Search Results (60)

Generative artificial intelligence (GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences (HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI’s capabilities. Yet, systematic evidence on the educational impacts of GenAI on HSS students remains limited. Addressing this gap, this study draws on a large-scale survey of HSS students in China to examine its role in academic development. Guided by relevant learning theories, this study focuses on four dimensions: patterns of use, effects on learning processes and academic performance, challenges associated with GenAI use, and preferred approaches to curricular integration. We found that more than half perceived enhanced learning motivation, independent thinking and creativity, although a substantial minority reported little change or even decline. Comparatively, a notably larger majority reported academic performance gains, although these gains may partly reflect limitations in conventional assessment practices. The study identifies variations in perceived learning and performance improvements among students with differing durations of GenAI experience, along with observable disciplinary differences and modest gender differences. While an overwhelming majority valued the importance of ethical considerations, only slightly more than half were satisfied with privacy protection. Limited accuracy and overreliance emerged as the most pressing concerns reported by students. Students favored partial or optional curricular integration supported by practice-oriented training, and widely recognized GenAI’s significance for their future professional development. Grounded in student perspectives, this study offers evidence-based recommendations for the responsible and pedagogically meaningful integration of GenAI. Full article

Artificial intelligence (AI) is transforming the modern workplace by offering unprecedented opportunities to enhance employee creativity and organizational innovation. In the context of digital transformation, organizations are striving to ensure sustainable performance; however, research remains limited on how perceived AI fairness and attitudes toward AI jointly influence creativity. Grounded in Social Exchange Theory and the Technology Acceptance Model, this study proposes a moderated mediation model to examine how perceived AI fairness shapes employees’ attitudes toward AI and, in turn, their creativity, with gender acting as a moderator of the relationship between fairness perceptions and attitudes toward AI. Data were collected from 214 highly skilled employees from diverse cultural backgrounds working in technologically advanced environments. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal a positive association between perceived AI fairness and creativity. Attitudes toward AI partially mediate this relationship; however, gender does not exert a significant moderating effect. The findings highlight the importance of AI fairness, reinforced by positive attitudes toward AI, in enhancing employee creativity. They also underscore the need for responsible and equitable AI practices and provide context-specific insights into the ethical challenges of AI in socio-technologically vulnerable environments. Finally, the findings point to a shift toward a more egalitarian and inclusive organizational landscape, in which gender differences become less salient in the context of digital transformation. Full article

Creativity relies on dynamic processing within the semantic network system; however, how this system varies under different cognitive strategies remains unclear. Grounded in the Associative Theory of Creativity, this study applied four cognitive strategies (application, analogy, abstraction, and combination) as distinct input constraints to the cognitive system. We tracked the N400 component using event-related potentials (ERPs), which capture brain activity time-locked to specific cognitive events. Specifically, the N400 serves as a reliable neural marker reflecting semantic mismatch and the integration of new information. Repeated-measures analysis of covariance (RM-ANCOVA) revealed that the abstraction strategy yielded the highest level of creativity, while the application strategy yielded the lowest. Neural data indicated that attenuated N400 amplitudes under the application strategy reflected minimal prediction errors within familiar conceptual spaces, whereas pronounced N400 amplitudes under abstraction and combination strategies represent substantial cognitive effort associated with feature extraction and concept integration. Subsequent linear mixed-effects model (LMM) analysis revealed that the N400 component exerted a significant negative moderating effect on individual creativity under the analogy strategy, establishing a boundary condition for transforming semantic updating into final creative output. By exploring associative processes through micro-neural mechanisms, this research provides practical insights for optimizing creative task design and evaluation structures. Full article

Generative artificial intelligence (AI) is increasingly integrated into sustainability-oriented entrepreneurial practices, raising important questions about its role in shaping human creativity and innovation. This qualitative study examines how postgraduate social entrepreneurship students engage with generative AI during the creativity phase of sustainable startup development. Drawing on Amabile’s componential theory of creativity, this study explores how AI is perceived to relate to domain-relevant skills, creativity-relevant processes, task motivation, and social–contextual factors. Data were collected through an AI-assisted ideation task, followed by semi-structured interviews, and analyzed using reflexive thematic analysis. The findings reveal that generative AI was perceived as supporting information access and associative thinking, while being unable to replicate human intuition and the “aha” moment associated with deep creativity. Moreover, AI was perceived to have limited influence on intrinsic motivation, which remains driven by personal values and contextual responsibility. Socially, AI was consistently described as a tool rather than a teammate, with emotional responses regarded as superficial. The study further suggests that AI may be understood as a social–contextual condition and highlights a perceived trade-off between efficiency and creativity in AI-assisted ideation. These insights extend the application of creativity theory to AI-supported sustainability contexts and offer practical implications for fostering responsible, human-centered innovation in entrepreneurship education. Full article

