Abstract:Classroom teaching and students' learning have been widely concerned. To support the implementation of effective classroom teaching, this study examines the current state of instructional practices and student learning by surveying 541 college students. The questionnaire is divided into three main aspects, in which students are asked to assess their learning experience in college: motivations for choosing their major, their learning status, classroom performance, and feedback from teachers. Research results show that the motivation for choosing undergraduate majors positively affects students' learning. However, if teachers do not continue to provide the necessary guidance and high-quality courses to students, they will lose interest in their majors. For freshmen, teachers should be more concerned about their learning status, because they have the lowest adaptability to university learning. In addition, we also find that dumb classroom teaching, performing classroom teaching, still exists, and classroom teaching efficiency is low. Further analysis indicates that the teaching effectiveness of teachers, including teacher-student communication, positive motivation from teachers to students, and the content of their teaching, has a direct effect on students' learning. The low efficiency of classroom teaching is primarily attributed to an underdeveloped and ineffective classroom ecological environment. In the concluding section, this paper proposes a set of targeted strategies to rebuild and enhance the classroom teaching ecology, aiming to foster more effective teaching and meaningful student engagement.
Abstract:In this study, shielding performance and pressure drop of the honeycomb, square and circular ventilation holes in a microwave furnace, which is operated at 2450 MHz, were evaluated. The effect of hole diameter, hole to hole distance and hole depth to the shielding and pressure drop were considered as variables. A simulation model prepared on Comsol Multiphysics v.5.2a and the results compared with the theoretical equations. The pressure drop and shielding performance decreases and increases with increasing hole diameter and hole to hole distance, respectively. Increasing hole depth causes a reduction in pressure drop but it enhances the shielding performance.
Abstract:Artificial Intelligence Generated Content (AIGC) is becoming a valuable tool ineducation. It supports personalized, interactive, and scalable learning. However, little is known about how preschool teachers continue using AIGC in their dailypractice. This study explores the key factors that influence their sustainedintention to use AIGC technologies. It integrates three theoretical models—Technology Acceptance Model (TAM), Expectation ConfirmationModel (ECM), and Flow Theory—into a unified framework. Data were collectedthrough a questionnaire survey of preschool teachers in China. The results wereanalyzed using both Partial Least Squares Structural Equation Modeling(PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA). Findings show that confirmation and perceived usefulness are strong predictors of continuous use. In contrast, perceived ease of use plays a smaller role. The fsQCA results also reveal three distinct combinations of conditions that lead to high usage intention. These findings provide new insights into teacher technology adoption and offer practical guidance for promoting sustainable use of AIGC in early childhood education, especially in developing regions.
Abstract:Despite longstanding theoretical and practical interest in subjective well-being (SWB), its structural composition remains debated. Life satisfaction, along with positive and negative affect, is widely recognized as a core component of SWB; however, the nature of their interrelationships within a unified construct is still unclear. This study examined the factor structure of SWB using data from a sample of Ukrainian university students (N = 1111; age range = 18–26 years; 59.0% women). Participants completed the Ukrainian versions of the Satisfaction with Life Scale (SWLS) and the Scale of Positive and Negative Experiences (SPANE). Confirmatory factor analysis (CFA), bifactor CFA, exploratory structural equation modeling (ESEM), and bifactor ESEM were employed to evaluate competing theoretical models. Model selection was based on Akaike’s Information Criterion (AIC) weights, balancing model fit and parsimony. While four models demonstrated adequate fit, the bifactor ESEM model showed the best overall performance. This model accounted for cross-loadings and identified a strong general SWB factor along with three specific components. Measurement invariance across gender was confirmed at the configural, metric, and scalar levels. Findings support the bifactor ESEM as a comprehensive and robust framework for conceptualizing the multidimensional structure of subjective well-being in emerging adults.
Abstract:This study developed an indicator system of instructional leadership by novice principals to facilitate the assessment of their leadership capabilities. This study employed a survey-based approach consisting of three studies to examine the reliability and validity of the proposed system and explored the perceived importance and actual performance of these indicators. The statistical techniques included expert review, item analysis, exploratory factor analysis, internal consistency reliability analysis, confirmatory factor analysis, cross-validation, measurement invariance analysis, and IPA. The proposed indicator system, consisting of 5 dimensions and 24 specific indicators, demonstrates good reliability and validity for assessing the overall, dimensional, and specific indicators of instructional leadership performance. Highly rated dimensions were enhancing school curriculum and instructional quality as well as creating supportive teaching and learning environments. Developing a vision for teaching and setting goals and tasks was also considered important; however, performance was relatively low.
