The current study investigates how faculty members in Chinese universities are navigating the integration of generative artificial intelligence tools into second language curricula, focusing on specific pedagogical and institutional challenges. Using an exploratory sequential mixed-method approach (N = 776), we examined how faculty perceive and address key areas of concern: curriculum adaptation, assessment transformation, student engagement, ethical concerns, professional development needs, and pedagogical shifts. Unlike prior studies, which often generalize faculty experiences, this study uniquely captures nuanced faculty strategies and gaps in readiness across a large-scale context in Chinese higher education. Results indicated that faculty members exhibited significant usage of generative artificial intelligence tools both for personal and professional purposes. They also used generative artificial intelligence tools for formative assessment practices, with limited application in summative assessments. Results indicated faculty faced Generative AI tool usage challenges like curriculum adaptation, assessment transformation, student engagement with generative artificial intelligence tools, ethical concerns, professional development, and pedagogical shifts. The findings also demonstrated that faculty members were struggling to address these challenges. Furthermore, outcomes indicated that professional development and ethical concerns directly, indirectly, positively and significantly contribute to helping faculty to enhance student engagement and pedagogical shifts in their teaching practices. Additionally, curriculum adaptation and assessment transformation have also mediated these relationships. These findings contribute novel insights into how professional development can support effective GenAI integration. Implications are offered for faculty development programs, curriculum design policies, and institutional governance in the era of AI-enhanced education.

Based on social exchange theory, social psychology theories, and despotic leadership theory, this study explored the impact of petty tyranny on employee turnover intentions. Specifically, the authors examined the mediating effect of toxic workplace environments through emotional exhaustion on this relationship among academicians. The authors surveyed 421 employees using a five-point Likert scale across six universities in Lahore, Pakistan and employed a time-lag research design. Partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) analyses, including performance comparisons of various algorithms, were used to test the relationships among the variables. The analysis results of the study suggested that petty tyranny does not significantly and directly contribute to employee turnover intentions; however, this relationship is positively and significantly mediated by toxic workplace environments and emotional exhaustion. The results indicated that toxic workplace environments and emotional exhaustion also have a direct effect on employee turnover intentions. A serial full mediation was found between petty tyranny and turnover intentions, mediated through a toxic workplace environment and emotional exhaustion. Similarly, results from the performance comparison of various algorithms reveal trade-offs between precision, recall, and processing time, with ZeroR and Stacking REP Tree emerging as the most effective in terms of overall model accuracy. This study contributes to the literature by examining petty tyranny, workplace environment, and emotional exhaustion, highlighting the need to address tyrannical behavior to improve employee retention in academic organizations. Our study offers valuable practical implications, emphasizing addressing these issues to reduce turnover in academic organizations. Our study also provides recommendations for future research directions.

The study examines the relationships among active bystander behavior (ABSB), innovative work behavior (IWB), team cohesion (TC), and sustainable work performance (SWP) among university faculty. Based on Social Exchange Theory (SET) and Organizational Citizenship Theory (OCB), our research examined the direct and indirect relationships between ABSB and both IWB and SWP, with TC serving as a mediator. A sample of 219 university faculty completed a validated self-report survey that assessed ABSB, TC, IWB, and SWP. Partial Least Squares Structural Equation Modeling (PLS-SEM), Artificial Neural Networks (ANN), and fuzzy-set Qualitative Comparative Analysis (fsQCA) were applied to test, validate, and compare the hypothesized relationships across linear, non-linear, and configurational perspectives. The PLS-SEM results demonstrated that TC significantly mediated the relationship between ABSB and both SWP (β = 0.366, p < 0.05) and IWB (β = 0.409, p < 0.05). The fsQCA analysis identified several configurations associated with higher SWP, with the combination ABSB ∗ IWB ∗ TC showing the highest consistency (0.925). Complementarily, the ANN model exhibited superior predictive accuracy (R² = 0.74; MSE = 0.25), confirming the presence of nonlinear and interactive dynamics between ABSB, TC, and IWB. The integrated findings revealed that TC consistently mediated the link between ABSB and both IWB and SWP across all analyses. PLS-SEM confirmed significant mediation, fsQCA identified ABSB, IWB, and TC as a sufficient configuration, and ANN verified a nonlinear interactive relationship. These convergent findings offer strategic insights for academic leadership and policymakers.