This article investigates how women’s relative absence from medieval textual archives can be reconsidered through the study of visual and material culture. Focusing on Mongol and Yuan China and read in relation to The Travels of Marco Polo, it argues that women’s artistic production functioned as a form of embedded counter-archive that preserves traces of participation obscured in narrative sources. Drawing on Black feminist epistemology as a heuristic framework and employing critical fabulation and poetic inquiry as analytical methods, the study interprets silence as a meaningful historical trace rather than a void, and considers silence not as absence but as a structured condition of archival production. Four case studies—Guan Daosheng’s literati bamboo painting, the handscroll tradition associated with Lady Su Hui, imperial phoenix embroidery, and Silk Road textile fragments—demonstrate distinct modes through which women’s presence becomes materially legible: mediated visibility, formal containment, infrastructural anonymity, and circulatory displacement. These “quiet arts” reveal how women’s labour and creativity persisted within and alongside patriarchal inscriptional systems even when textual attribution receded. In dialogue with the shadow silhouettes of contemporary artist Kara Walker, the article further situates these premodern archives within a broader visual language of absence and recovery. Rather than reconstructing lost biographies, it proposes a transdisciplinary method—integrating art history, feminist theory, theology, and poetic inquiry—for reading material culture as a site where historical silence becomes structurally legible. It proposes a transdisciplinary approach that expands art historical methods for interpreting gender, authorship, and archival silence in medieval visual culture. Full article

As generative artificial intelligence (AI) technologies become increasingly present in creative and professional domains, examining public discourse surrounding these tools is important for understanding their broader social implications. This study conducts a two-part analysis of the initial public reaction to Sora, the generative video model developed by OpenAI, by analyzing 23,543 English-language comments posted on YouTube between February and April 2024. Rather than relying on traditional positive–negative sentiment classifications, this study integrates fine-grained emotion detection with topic modeling to examine the relationship between emotions and topics in the discourse. Based on the residual analysis, the overall association between topics and emotions was weak; however, certain topics were associated with specific emotions. For instance, ethical discussions were more likely to be associated with sadness and anger, artistic settings were associated with fear, and benchmark discussions were associated with joy. Methodologically, this study utilizes an emotion–topic coupling through residual deviation with a hierarchical LDA-BERTopic approach, bringing together computational modeling and theories of emotion. This study provides a structured and theory-based way to explore the affective and thematic patterns in the public’s discourse surrounding Sora. Full article

The teaching profession plays a central role in shaping educational quality and student development, yet it is increasingly characterized by high job demands and increasing pressures. Against this backdrop, this study examines how individual proactive behaviors (i.e., structural and social job crafting) interact with relational resources (i.e., LMX), to foster teachers’ emotional well-being and professional functioning, drawing on the Job Demands–Resources (JD-R) model and LMX theory. Using cross-sectional survey data from 374 Flemish public secondary school teachers, we investigated the relationships between job crafting, well-being, and performance outcomes, as well as the mediating role of LMX. The results indicate that both forms of job crafting are significantly associated with lower emotional exhaustion and higher teacher enthusiasm and creative performance. Moreover, LMX emerged as a key, yet underexplored, mediating mechanism linking job crafting to teacher well-being and enthusiasm. These findings advance theoretical understanding of how proactive work behaviors translate into positive outcomes in educational contexts and highlight the importance of high-quality leader–teacher relationships. From a practical perspective, the results suggest that encouraging teachers’ job crafting behaviors alongside supportive school leadership may be crucial for fostering sustainable well-being and performance in education. Full article