Abstract:Crime poses a significant challenge to the prosperity and growth of nations. Various factors, including poverty, deficiencies in the legal system, unstable economic conditions, and insufficient technological capabilities for crime analysis and detection, contribute to its emergence. This work proposes a novel framework for crime identification and detection utilizing generative and deep learning models. Initially, we extract latent features from an available dataset using a combination of generative model, Deep Learning (DL) and Machine Learning (ML), techniques, including a Variational Auto-Encoder (VAE), transformers, Convolutional Neural Networks (CNN), and Principal Component Analysis (PCA), followed by K-means clustering. We then evaluate the effectiveness of this clustering approach using renowned classifiers, such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), and Naive Bayes (NB). As a result, the framework, which utilizes VAE for feature extraction and combines it with RF as the classifier, achieves the highest accuracy of 0.9993. The strength of the proposed framework lies in its unsupervised learning approach, which attains significant information from data without relying on labeled datasets. This data-driven methodology adeptly leverages generative and deep learning models for feature extraction, subsequently employing these features for crime detection. Furthermore, we analyze individual attributes in latent spaces and apply classifiers, with the VAE demonstrating exciting performance, achieving an accuracy of 0.999.
Abstract:Vestigial organs serve as one of evidence for the theory of evolution, gradually atrophying and disappearing when they no longer contribute to an organism’s survival. This principle can also be applied to human consciousness and intelligence, as the brain is a product of an intricate and ancient evolutionary process. While the concept of cognitive atrophy from an evolutionary perspective is less well-defined than physical atrophy, evidence suggests that mental functions deteriorate when they become obsolete. Environmental shifts, lifestyle changes, and evolving social structures all play a vital role in shaping this dynamic process. Organisms tend to attract stability, minimizing conflict and competition tendency that also influences cognitive decline. In this context, the rise of artificial intelligence (AI) may accelerate the atrophy of human cognition. As societies grow increasingly reliant on technology, certain cognitive abilities essential in earlier human history may diminish due to reduced necessity. This paper argues that the rapid development of AI will facilitate mental and cognitive ease, ultimately leading to a decline in human knowledge in the near future.
Abstract:This study seeks to explore the intricate relationship between national culture and leadership styles within higher education institutions (HEIs). It also examines the pivotal role that leaders play in navigating workforce diversity within this context. Conducting in-depth interviews with 35 participants from seven different nationalities across six universities in North Cyprus, from August 2020 to June 2021, we employed a descriptive thematic analysis to extract relevant themes from the qualitative data. Our findings reveal that transactional and transformational leadership styles predominantly shape the leadership landscape in these HEIs. Moreover, we aimed to validate the applicability of transformational leadership within managerial frameworks in multicultural university settings, particularly in the context of effectively managing workforce diversity. The results illuminate how national culture significantly influences leadership styles, with a notable emphasis on transactional leadership approaches. The study contributes to the understanding of cross-cultural leadership dynamics in higher education, highlighting the importance of cultural considerations in leadership effectiveness and diversity management.
Abstract:This study examines the transformation of Chuanjiang Haozi from a traditional labor song to an intangible cultural heritage, tracing its evolution across various performance fields. Initially, it functioned primarily in labor, enhancing teamworkandproviding spiritual solace during strenuous tasks. With its recognition as a cultural heritage in 2006, it has adapted to modern settings, diversifying its performancecontexts. The stage field fosters innovation by reinterpreting the songfor contemporary audiences, incorporating modern artistic elements while retainingits cultural essence. The educational field plays a crucial role in passing down the art form, emphasizing technical skills and cultural understanding, thereby ensuringits intergenerational transmission. The study reveals how Chuanjiang Haozi thrives inits original stage and educational fields through qualitative research methods, includingparticipant observation and semi-structured interviews. These fields support its preservation and evolution, enabling the song to maintain its relevance in modernsociety while preserving its cultural identity. Its adaptability across multiple contexts demonstrates the dynamic nature of cultural heritage in a rapidly changing world.
Abstract:Social networking sites have been frequently analyzed in psychological studies due to a great number of their users and the influence they have on people’s social life. Instagram is among the most popular image-based networking sites. The main aim of this research is to show problematic Instagram use (PIU) as a mediator in the relationship between self-esteem and life satisfaction. The study was carried out on a group of N = 912 people aged from 19 to 30. The following tools were used: Rosenberg Self-esteem Scale, Satisfaction with Family Life Scale, Problematic Instagram Use Questionnaire, and Satisfaction with Life Scale. It was found that there is a negative correlation between self-esteem and problematic Instagram use. The relation between PIU and life satisfaction was shown as well as the mediating impact of PIU on the relationship between selfesteem and life satisfaction after an average level of family satisfaction was taken into account.