentation contexts. To overcome these limitations, Virtual Reflectance Transfor-mation Imaging (VRTI), based on high-resolution 3D models acquired through photo-grammetry or structured light scanning, has emerged as a promising alternative. This study investigates whether VRTI offers an operationally simpler yet perceptually equivalent alternative to conventional RTI for dinosaur footprint interpretation, while providing a standardised FAIR-compliant VRTI workspace implemented in an open-source 3D environment. A comparative protocol was developed and validated through a classroom experiment involving paleobiology students, who performed footprint delineation and morphological interpretation using both RTI and VRTI da-tasets derived from a dinosaur footprint from the Geological Collection of the "Giovanni Capellini Museum" of the University of Bologna. The evaluation combines quantitative statistical analysis with qualitative expert assessment to compare interpretative per-formance, while optimal PTM-based raking lighting conditions are also investigated. The results indicate that VRTI achieves footprint readability comparable to conventional RTI without introducing perceptual bias. Building on this validation, the proposed workspace demonstrates satisfactory usability and offers a reproducible, interoperable, and scalable workflow for cultural heritage documentation.

Abstract: This research paper examines the evolving role of police forces in enforcing Intellectual Property Rights (IPR) in India, a critical yet underexplored dimension of India's intellectual property regime. As India transitions into a knowledge-based economy and strengthens its IPR framework to comply with international obligations under TRIPS (Trade-Related Aspects of Intellectual Property Rights), law enforcement agencies have assumed increasingly significant responsibilities in combating IP crimes. This paper analyzes the legal framework empowering police action in IPR cases, examines specialized police units established for IP enforcement, evaluates operational mechanisms and challenges, and proposes recommendations for strengthening police capacity in this domain. Drawing on scholarly literature, legal provisions, and case studies, the paper reveals that while India has made notable progress in establishing specialized IP crime units and providing legal powers for police intervention, significant challenges persist including inadequate training, resource constraints, jurisdictional complexities, corruption, and coordination gaps between stakeholders. The findings underscore the need for comprehensive capacity building, inter-agency collaboration, technological modernization, and policy reforms to enhance the effectiveness of police in protecting intellectual property rights in India.

Abstract: This research paper examines the critical intersection of traditional ecological knowledge (TEK) protection, dam development, and glacial lake outburst flood (GLOF) mitigation in mountain regions, particularly the Hindu Kush-Karakoram-Himalaya (HKKH) region. Drawing from 77 peer-reviewed studies, this review synthesizes evidence on how indigenous and local knowledge systems can be protected and integrated into large-scale infrastructure projects and disaster risk reduction strategies. Key findings reveal that while TEK offers invaluable insights for GLOF early warning systems and community-based adaptation, significant gaps persist in formal protection mechanisms, particularly in dam planning contexts. The paper identifies successful participatory frameworks, documents persistent challenges in knowledge integration, and proposes policy recommendations for safeguarding TEK while enhancing climate resilience in vulnerable mountain communities. This synthesis is particularly timely given the accelerating impacts of climate change on glacial systems and the expansion of hydropower infrastructure in high-mountain Asia.

Abstract: Peer teaching has been proposed as a pedagogical mechanism to foster independent learning, willingness, and confidence in students' learning processes (Doyle, 2008). However, the empirical evidence supporting these claims in English as a Foreign Language (EFL) contexts remains limited, with few studies examining the applicability and effectiveness of peer teaching approaches in African educational settings. This quasi-experimental study examines the effect of peer teaching on students' classroom engagement—comprising behavioral, cognitive, and emotional dimensions—and English language achievement in Ethiopian secondary EFL classrooms. The study involved 91 Grade 11 students from two randomly selected sections at Dangila Higher Education Preparatory School. Six students from the experimental group (n=45) were selected and trained to peer-teach grammar lessons over a four-week period, while the control group (n=42) continued with conventional teacher led instruction. Data were collected using a classroom engagement questionnaire (Cronbach's α = 0.82) and grammar tests administered both before and after the intervention, with independent samples t-tests employed for statistical analysis. The findings revealed no statistically significant effect of peer teaching on either students' engagement or language achievement. Unexpectedly, the experimental group showed a slight decline in behavioral engagement compared to the control group, while no significant differences were observed for cognitive or emotional engagement, nor for language achievement between the two groups. These findings challenge assumptions about the universal effectiveness of peer teaching in EFL contexts, suggesting that contextual factors—including learner readiness, implementation quality, and cultural considerations—may significantly moderate its pedagogical impact. The study underscores the critical need for careful consideration of implementation conditions and learner characteristics when adopting peer teaching approaches in similar educational settings, and highlights the importance of contextual adaptation rather than uncritical adoption of pedagogical innovations.