The relationship between rural Christianity and the Chinese ethical conception of interpersonal relationships has long been a central concern in scholarly research. Existing studies often frame the two as antagonistic or argue that the Christian configuration of interpersonal relationships is a mere continuation of the traditional differential mode of association (chaxu geju). However, these perspectives often neglect local Christians’ own ethno-theology and its praxis, rendering the cultural transformations brought about by conversion invisible. Focusing on the ordinary ethics of rural Christians and based on long-term fieldwork in Shui County (a pseudonym), a rural region at the junction of Jiangsu, Shandong, Henan and Anhui provinces in China, this study reveals that Christianity instantiates a dual moral authority system within believers’ daily practices: “centripetal authority” and “centrifugal authority”. The former emphasizes inner sincerity, granting believers a degree of moral autonomy. The latter establishes a divine foundation for believers’ social relations. Employing anthropologist Marcel Mauss’s theory of gift to analyze the interaction between two types of authority in the ordinary ethics of believers, this study finds that rural Christianity both consolidates and expands pre-existing, local relational configurations. The extent of this cultural transformation is closely correlated with the depth of the divine–human relationship. Consequently, Christianity’s relationship with traditional Chinese ethics transcends binary oppositions between antagonism and continuity, instead enacting a creative reconfiguration. Full article

Against the dual backdrop of the rural revitalization strategy and the pursuit of high-quality, balanced urban–rural education, optimizing rural campus spaces has emerged as an important lever for addressing educational resource disparities and improving pedagogical quality. However, conventional evaluation of campus space optimization faces two systemic dilemmas. First, top-down decision-making often neglects the authentic needs of diverse stakeholders and place-based knowledge, resulting in spatial interventions that lose regional distinctiveness. Second, routine public participation is constrained by geographical barriers, time costs, and sample-size limitations, which can amplify professional cognitive bias and impede comprehensive feedback formation. The compounded effect of these challenges contributes to a disconnect between spatial optimization outcomes and perceived needs, thereby constraining the distinctive development of rural educational spaces. To address these constraints, this study proposes a novel method that integrates regional spatial feature recognition with digital media-based public perception assessment. At the data collection and ethical governance level, the study strictly adheres to platform compliance and academic ethics. A total of 12,800 preliminary comments were scraped from major social media platforms (e.g., Douyin, Dianping, and Xiaohongshu) and processed through a three-stage screening workflow—keyword screening–rule-based filtering–manual verification—to yield 8616 valid records covering diverse public groups across China. All user-identifying information was fully anonymized to ensure lawful use and privacy protection. At the analytical modeling level, we develop a Transformer-based deep learning system that leverages multi-head attention mechanisms to capture implicit spatial-sentiment features and metaphorical expressions embedded in review texts. Evaluation on an independent test set indicates a classification accuracy of 89.2%, aligning with balanced and stable scoring performance. Robustness is further strengthened by introducing an equal-weight alternative strategy and conducting stability checks to indicate the consistency of model outputs across weighting assumptions. At the scenario interpretation level, we combine grounded-theory coding with semantic network analysis to establish a three-tier spatial analysis framework—macro (landscape pattern/hydro-topological patterns), meso (architectural interface), and micro (teaching scenes/pedagogical scenarios)—and incorporate an interpretive stakeholder typology (tourists, residents, parents, and professional groups) to systematically identify and quantify key features shaping public spatial perception. Findings show that, at the macro level, naturally integrated scenarios—such as “campus–farmland integration” and “mountain–water embeddedness”—exhibit high affective association, aligning with the “mountain-water-field-village” spatial sequence logic and suggesting broad public endorsement of ecological campus concepts, whereas vernacular settlement-pattern scenarios receive relatively low attention due to cognitive discontinuities. At the meso level, innovative corridor strategies (e.g., framed vistas and expanded corridor spaces) strengthen the building–nature interaction and suggest latent value in stimulating exploratory spatial experience. At the micro level, place-based practice-oriented teaching scenes (e.g., intangible cultural heritage handcraft and creative workshops) achieve higher scores, aligning with the compatibility of vernacular education’s “differential esthetics,” while urban convergence-oriented interdisciplinary curriculum scenes suggest an interpretive gap relative to public expectations. These results indicate an embedded relationship between public perception and regional spatial features, which is further shaped by a multi-actor governance process—characterized by “Government + Influencers + Field Study”—that mediates how rural educational spaces are produced, communicated, and interpreted in digital environments. The study’s innovative value lies in integrating sociological theories (e.g., embeddedness) with deep learning techniques to fill the regional and multi-actor perspective gap in rural campus POE and to promote a methodological shift from “experience-based induction” toward a “data-theory” dual-drive model. The findings provide inferential evidence for rural campus renewal and optimization; the methodological pipeline is transferable to small-scale rural primary schools with media exposure and salient regional ecological characteristics, and it offers a new pathway for incorporating digital media-driven public perception feedback into planning and design practice. The research methodology of this study consists of four sequential stages, which are implemented in a systematic and progressive manner: First, data collection was conducted: Python and the Octopus Collector were used to crawl online comment data related to Fuwen Township Central Primary School, strictly complying with the user agreements of the Douyin, Dianping, and Xiaohongshu platforms. Second, semantic preprocessing was performed: The evaluation content was segmented to generate word frequency statistics and semantic networks; qualitative analysis was conducted using Origin software, and quantitative translation was realized via Sankey diagrams. Third, spatial scene coding was carried out: Combined with a spatial characteristic identification system, a macro–meso–micro three-tier classification system for spatial scene characteristics was constructed to encode and quantitatively express the textual content. Finally, sentiment quantification and correlation analysis was implemented: A deep learning model based on the Transformer framework was employed to perform sentiment quantification scoring for each comment; Sankey diagrams were used to quantitatively correlate spatial scenes with sentiment tendencies, thereby exploring the public’s perceptual associations with the architectural spatial environment of rural campuses. Full article

