As generative artificial intelligence (Gen AI) becomes more integrated into higher education, institutions struggle to communicate clear and effective policies. This multiple‐methods study examines survey and interview data collected with 124 undergraduates and seven faculty members from two U.S. R1 universities regarding their perceptions of institutional AI policies, supportive resources and challenges. Students reported that while classroom‐level policies are recognised, institutional guidelines remain unclear. Similarly, faculty highlighted the implementation challenges they face due to practical constraints and insufficient training. Additional findings show that students aware of AI policies are less likely to use AI for writing and research; disciplinary and gender differences in institutional resources and policy awareness. Faculty interviews revealed themes such as AI use in research and varied colleague attitudes. Although this study is limited by the number of institutions and sample size, it highlights the need for ongoing research to support policy refinement.

ChatGPT has surprised academia with its remarkable abilities but also raised substantial concerns regarding academic integrity and misconduct. Despite the debate, empirical research exploring the issue is limited. The purpose of this study is to bridge this gap by analyzing Twitter data to understand how academia is perceiving ChatGPT. A total of 9733 tweets were collected through Python via Twitter API in three consecutive weeks in May and June 2023; and 3000 most relevant ones were analyzed in Atlas ti. 23. Our findings reveal a generally supportive attitude towards using ChatGPT in academia, but the absence of clear policies and regulations requires attention. Discussions primarily focus on academic integrity, learning effectiveness, and teaching efficiency. Tweets from influencers with over one million followers were analyzed separately. The significance of these findings and the limitations of the study are included.

Psychological stress among college students is significantly higher than that among the general population, and the COVID-19 pandemic has impacted the mental health of many college students. However, relatively little research has focused on Chinese international students’ (CISs) mental health in the USA. The purpose of this study is to identify factors that may affect Chinese international students’ mental health through a systematic review of the literature. We reviewed refereed empirical research articles published during 2010–2021 and explored the factors identified in these articles that affect the mental health status of CISs who are attending US universities. A total of 49 articles (31 quantitative, 15 qualitative, and 3 mixed-methods) that met the inclusion criteria were reviewed and analyzed. Through this review, we identified three main categories of factors: personal, environmental, and behavioral. We further examined specific factors under each category. Results demonstrate 104 personal factors, 68 environmental factors, and 18 behavioral factors that affect CISs’ mental health status. Findings suggest that many factors may trigger CISs’ mental health, but little was known about causal factors, which point to future research on intervention studies to identify causal relationships between variables. Practical implications are discussed.

This study aims to enhance our understanding of the diverse nature of social–emotional development and explore the demographic disparities and intersectionality of social determinants among children, with an emphasis on underserved populations of children in low-resource environments. Young children living in low-income families are exposed to a wide array of social and systemic risks that increase the propensity for poor learning and social–emotional development. Using data from the Head Start Family and Childhood Experiences Survey (FACES, this study focuses on the social–emotional development of a nationally representative sample of young children enrolled in the Head Start program (n = 1921, 50.18% male). Employing a person-centered approach, we assessed teacher-rated social–emotional competence, including approach to learning, social cooperation, aggression, hyperactivity, and anxiety/depression/withdrawal, to classify young children’s social–emotional development. This study identified four distinct social–emotional profiles—Adaptive, Average, Moderate Risk, and High Risk—through latent profile analysis. Furthermore, multinomial regression analysis revealed demographic disparities within each social–emotional profile, and significant intersectionality was found between race/ethnicity, age, and disability status in the social–emotional profiles. This research provides valuable insights for better supporting each child’s unique needs.

Work-related rumination has been shown to affect professional well-being negatively. Like school counselors, other mental health professionals are faced with high emotional demands during their daily workdays; it is crucial to understand the role of work-related rumination within this population. To accomplish this, we conducted a confirmatory factor analysis to examine the psychometric properties of the Work-Related Rumination Questionnaire to determine its fit among mental health professionals and found an acceptable fit. Additionally, we explored the relationship of work-related rumination to work-related stress among 348 mental health professionals. Our findings indicated that work-related rumination correlated with work-related stress levels and that higher affective rumination was significantly associated with higher stress levels. We discuss implications for mental health professionals based on our findings.