Abstract: Writing constitutes a central component in the assessment of knowledge at the university level, as it enables students to demonstrate disciplinary understanding and academic performance. Given the frequency with which learning is evaluated through written assignments, feedback provided through written comments becomes especially relevant. Although numerous studies (Prado & Pérez, 2021; Tapia-Ladino & Correa, 2022) position feedback as a valuable and necessary pedagogical practice there is still limited research in Latin America examining how students engage with and make use of the feedback they receive. This study aims to examine how university students construct meaning from feedback through peer interactions at a regional university in Chile. The research was conducted with fourth-year students enrolled in an English as a Second Language Teacher Education program. Participants completed a written assignment in pairs and subsequently received feedback from their teacher on their work. For data collection, feedback encounters (Esterhazy & Damşa, 2019) were organized, during which general guidelines were provided to support student interactions. These interactions were audio-recorded, transcribed, and analyzed through category coding using Nvivo15 software. The findings revealed that students construct meaning from feedback through two recursive and iterative interaction sequences. The first, an extended sequence, is organized around the stages of idea generation, revision, discussion, decision-making, and elaboration. The second, a shorter sequence, includes idea generation, revision, and elaboration. Both sequences contributed to students’ decision-making and following actions in the task.

Abstract: Social media platforms and user-generated content (UGC) have become central to how travelers discover and evaluate cultural destinations. Yet lesser-known second-tier heritage sites remain substantially underrepresented in digital tourism research. This study investigates how Chinese tourists perceive and engage with the intangible cultural heritage (ICH) of Lamphun, Thailand, through UGC collected from three major Chinese social media platforms (WeChat, Douyin, and Rednote) spanning the period from 2019 to 2023. A total of 642 relevant posts were analyzed using a mixed-methods analytical framework comprising VADER-based sentiment analysis, machine learning classification of tourism intention, and TF-IDF-driven thematic clustering. Results indicate an overall predominance of positive sentiment, particularly toward social rituals, festive events, and traditional craftsmanship, with positive sentiment emerging as the strongest predictor of travel intention. Digital engagement metrics, notably likes and favorites, further amplified the impact of intention-bearing content, while thematic clustering revealed four distinct experiential dimensions, with festival and ritual-centered narratives generating the highest sentiment and tourism intention scores. These findings demonstrate the strategic value of integrating advanced UGC analytics into destination marketing frameworks, offering actionable insights for promoting underrepresented cultural heritage destinations within the increasingly competitive global digital tourism landscape.

Abstract: This study examines women’s textile knowledge in Portugal as a fundamental element of cultural heritage, situating it within domestic, social, and industrial contexts, with a particular focus on Guimarães. Drawing on a multidisciplinary approach grounded in historical and documentary evidence, it analyses how female expertise in spinning, weaving, embroidery, and lacemaking contributed to the evolution of textile practices from the fifteenth century to the present day. The findings indicate that this knowledge was pivotal to the transformation of domestic textile activities into an emerging industrial sector, shaping both production methods and cultural identity. The study concludes that recognising the historical importance of women’s textile labour is essential for understanding the development of the Portuguese industry. Furthermore, this research emphasises the urgency of preserving, transmitting, and legitimising the intangible cultural heritage inextricably linked to women’s textile mastery. It argues that integrating this legacy into contemporary creative and industrial practices can foster cultural sustainability and unlock new possibilities for future innovation, ensuring that this ancestral expertise remains a living pillar of regional identity.

