Search Results (1,141)

Increased competition in the higher education market is a key reason for higher education institutions (HEIs) to adopt marketing strategies to remain competitive. Branding is one of the strategies frequently used in this context. This study examines changes in university brand value perception from the student perspective. It analyses internal changes, i.e., those made within the HEI, as well as changes in the external environment, and their impact on university brand value perception over a five-year period. The research used a mixed-methods approach to capture both aspects of the phenomenon. The qualitative research included interviews with four members of a private HEI management board, while the quantitative research was based on a questionnaire designed to identify and evaluate elements of Aaker’s model of brand equity. The research results show that although all dimensions display a slight decrease, the difference in perceived brand value is not statistically significant. Despite the fact that the overall grading shows no statistically significant differences and that the total grading is above average, these results indicate that the efforts made in the last five years to increase the quality of different dimensions relevant to better perception of HEI brand value were not recognized by students. Full article

This study examines how individuals experience AI-generated natural landscapes and whether visually simulated, non-immersive environments activate perceptual, emotional, and restorative mechanisms typically associated with real or immersive nature. Grounded in a critical realist epistemology, AI-generated nature is conceptualized not as a substitute for natural environments, but as a distinct experiential domain in which the transferability of established environmental and restoration theories can be empirically tested. A total of 1021 participants evaluated AI-generated landscapes using a 36-item instrument derived from environmental psychology, digital media studies, and restoration research. Exploratory factor analysis identified six experiential dimensions—perceived naturalness, sense of presence, affective attunement, emotional resonance, restorative quality, and cognitive restoration—which were examined using confirmatory factor analysis and structural equation modeling. While the measurement model showed excellent fit, structural relationships among constructs were consistently weak, indicating systematic non-support of theoretically expected pathways. The findings show that AI-generated landscapes can elicit salient perceptual, affective, and cognitive responses that remain largely unintegrated, limiting their capacity to produce coherent restorative outcomes. The study delineates boundary conditions for applying environmental and restoration theories to visually simulated AI landscapes and supports positioning synthetic nature as a complementary element in sustainable tourism experience design and digital environmental communication. Full article

This paper presents the findings of a study on computer science teachers’ views regarding the reform of the computer science curriculum and its implementation in Greek model and experimental lower secondary schools (called Gymnasiums). Research data were collected through interviews with 19 computer science teachers who implemented the new curriculum in 12 model or experimental junior high schools. The results showed that the teachers acknowledged the important role of the computer science curriculum, which is perceived as a tool guiding their instruction. They have also understood and adopted, to a large extent, many elements of the instructional framework proposed by the new curriculum: (a) student-centred teaching approaches; (b) learning activities that promote students’ active participation, inquiry, and collaborative learning; (c) focus on the expected students’ learning outcomes related to developing a range of computational competences such as digital skills, computational thinking, problem-solving skills, creativity, and collaboration; and (d) students’ assessment is constructively aligned with the anticipated learning outcomes, including the learning activities implemented as well as their digital-computational creations. Full article

Village landscapes within an 80 km radius of Lubumbashi (south-eastern Democratic Republic of the Congo) are undergoing rapid spatial transformation driven by subsistence agriculture, charcoal production, and mining activities. This study analyzes how these transformations are spatially perceived and organized across five village territories of the Lubumbashi Charcoal Production Basin using an adapted version of Kevin Lynch’s perceptual model. Landscape elements were independently identified by trained cartographic observers and by local community members. A comparison of the resulting maps yields a Sørensen similarity index ranging between 70% and 75% across villages, indicating strong convergence in spatial interpretation despite differences in expertise. Among the perceptual components, districts and landmarks account for nearly half of all identified elements and comprise the most perceptible anthropogenic disturbances. Spatial analysis shows that areas perceived as negatively impacted represent between 40% and 79% of total village surfaces. Deforestation associated with post-cultivation fallow dominates in Makisemu (47.6%) and Texas (64.4%), while woodland degradation linked to charcoal production is particularly pronounced in Mwawa (39.0%) and Luisha (25.1%). Mining-related disturbances, including soil and water alteration, are especially evident in Nsela (24.6%). These findings demonstrate that Lynch’s framework, although originally developed for urban systems, can effectively structure perception in diffuse rural woodland environments when methodologically adapted. Perception-based cartography therefore provides a robust complementary tool to biophysical monitoring for understanding the spatial footprint of anthropogenic pressures at the village scale and informing ecosystem restoration strategies. Full article