Understanding how psychological attributes are associated with academic behavior is fundamental to educational psychology. This exploratory study investigated the relationships between emotional intelligence (EI), relational instructor warmth (RIW), and a newly developed measure of metacognitive effort regulation (MER) among nursing students in Pakistan and China. While prior research has examined these constructs separately, their interrelationships across different institutional contexts remain underexplored. A questionnaire survey containing 36 statements was completed by 581 nursing students in Pakistan and China, with responses collected on a 5-point Likert scale. The relationships were analyzed via partial least-squares structural equation modeling. The results indicate that emotional intelligence is directly and indirectly related to metacognitive effort regulation. Specifically, all four aspects of emotional intelligence (self-awareness, self-regulation, motivation, and social skills) were positively associated with metacognitive effort regulation. These associations are preliminary and require confirmation with validated measures. Relational instructor warmth was also positively correlated with metacognitive effort regulation, suggesting its potential association with higher metacognitive engagement and effort regulation in an academic context. Relational instructor warmth played a partial mediating role in the relationship between emotional intelligence and metacognitive effort regulation. Multigroup analysis revealed one significant difference between the two participating institutions: the path from self-regulation to relational instructor warmth was significantly stronger among students at the participating Pakistani institution than at the participating Chinese institution (p = 0.004). This institutional difference suggests that context-specific educational interventions may be more effective than one-size-fits-all approaches. These findings suggest that students with higher levels of emotional intelligence and relational instructor warmth may report better metacognitive regulation, which is associated with higher metacognitive effort regulation. As an exploratory study, the findings are preliminary and hypothesis-generating; they require confirmation using validated measures and longitudinal designs. The paper concludes by discussing the implications of these results and offers suggestions for future research.

Background: Based on the Transactional Model of Stress and Coping and Cognitive Overload Theory, this study explores the association of technostress creators with cognitive overload in academia. Specifically, the authors examined the mediating role of emotional exhaustion on this relationship. Method: The authors surveyed higher education students from universities in China. We employed a time-lag survey method to test the relationships between the variables used in the research model, utilizing partial least squares structural equation modeling (PLS-SEM) through SmartPLS. Results: The findings indicate that technostress creators, modeled as a higher-order construct reflected by five lower-order dimensions (techno-complexity, techno-overload, techno-invasion, techno-insecurity, and techno-uncertainty), significantly and positively correlate with cognitive overload and emotional exhaustion. Emotional exhaustion is also significantly and positively associated with cognitive overload. Furthermore, emotional exhaustion was identified as a significant mediator, though this mediating role should be interpreted as data-inferred and requires confirmation through longitudinal or experimental designs. These findings advance the application of the Transactional Model of Stress and Coping and Cognitive Load Theory in digital learning environments. This study offers two key theoretical contributions. First, it extends technostress research by identifying cognitive overload as positively associated with technostress creators among higher education students. Second, it reveals emotional exhaustion as a novel mediating mechanism explaining how technostress creators correlate with cognitive overload. Policymakers should design targeted interventions such as counseling services and stress management workshops to mitigate technostress, while academic institutions and teachers can implement strategies to help students manage technology-related academic stress. Conclusions: These findings advance the application of the Transactional Model of Stress and Coping and Cognitive Load Theory in digital learning environments. This study offers two key theoretical contributions. First, it extends technostress research by identifying cognitive overload as positively associated with technostress creators among higher education students. Second, it reveals emotional exhaustion as a novel mediating mechanism explaining how technostress creators correlate with cognitive overload. Policymakers should design targeted interventions such as counseling services and stress management workshops to mitigate technostress, while academic institutions and teachers can implement strategies to help students manage technology-related academic stress.