Abstract: In the contemporary landscape, natural language processing (NLP) stands as a vital force, empowering computers to comprehend and engage with human languages, thereby enhancing the realm of human-computer interaction (HCI) through the utilisation of large language models (LLMs) and multilingual pre-trained language models (mPLMs). The widespread adoption of these LLMs on a global scale is obvious. However, a critical observation reveals a significant gap in their capacity to effectively recognize some low-resource African languages, a concern observed by numerous researchers. This paper endeavours to contribute to the discourse by conducting a comprehensive metadata analysis of existing African language models. Through this investigation, the aim is to outline the importance, strengths, and weaknesses inherent in these models. By shedding light on these aspects, the paper seeks to not only underscore the current limitations but also to provide valuable insights and recommendations for future research endeavours in the domain of language recognition, particularly focusing on African languages. In doing so, the paper aspires to catalyse advancements that promote inclusivity and a more nuanced understanding of linguistic diversity within the realm of natural language processing. Multilingual Testing shall be used on Cheetah to evaluate the model's proficiency strength in multiple languages, including those that are less widely spoken such as Margi and Ibibio as well as identify any language-specific weaknesses or limitations of the LLMs, especially in recognizing and understanding languages like Margi spoken in the North-East geo-political zone of Nigeria and Ibibio spoken in the South-South geo-political zone of Nigeria.

Abstract: The rise of the collaborative economy has transformed global tourism through peer-to-peer platforms such as Airbnb, enabling alternative lodging options and reshaping traditional hospitality models. This study examines the phenomenon of diffuse guest accommodations in Old Cairo, a historic neighborhood characterized by rich architectural heritage and cultural traditions, where private homes are informally used to host visitors without regulatory oversight. The research aims to assess the socio-economic and cultural implications of Airbnb-driven practices, exploring stakeholder perspectives, including residents, visitors, professionals, scholars, and government officials—on their potential for sustainable tourism development. Using qualitative methods, the study analyzes community attitudes toward strengths such as economic opportunities and cultural exchange, alongside perceived threats including heritage degradation and lack of governance. Findings reveal broad support for integrating these practices into formal tourism frameworks, recommending the introduction of a new sub-classification under the Egyptian Tourism Federation and Ministry of Tourism. The study concludes that collaborative micro-economic systems, if strategically managed, can foster sustainable tourism while preserving cultural identity in historic urban contexts.

Abstract: Intangible cultural heritage (ICH) is a cornerstone of national identity, driving economic development and social cohesion globally. Yangliuqing New Year Woodblock Paintings, a representative Chinese national ICH, face development bottlenecks due to insufficient internal innovation and ineffective external interventions, with existing research lacking holistic analysis of its historical evolution and contemporary challenges. This study aims to establish a dynamic framework for its innovative development. It first identifies cultural ecological factors via representative case analysis, then employs an integrated EWM-DEMATEL-ISM model to quantify these factors, determine their core components, and map their influence relationships. The results reveal that technical factors, cultural merit, and resource factors constitute the core cultural ecology of Yangliuqing New Year Paintings, with cultural merit as the deep-layer cultural gene, technical factors as the intermediate maintenance force, and resource factors as the surface-level interface. Three feasible innovative development paths are proposed, centered on activating cultural merit, upgrading technical factors, and optimizing resource allocation. This research provides a new analytical perspective for Yangliuqing New Year Paintings and offers insights for the sustainable development of other ICH categories by integrating historical context with future-oriented strategies.

Abstract: The city of Bukavu, Democratic Republic of Congo, faces multiple urban mobility challenges. Already confronted with major socio-economic issues, it must cope with rapid population growth, accelerated and unplanned urbanization, and signifi cant defi cienciesin transport infrastructure. Approximately 70% of the population lives in precarious conditions, severely limiting access to reliable transport services. Furthermore, due to its hilly terrain, the city is strongly affected by climate-related disruptions, which negatively impact transport networks and increase user costs. These factors exacerbate economic vulnerability related to mobility and strain household budgets. This study adopts a quantitative, predictive approach to better understand and anticipate household vulnerability in daily mobility, contributing to more inclusive public policy development. The analysis relies on Principal Component Analysis (PCA) to identify key determinants, followed by clustering to segment households according to their vulnerability level. Finally, three predictive models were compared. Cluster analysis revealed three distinct vulnerability profi les, highlighting marked socio-economic stratifi cation. The most disadvantaged households, representing 73% of the sample, are the most exposed, with budget shares reaching up to 50% of income. Conversely, affl uent and middle-class households enjoy better mobility conditions but remain sensitive to economic and climate shocks. These fi ndings underscore the need to integrate spatial and economic inequalities into local public policy planning. Among the tested models, logistic regression stood out for its accuracy and its ability to identify vulnerable households with perfect recall.