People’s perception of the comfort level of street landscape elements is influenced by the built environment, and improving the quality of street landscape environment is of great significance for promoting the sustainable development of cities. This study focuses on 12 sample streets in Zibo City. After obtaining panoramic images of the area through the OSM platform, the FCN framework was used for semantic segmentation. A combination of subjective and objective methods was adopted, and eye tracking indicators were collected using the D-Lab wearable eye tracker. At the same time, a questionnaire quantitative analysis was conducted to systematically investigate the impact mechanism of the combination characteristics of street elements on comfort perception preferences. Research has found that there is a significant correlation between the perceived comfort preference of street scenes and GVI, and the increase in total gaze time towards green elements also shows a significant improvement in perceived comfort preference. After entering the street interface, observers show a high degree of priority attention to street view elements such as building facades and advertising facilities. As the gaze time on the sky (a street view element) increases, people’s perceived comfort evaluation shows a downward trend. There are significant differences in the structural characteristics of different streets, and their impact on improving comfort also varies to some extent. This study links the comfort perception of street landscape elements with sustainable urban development planning. By reasonably allocating landscape elements such as green visibility, basic roads, building interfaces, and signage facilities, it provides certain reference suggestions for the sustainable development of urban street space and human-centered urban construction. Full article

This study examines how visual features and green space morphology jointly shape restorative perception in dog-friendly urban green spaces using a data-driven analytical framework. A self-constructed dataset integrating street-view imagery, landscape element composition, and morphological metrics was developed to quantify visual entropy, visual richness, and spatial structure. Ten dimensions of visual perception were modeled using an XGBoost framework optimized with a genetic algorithm, achieving high predictive performance (R² = 0.827–0.989). Streetscape analysis revealed relatively stable visual entropy but pronounced heterogeneity in visual richness, reflecting variability in color, form, and spatial layering. Element-level decomposition showed the visual dominance of natural components, particularly trees, sky, and grass. Piecewise linear regression further identified threshold-dependent and dimension-specific effects of green space proportion, fragmentation, patch size, connectivity, aggregation, and shape complexity. Moderate fragmentation and aggregation enhanced perceived complexity and stimulation, whereas excessive shape complexity reduced most restorative responses. Full article

Critical thinking (CT) is essential for navigating the complex socio-scientific issues in contemporary biomedicine. These issues cross disciplinary boundaries and involve multiple societal stakeholders. Interdisciplinary and transdisciplinary (ITD) education therefore provides a valuable context for developing CT by confronting students with diverse forms of knowledge and prompting reflection on their disciplinary assumptions. In this study, boundary crossing is used as a pedagogical framework, with a focus on identification (understanding alternative perspectives) and reflection (examining one’s own assumptions). We examine how such ITD education can foster CT by enhancing students’ appreciation of disciplinary and societal viewpoints. Data from a pre- and post-course assignment were analyzed using a convergent mixed-methods approach. Students ranked the relevance and effectiveness of sessions engaging with different perspectives and identified educational design elements that contributed to broadening their biomedical outlook. Findings indicate shifts in how students perceived the relevance of different perspectives. Particularly, appreciation of the legal perspective increased. Sessions were considered most effective when involving interaction with perspective owners, interactive learning methods, and clear instructional design. The results suggest that boundary-crossing pedagogies can support CT in higher education by engaging students in reflective engagement with different disciplinary and societal perspectives. Full article