Employee innovative behavior is an important source of organizational competitiveness and sustainable development. Accordingly, increasing scholarly attention has been directed toward how leadership behaviors are associated with employees’ innovative actions. Drawing on Affective Events Theory and the ABC Theory of Emotion, this study develops a cognition–emotion–attitude–behavior framework to examine the relationships among inclusive leadership, positive emotions, creative self-efficacy, and employee innovative behavior. Using a questionnaire survey, data were collected from 463 employees working in innovation-oriented enterprises. Hierarchical regression analyses and bootstrap procedures were employed to examine the proposed associations and indirect effects. Inclusive leadership plays a positive role in stimulating employee innovation. Moreover, positive emotions and creative self-efficacy each exhibit significant indirect associations linking inclusive leadership to employee innovative behavior. This study contributes to the literature by clarifying the affective and attitudinal processes associated with inclusive leadership and by enriching understanding of the psychological pathways linked to employee innovative behavior. Full article

This article offers a comparative study of two closely linked constellations of early Ṣūfī thought: the ascetic–mystical program of al-Fuḍayl ibn ʿIyāḍ (d. 187/803) and that of his renowned disciple Bishr al-Ḥāfī (d. 227/841). Moving beyond hagiographic anecdote, the study advances the thesis that the pair articulate two complementary modalities of tawba (repentance) that generate distinct ascetic habitus and pedagogical lineages: al-Fudayl’s “ethic of awe” (fear, juridical redress, and renunciation of patronage) and Bishr’s “aesthetics of reverence” (beauty-induced modesty, evident humility, and fame avoidance). Drawing on primary sources (Ḥilyat al-Awliyāʾ, al-Sulamī’s Ṭabaqāt al-Ṣūfiyya, al-Qushayrī’s Risāla, al-Sarrāj’s Lumaʿ), the article reconstructs each thinker’s core concepts, practices (e.g., returning wrongs, ḥafāʾ/barefoot humility), and teaching styles and maps how the teacher–disciple nexus transmits, adapts, and ritualizes these ethics into durable Ṣūfī dispositions. Methodologically, the article combines close textual analysis with practice theory to show how emotions—such as fear and modesty (ḥayāʾ)—are choreographed into public, socially legible acts, thus reframing repentance as embodied discipline rather than interior feeling alone. A prosopographic appendix traces transmission from al-Fudayl to Bishr to Sarī al-Saqaṭī and al-Junayd, clarifying how each modality survives in later Baghdad sobriety and Malāmatī self-effacement. The contribution is twofold: first, it supplies a granular typology of early Ṣūfī repentance that explains divergent stances toward money, publicity, and power; second, it models how to read early Ṣūfī biography as anthropology of practice, recovering the lived grammar by which “conversion stories” become social programs. In doing so, the article nuances standard narratives of early Ṣūfism, showing that Bishr is not merely al-Fuḍayl’s echo but a creative reframer whose “reverential” path complements—rather than imitates—the awe-driven ethic associated with al-Fuḍayl. Full article