Abstract: Advanced Design, as a discipline focused on exploring future opportunities, has the potential to significantly enhance New Product Development, understood as the process of designing and introducing new products to the market. However, organizations such as COTECMAR -the Science and Technology Corporation for the Development of the Naval, Maritime, and Riverine Industry, a mixed public and private organization- despite their extensive experience and capabilities in New Product Development, have traditionally concentrated their design efforts on addressing immediate and operational challenges. While the automotive industry has long employed concept cars to anticipate future scenarios, this practice has not been widely adopted within the shipbuilding sector, and even less so in Colombia. Within this context, an opportunity emerged to develop vision concepts - analogous to concept cars but applicable across industries -to explore potential future pathways for COTECMAR in Colombia’s Pacific Region. Through the application of DIVE, an Advanced Design technique, this research project explored and articulated ten diverse vision concepts. These range from an amphibious boat operating in conjunction with a health center built on stilts to improve access to quality visual healthcare services, to integrated tourism mobility systems composed of small yacht cruises, floating stations, and collectible tickets that connect travelers and local communities with the region’s natural and cultural assets. Across these explorations, it became evident that Advanced Design holds substantial potential to strengthen COTECMAR’s New Product Development processes. It can unlock new creative opportunities by expanding the Corporation’s product portfolio, fostering the adoption of a product–service systems approach, and enabling engagement with a broader and more diverse set of target markets.

Abstract: This study develops an innovative method for the attribution and visual reconstruction of hand-woven fabrics using artificial intelligence, employing Chinese Hong'an Homespun as a case study. The paper proposes a comprehensive algorithm integrating microscopic analysis, physical micro-model creation, and bimodal prompt engineering. The semantic differential method with a five-point scale was applied for objective evaluation of visual replica of historical fabrics. Comparative testing of AI models (Midjourney, ChatGPT, Qwen3, DouBaoAI, HailuoAI) revealed significant differences in their ability to reproduce characteristic features of hand weaving. The results demonstrate the superiority of detailed prompts with precise quantitative parameters and confirm the effectiveness of micro-models as visual anchors. The research establishes new standards in the digital documentation of cultural heritage and opens prospects for preserving traditional textile techniques. The most successful AI are Midjourney and ChatGPT have achieved an average score of 0.88 on the semantic scale, confirming the practical applicability of the method.

Abstract: Recent conflicts indicate a structural inversion in the economics of warfare. The exposed human warfighter, requiring prolonged training, continuous sustainment, and high replacement cost, now operates at a growing disadvantage relative to low cost, rapidly replaceable machine systems. This paper argues that modern warfare is increasingly governed not by individual skill or platform sophistication, but by logistics, replacement speed, and cost asymmetry under sustained attrition. Using attrition economics and battlefield evidence from the ongoing war in Ukraine, the analysis demonstrates that humans are being displaced from exposed combat roles not primarily by ethical preference, policy choice, or doctrinal failure, but by binding logistical and regeneration constraints. As low cost systems absorb risk at scale, the human role shifts away from the highest-attrition layer toward remote command, supervision, and coordination, while machines assume primacy at the point of contact. This transition is observable in current conflicts and reflects a reversal in the cost structure that has historically defined military effectiveness, rendering the exposed human warfighter economically non-viable under sustained attrition.

