In the absence of an ambitious federal climate strategy, a new study shows state-led action can make a significant difference in reducing carbon emissions and addressing climate change. The study also found that while state-led action is only slightly more expensive than a coordinated national effort, it would likely result in the adoption of different decarbonization technologies.

School-to-school collaboration has the potential to improve student learning outcomes, especially in underperforming schools. A recent study explores the impact of Shanghai’s Strong School Project, which pairs high- and low-achieving schools to boost academic achievement. It examines how peer relationships and principal leadership contribute to significant gains in subjects like Math and Chinese. By fostering collaboration, this approach highlights the power of partnership in reshaping education and enhancing student performance across diverse schools.

A new study from the University of Oxford, published in Public Health, shows that European people in the lowest income deciles are much more likely to feel lonely than those in the highest income deciles, despite no difference in how often they socialise. Furthermore, both poverty and loneliness were strongly associated with higher scores on a defensive symptom cluster characterised by elevated levels of pain, fatigue and low mood.

The study also showed that the symptom-reducing effects of social connection were strongest for people living in poverty. These findings have important implications for social, economic, and health policy, suggesting that strong social relationships may serve as important buffers against some of the health consequences of poverty.

A new study from the University of Oxford, published in Public Health, shows that European people in the lowest income deciles are much more likely to feel lonely than those in the highest income deciles, despite no difference in how often they socialise. Furthermore, both poverty and loneliness were strongly associated with higher scores on a defensive symptom cluster characterised by elevated levels of pain, fatigue and low mood.

The study also showed that the symptom-reducing effects of social connection were strongest for people living in poverty. These findings have important implications for social, economic, and health policy, suggesting that strong social relationships may serve as important buffers against some of the health consequences of poverty.

Encouraging people in North America and Sub-Saharan Africa to adopt a low-carbon lifestyle could help to cut global household emissions of planet-warming carbon dioxide by up to two-fifths, a new study reveals.

As AI technology continues to evolve in the digital era, developing AI literacy among college students has become a crucial educational priority. This study aims to establish a scientific AI literacy evaluation system and to empirically assess the AI literacy levels of undergraduate students at Wuhan University, with the findings providing data support and theoretical reference for future AI education policy-making and curriculum design in higher education institutions. In response to the demands of AI education and university talent cultivation objectives, this study develops an AI literacy evaluation system for college students, based on the KSAVE (knowledge, skill, attitude, value, and ethics) model and the UNESCO AI competency framework. The system includes 4 level-1 indicators (AI attitude, AI knowledge, AI capability, and AI ethics), 10 level-2 indicators, and 25 level-3 indicators. The Delphi method was used to determine indicator content, while the analytic hierarchy process was employed to calculate the weights for each level of indicators. Through large-scale questionnaire surveys and statistical analysis, the study empirically measured the AI literacy levels of 1,651 undergraduate students at Wuhan University and analyzed variations in AI literacy across factors including gender, academic year, academic discipline, and technical background. The results demonstrate that the constructed AI literacy evaluation system is scientifically sound and highly applicable, providing a comprehensive and objective measure of students’ AI literacy levels. Furthermore, notable differences were observed in AI literacy levels across different dimensions among Wuhan University undergraduates, with variables such as academic discipline, technical background, and participation in digital intelligence education programs significantly influencing students’ AI literacy, particularly in knowledge and capability dimensions.