While BioTRIZ is widely employed in biomimetic design to facilitate creative ideation and standardize workflows, accurately formulating domain conflicts and assessing design schemes during critical stages—such as initial concept development and scheme evaluation—remains a significant challenge. To address these issues, this study proposes an advanced BioTRIZ method. Firstly, the theory of technological evolution is integrated into the domain conflict identification stage, resulting in the development of a prompt framework based on patent analysis to guide large language models (LLMs) in verifying the laws of technological evolution (LTE). Building on these insights, domain conflicts encountered throughout the design process are formulated, and inventive principles with heuristic value, alongside standardized biological knowledge, are derived to generate conceptual solutions. Subsequently, a main parameter of value (MPV) model is constructed through mining user review data, and the evaluation of conceptual designs is systematically performed via the integration of orthogonal design and the fuzzy analytic hierarchy process to identify the optimal combination of component solutions. The optimization case study of a floor scrubber, along with the corresponding experimental results, demonstrates the efficacy and advancement of the proposed method. This study aims to reduce the operational difficulty associated with implementing BioTRIZ in product development processes, while simultaneously enhancing its accuracy. Full article

We investigate how generative AI tools function in smart learning by estimating a structural path model that combines the Stimulus–Organism–Response (SOR) framework with Self-Determination Theory (SDT). Using survey data from N = 540 university students and covariance-based SEM, we examine whether perceptions of these tools—usefulness (PU), ease of use (PEU), creative benefit (PCB), and personalization (PP)—align with SDT’s motivational states of perceived autonomy (PA) and perceived competence (PC) and, in turn, relate to creative confidence (CC) and creative engagement (CE). All four perceptions show positive links to PA and PC, with PP exhibiting the largest association with PA. PA precedes PC, indicating a sequential motivational route. At the behavioral level, PC relates more strongly to CC, whereas PA shows a comparatively larger association with CE. In aggregate, the results support integrating SOR with SDT to explain students’ psychological responses to generative AI tools and inform course designs that cultivate autonomy and competence to sustain creative confidence and engagement in smart-learning contexts. Full article

As a typical high-risk accident in mine safety production, roof accidents occur frequently and cause severe harm, posing a major threat to miners’ lives. Through the causal analysis of the occurrence process of roof accidents, this study creatively constructs an accident causation matrix to realize the characteristic description of accident causes, which serves as the data support for the Bayesian network built based on fault tree modeling. Ultimately, a new analysis framework integrating the accident causation matrix and the Bayesian network model is established. In the process of accident analysis, first, based on the 2–4 causation model theory and combined with the association rule algorithm, the key factors of the accident and their internal correlations are obtained, and the accident causation matrix is constructed. Second, the fault tree is transformed into a Bayesian network model, and the accident causation matrix is used for parameter learning and optimization. Finally, two methods-model comparative analysis and real case verification are adopted to prove the advancement and effectiveness of this study. Researching results indicate that the accident causation matrix can effectively characterize accident causation factors, providing precise input data for Bayesian network models and significantly enhancing their reliability. Through the reverse reasoning function of Bayesian networks, dynamic diagnosis of accident causes and identification of key risk factors are achieved, enabling a more dynamic and detailed analysis of accident causes. This offers a scientific basis for coal mining enterprises to formulate preventive measures. Full article

Background: Bullying victimization is a common phenomenon that can affect middle school students’ malevolent creativity. However, the underlying mechanisms between the two remain unclear. This study integrates the social hostility model and the Conservation of Resources theory to further explore the relationship between bullying victimization and malevolent creativity, the mediating roles of trait anger and social mindfulness, and the moderating role of emotion regulation, thereby advancing the research and filling the relevant gaps. Method: Using validated Chinese versions of the Olweus Bullying Scale, Trait Anger Scale, Social Mindfulness Self-Report Scale, malevolent Creativity Behavior Scale, and Emotion Regulation Questionnaire, N = 860 students were surveyed in a cross-sectional design. Results: The results showed that bullying victimization was positively related to malevolent creativity (total effect size β = 0.44), with a direct effect of size β = 0.17 and significant indirect effects via social mindfulness (β = 0.05; 11%), trait anger (β = 0.18; 41%), and the sequential path (β= 0.04; 9%). Emotion regulation moderated the links of social mindfulness and trait anger with malevolent creativity, such that higher emotion regulation strengthened the negative association for social mindfulness and weakened the positive association for trait anger. Implications: These findings suggest that school-based programs targeting emotion regulation and social mindfulness, alongside anger management components, may help mitigate the harmful impact of bullying on malevolent creativity. Full article