Abstract: Cybersecurity assurance drifts under change. Tooling updates, policy revisions, monitoring redesigns, and AI-enabled automation can silently change what is measured, how it is measured, and which differences are treated as “the same,” while human workflows adapt under staffing constraints, alert fatigue, incentives, and competing priorities. We introduce a human-centred, proof-carrying approach to security assurance: a certificate layer that freezes one operational record—system boundary, defect definitions, risk scoring ruler, neutrality conventions, audit window, upgrade path, and observation interfaces—so that “improvement under upgrades” has a precise and checkable meaning. Over time, the method combines multiple interacting risk channels into a single decision-ready assurance summary with an explicit improvement margin and an explicit disturbance allowance, designed to remain interpretable during incidents and operational spikes. Across versions and refinements, it enforces a vertical-coherence requirement: upgrade effects must have a finite total footprint so that claims do not drift without bound as systems evolve. We package the framework as four auditable obligations—controlling semantic and policy drift, maintaining a uniform improvement claim, ensuring upgrade coherence, and transporting guarantees to observable evidence—and prove a Master Certificate showing that passing these checks yields version-stable, mechanically verifiable assurance envelopes on the declared episode window. The resulting rates, budgets, and slack are human-centred objects: decision-ready summaries, governance-grade non-regression guarantees, and feasibility diagnostics under organisational constraints.

Abstract: This study presents reflections from the Introduction to Sustainable Business course. Thirty-five students from various courses of the Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, participated in this course for this semester. The course applied a service-learning pedagogical method to link lecture theory with real-world practice. Data were collected based on student reflections using both qualitative methods. Embedding the service-learning model in business courses focusing on sustainability is the first in the local context and is an interactive transformational innovation in education. Data were analyzed using WebQDA software to interpret the textual data. Based on the reflection, it was proven that this course has improved the students’ professional and personal development. This study is significant for enhancing education through service-learning. The findings also reveal gaps in soft skills like communication and teamwork, guiding educators on necessary improvements. Additionally, students showed positive attitudes toward community engagement, underscoring the role of service-learning in fostering social responsibility. This study underscores the potential of service-learning as an innovative approach to higher education, offering a replicable framework for promoting transformative learning and preparing graduates for the demands of sustainable business practice.

Abstract: Contemporary global crises reveal the limitations of classical civilization theories that privilege single causal dimensions such as economic growth, military power, or cultural ethos. Drawing on recent scholarship in complexity science, global political theory, and civilizational studies, this article proposes a multi-layer systems framework that reconceptualizes civilizations as complex, adaptive, and emergent living systems. Through the interplay of material, cognitive, spiritual-ethical, ecological, and technological layers, civilizations exhibit civilizational intelligence—an emergent capacity for integrative foresight, ethical governance, and adaptive resilience. Unlike deterministic or power-centric models, this framework explains both continuity and breakdown across civilizations while providing prescriptive insights for sustainable and pluriversal futures. Comparative examples and recent empirical research illustrate how inter-layer coherence fosters resilience, whereas misalignment leads to systemic fragility, offering a paradigmatic platform for new civilizational science.

Abstract: As learning settings become more intermediated by algorithm-based platform, a new “invisible curriculum” takes shape that organizes the cognitive and affective substrates of Generation Z. This paper examines the way in which the embedded logic of these platforms (that is, the way they are designed to be quantified, to predictively recommend, and to engage) shapes attention, motivation and psychosocial well-being. Drawing on educational psychology and platform studies, we apply a mixed-method approach that combines critical architectural analysis, survey data (n=XXX), and semi-structured interviews (n=XX), with interpretation through the conceptual perspectives of attentional economics and digital nudge theory. Results suggest that algorithmic curation sustains short-cycle attention and prioritises fast interaction over slow consumption, cultivating motivational states that are attentive to notifications and micro-feedback loops. Adaptive elements can tailor learning experiences, but also promote compulsive checking, emotional volatility, and a decrease in intrinsic motivation for lengthy undertakings underscoring a fundamental tension between platform effectiveness and cognitive health. They go on to say that “platform logics” infuse educational institutions as a force that impacts them systemically. The talk will make the case for, and present specific design principles and policy mechanisms for, healthier, learner-centred digital ecosystems that re-enable agency of the algorithmic learner.