This study aims to explore perceptions among students at Jordanian universities regarding “wasta,” defined as the use of social relations or kinship ties to pressure faculty members into granting them undeserved academic privileges, and to examine the impact of these perceptions on their academic behaviors and attitudes toward their institution. The study uses Travis Hirschi’s Social Bond Theory, which posits that the strength of social bonds is determined by four key elements: attachment, commitment, involvement, and belief. The researchers designed a survey using a proportionally stratified random sample of 748 students from two universities in the south of Jordan. The data were collected using a questionnaire whose validity and reliability were deemed suitable for analysis. The findings reveal a varying degree of erosion in social bonds as follows: while students expressed a rejection of wasta on ethical grounds, the involvement of others in such behavior to gain unearned academic advantages undermined their sense of belonging to the university. Participants also indicated that their peers’ reliance on wasta devalued their individual efforts and weakened trust in the fairness of the educational institution. Furthermore, students’ motivation to participate in campus activities was lower when they perceived that opportunities were granted based on connections rather than merit, while statistical significance was observed only for the involvement dimension in favor of the public university. Last, some students saw wasta as a practical resource in the absence of institutional justice, even if they recognized the harm it causes to academic integrity and the value of university credentials. The findings highlight the importance of addressing wasta within academic institutions by strengthening transparent decision making and academic integrity safeguards to enhance fairness and strengthen trust. Full article

The rapid spread of generative artificial intelligence (AI) in higher education creates both opportunities for innovation and challenges for academic integrity, ethical use, and students’ critical thinking, particularly in scientific writing. This study examines whether a synchronous live coaching format can support students in developing reflective and responsible AI practices. A mixed-methods cross-sectional evaluation was conducted at a German distance-learning university with a strong focus on health and social sciences. An online survey was administered to 168 students who participated in voluntary live coaching sessions on “AI in Scientific Writing”. Quantitative items assessed perceived competence gains, ethical awareness, and confidence in handling AI tools, while open-ended questions captured qualitative feedback on the format’s strengths and improvement needs. Students reported that the coaching enhanced their understanding of responsible AI use and scientific integrity and valued the opportunity for open discussion, peer interaction, and the supportive attitude of instructors. Reflective and dialogic elements were perceived as particularly beneficial. Overall, the findings suggest that synchronous live coaching can contribute to fostering ethical awareness and higher-order thinking in AI-supported academic work, especially when it integrates structured input with dialogue, reflection, and peer learning. Full article

Background/Objectives: Identification of tools to minimize opioid-related harms is critical in the U.S. The purpose of this study was to better understand community responder and healthcare provider perceptions and preferences regarding the design and function of a potential new opioid sensor device (OSD). Methods: Adults aged ≥ 18 years employed as community responders or healthcare providers in Alabama were recruited via email to participate in an anonymous online cross-sectional survey informed by the Unified Theory of Acceptance and Use of Technology (UTAUT). Primary outcomes were assessed via multiple-choice and 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree) and included the following topics: (1) past OSD utilization (4 items); (2) perceived importance of OSD design elements (15 items); (3) OSD function and cost preferences (3 items); and (4) UTAUT measures including perceived usefulness of OSDs (3 items), ease of use (4 items), social factors (4 items), resources (4 items), concerns (3 items), and intentions (3 items). Differences in UTAUT measures across professions were assessed via Mann–Whitney U tests, and predictors of OSD utilization intention were analyzed via multiple linear regression. Results: Respondents (N = 145) included pharmacists (40.0%), nurses (23.4%), physicians (14.5%), behavioral health (4.8%), social work (4.8%), and law enforcement (0.7%). Availability in hospital emergency departments was rated as the most important device element (mean [SD] score: 6.66 [0.80]), followed by sensitivity and specificity of the test (6.42 [0.98]), rapid detection time (6.42 [0.88]), ability to detect opioids in a broad range of substance (6.42 [0.93]), and availability in law enforcement offices (6.33 [1.08]). A 2–5 min detection time was rated as reasonable by 32.6% of respondents, with 53.0% preferring to pay <USD 15 per test. There were no statistically significant differences in UTAUT scale scores across professions. Perceived usefulness (β = 0.493; p < 0.001), social acceptance (β = 0.281; p = 0.023), and resource availability (β = 0.708; p = 0.002) were positive predictors and perceived ease of use was a negative predictor (β = −0.472; p = 0.007) of intention to use an OSD. Conclusions: Newly developed OSDs should consider prioritizing accessibility in hospital emergency departments and law enforcement offices, ability to detect a broad range of opioids, detection time between 2 and 5 min, and cost less than USD 15 per test. Future research may explore perspectives from a more diverse sample across multiple states and different professional roles. Full article

