The present study aimed to explore latent profiles of adolescent parentification and school refusal, and to examine the association of trait emotional intelligence in profile membership. 1669 adolescents completed self-report measures assessing parentification, school refusal, and trait emotional intelligence. Latent Profile Analysis (LPA) was conducted to identify distinct subgroups based on patterns of school refusal and parentification, followed by multivariable logistic regression analyses to examine the associations of trait emotional intelligence. (1) LPA identified three latent profiles: Non-School Refusal and Non-Parentification (60
With the growing integration of artificial intelligence (AI) into education, students’ dependence on AI for learning has become increasingly prevalent, attracting substantial academic interest in the effects of AI dependence on creativity. Considering resource dependence theory, this study distinguishes between AI functional dependence (AFD) and AI existential dependence (AED), exploring their differential effects on student creativity while investigating the mediating role of ambidextrous learning and the moderating role of AI self-efficacy. Through a questionnaire survey and data analysis involving 851 university students, the study demonstrates that AFD positively influences student creativity, whereas AED exerts a negative influence. Ambidextrous learning mediates the relationship between AI dependence and student creativity. AI self-efficacy significantly mitigates the negative effect of AED on ambidextrous learning. However, its moderating effect on the relationship between AFD and ambidextrous learning is not significant. These findings enrich the theoretical understanding of the effects of AI dependence and offer novel insights for the effective improvement of student creativity.
As digital technologies increasingly shape learning environments in higher education, understanding how institutional support is associated with students’ digital citizenship has become an important research issue. Drawing on Self-Determination Theory (SDT), this study examined the relationships between perceived school support (PSS) and digital citizenship literacy (DCL) among 600 university students in China. The measurement model demonstrated satisfactory reliability and validity. Results showed that PSS was positively associated with DCL, with competence need satisfaction serving as the only significant mediator. The non-significant mediating effects of autonomy and relatedness should be interpreted cautiously, as they may reflect the domain-specific nature of DCL, the operationalization of basic psychological needs, or contextual characteristics of Chinese higher education rather than their theoretical irrelevance. Theoretically, this study extends the application of SDT to digital citizenship by highlighting the differentiated roles of the three basic psychological needs. Practically, the findings suggest that supportive digital learning environments may strengthen students’ digital competence while encouraging reflective engagement and responsible digital participation. These implications are consistent with SDG 4’s emphasis on educational quality and inclusive learning environments. 1. Perceived school support is positively associated with digital citizenship literacy. 2. Competence need satisfaction mediates this association. 3. Autonomy and relatedness show no significant mediating effects. 4. Informal school support may complement formal digital citizenship education. 5. Evidence is drawn from 600 Chinese university students.
While identity construction is recognized as an integral part of higher education, particularly for interdisciplinary students who need to negotiate their identities between two markedly different disciplines, relevant research remains limited. Moreover, existing research on interdisciplinary learners’ identity tends to regard participants as a unified collective and gives insufficient attention to variations across grade levels. Using Q methodology and follow-up interviews, this study compares identity profiles of first- to fourth-year students in a Chinese “English + Engineering” dual degree program, revealing between-group differences and key influences on their identity construction. Findings show that first- and second-year students exhibit dual English-Engineering and engineering-oriented identities. Third-year students hold three profiles, including engineering-centric career preparers, unsettled identity navigators, and a small group of English-centered learners. Fourth-year students are predominantly engineering-dominant, with a smaller subset of unsettled navigators. Personal interest, curriculum fragmentation, career planning, and family background emerge as primary drivers. These findings also enable this study to propose some practical implications for curriculum design and student support within interdisciplinary programs.
With Generative Artificial Intelligence (GAI) deeply integrated into education, teachers serve as the core agents bridging technology and pedagogy. Teachers’ AI literacy (TAIL) is pivotal in facilitating teaching innovation, cultivating innovative talent, and driving educational transformation. Yet, existing research remains inconclusive regarding which technology-related psychological factors underlie the systematic association between TAIL and Teachers’ Teaching Innovation Behaviors (TTIB). Based on the 3P model, this study constructed a multiple mediation model and employed structural equation modeling (SEM) to analyze questionnaire data from 528 primary and secondary school teachers in China. The results revealed that TAIL was significantly and positively associated with TTIB, GAI-related Technology Self-Efficacy (GAI-TSE), GAI-induced Technology Stress (GAI-TS), and GAI-driven Cognitive Reconstruction (GAI-CR). Additionally, the relationship between TAIL and TTIB was mediated not only by GAI-TSE and GAI-CR, but also by two serial mediation pathways: GAI-TSE→GAI-CR and GAI-TS→GAI-CR. These findings clarify the multifaceted psychological pathways linking TAIL and TTIB, highlighting the prominent role of GAI-TSE within the model. This study not only deepens our understanding of the hierarchical processing logic intrinsic to the 3P model, but also provides robust empirical evidence for the design and delivery of targeted GAI training programs and teacher support systems. Reveals dual pathways of teachers' AI literacy affecting teaching innovation (China). Breaks 3P model's parallelism flaw; highlights Emotional-Cognitive pathway effect. Deepens differentiated cognition of psych mediation roles. Proposes 3D strategies for synergizing teachers' AI literacy and teaching innovation.