Reflective writing is a core component of teacher education, especially during practical internships. However, providing high-quality feedback on reflections is resource-intensive. This study examines descriptively observable associations between an early dual-feedback approach combining basic (automated) and elaborate (human-generated) feedback and structural features of preservice physics teachers’ reflective writing, prior to the widespread adoption of generative AI in education. Using an exploratory, non-equivalent, non-concurrent cohort design, we analyzed participant-level aggregates of written reflections from a non-intervention cohort (N = 22) and an intervention cohort (N = 32), applying a validated reflection-supporting model to assess structural composition and discursive elements of reflective writing. In the intervention, basic feedback was generated by a previously validated BERT-based machine learning model focusing on structural reflection elements, while elaborate feedback addressed content-related and pedagogical depth. In this study, the automated model was employed as an analytic measurement instrument drawing on validation work demonstrating its transferability across comparable reflection contexts. Quantitative analyses did not reveal systematic longitudinal growth in indicators of reflective writing quality in either cohort. Across comparable measurement points, descriptively different structural reflection profiles were observed between cohorts, without permitting causal or developmental interpretations. Feedback acceptance was high overall, although structural AI feedback was perceived as less personalized and less useful. These findings highlight the descriptive value of early, non-generative AI-based approaches for scalable structural diagnostics of reflective writing, while underscoring the continued importance of human-generated, content-focused feedback. The study establishes an empirical baseline for evaluating contemporary generative AI–based feedback systems in teacher education. Full article

Background: Research on spatial imagery as perceived by humans is an important frontier for deepening the theoretical understanding of Tourism Destination Image and promoting sustainable urban development. Significance: This study, from the perspective of tourists, explores the correlation mechanism between the cognitive image and affective image of urban space. This is of great significance for enhancing the overall spatial quality of cities, promoting the integration of the man–land relationship, and driving the sustainable development of tourism. Method: In this study, we took Harbin as the case site, collected 89,375 reviews and 23,561 review images of 488 scenic spots on the Mafengwo and Ctrip platforms, and constructed a multimodal dataset. We classified the image scenes with the help of the Places365-CNN model. We then extracted text emotional features by utilizing the SnowNLP deep learning algorithm. We constructed a map of the spatial influence mechanism acting on cognitive image and emotion through MGWR. Results: The experimental results showed that in the level of Pleasure, the five indicators NHS, HPA, RPA, PDS and WRV had significant spatial correlations with urban sentiment. In the level of Arousal, the three indicators PD, MaSD and WRV showed significant spatial characteristics. Conclusions: This study reveals the influence mechanism of urban spatial perception elements on tourists’ emotions. It not only deepens the understanding of the Tourism Destination Image theory, but also provides a practical path based on the optimization of perception scenarios for the improvement of urban space, which has important implications for regional sustainable development. Full article

(1) Background: Virtual environments (VEs) significantly influence human emotions through various elements such as lighting, color, and terrain. While the effects of lighting and color on emotions within VEs have been extensively studied, the impact of the terrain remains underexplored. This paper addresses this gap by investigating the correlation between terrain characteristics in VEs and users’ emotional states. (2) Methods: We conducted a user study in which participants were exposed to various 3D terrains and used the Self-Assessment Manikin (SAM) to rate their emotional responses (valence, arousal, and dominance). Building on these insights, we propose MoodScape, an automated framework for emotion-informed terrain generation that significantly reduces the need for extensive expertise and manual effort. In the current implementation, continuous SAM valence–arousal targets are discretised into four quadrant-based affect/terrain classes, and this discrete class label conditions DH-CVAE-GAN terrain synthesis. MoodScape designs a generative adversarial network (GAN) architecture called DH-CVAE-GAN, which integrates a dual-head conditional variational autoencoder as the generator alongside a discriminator network to ensure effective and realistic terrain generation. The DH-CVAE-GAN is trained on a satellite-derived digital elevation model (DEM) dataset, which helps the generated terrains reflect realistic geographic patterns. (3) Results: Quantitative and qualitative evaluations on our study sample suggest that MoodScape can generate terrains whose perceived affective tone is broadly consistent with the specified affect-class inputs, indicating potential applications in gaming and exploratory therapeutic Virtual Reality, while formal clinical efficacy remains in future work. Full article

In the context of accelerating urbanization, university students face mounting academic stress and increasingly severe psychological health challenges. University blue-green spaces are critical environments for fostering restorative experiences. They highlight the urgent need for targeted strategies to enhance their restorative potential. This study used three universities in Guangzhou as case studies, based on image collection and deep learning-based semantic segmentation methods, and employed the Perceived Restorativeness Scale (PRS) and Restoration Outcome Scale (ROS) to explore the hypothesized pathways and threshold characteristics through which visual elements of blue-green spaces are associated with university students’ psychological restoration within everyday campus environments. The results indicate: (1) the restorative effects of different space types follow a clear gradient: waterfront spaces > planar vegetation spaces > linear vegetation spaces > point vegetation spaces; (2) perceived restorativeness acts as a key mediator between visual elements and psychological restoration. The mediating pathways vary across space types. Waterfront spaces show polarized effects. Planar vegetation spaces rely on a dual pathway of being away and compatibility, supplemented by a secondary role of fascination. Linear vegetation spaces exhibit complex pathway patterns in which multidimensional positive support coexists with both positive and negative influences; (3) several visual elements display nonlinear threshold effects. This study deepens the understanding of the “environment–perception–psychology” pathway in the context of sustainable campus environments. It also proposes a three-level optimization framework (macro–meso–micro) that provides empirical references for evidence-informed planning and design of university blue-green spaces, with potential implications for sustainable campus environments and student well-being. Full article

This article scientifically addresses the challenges related to data security and stakeholder privacy faced by companies operating in the European Union. These challenges stem largely from the global digital transformation, within which the European Union imposes regulations governing data protection and stakeholder privacy. The digital transformation in the European Union focuses on the integration of people and technology, sustainable development, and the resilience of management systems, which are the pillars of Industry 5.0. From a practical perspective, the paper examines the current level of awareness among employees of the enterprise in Poland regarding data and privacy risk management in today’s economic environment. The paper presents both a theoretical review and, in the empirical section, the results of primary research. The study was conducted in Poland on a sample of 556 enterprises from various economic sectors. The paper begins with Introduction. Background presents a literature review conducted on the conditions for enterprise functioning in the evolving paradigm of Industry 5.0, as well as the fundamental legal requirements regarding data security and stakeholder privacy across business activities. Materials and Methods presents the research methods employed to assess how respondents perceive threats to data security and stakeholder privacy. Results summarizes the research findings. In Discussion, both practical business implications are addressed, and the role of technology and organizational procedures in responsible data and privacy management is highlighted. Furthermore, the importance of creating ethical cyber–physical environments as an element of sustainable enterprise transformation is emphasized. Finally, Conclusions presents the results and key findings regarding the level of awareness among employees of Polish enterprises about data security and stakeholder privacy in the context of digital transformation. Full article