Qing Liu

The COVID-19 pandemic caused widespread disruption as governments took actions to limit the spread of the virus. Measures such as physical distancing and lockdowns changed living conditions, leading to challenges such as social isolation and reduced connectedness. This study explores COVID-19’s impact on adolescents’ well-being, emphasising family social capital, which refers to supportive adult-child relationships that foster well-being and enhance remote learning. Quantitative data was collected through an online survey from August 2022 to August 2023, involving 4008 students and 3511 parents. Semi-structured interviews with six students and their parents (either the mother or the father) provided in-depth insights into the perceived role of family social capital in shaping adolescents’ well-being during quarantine. Quantitative data revealed that parental education level significantly influenced adolescents’ self-reported well-being and resilience, and family income influenced parents’ perceptions of their children’s well-being. Qualitative data highlighted the importance of strong family bonds, effective parent-child relationships, and robust family support in mitigating the adverse effects of prolonged home quarantine. The research also discovered the role of adolescents’ agency in building social capital through web-based communities. The study contributes to understanding Chinese adolescents’ well-being during the COVID-19 pandemic, providing implications for supporting their well-being in the post-pandemic era.

The workshop’s design was a masterstroke of intellectual engagement. WesternWestern scholars were tasked with defending Eastern valuesValues, while their EasternEastern counterparts were charged with championing WesternWestern values. This intriguing setup, I believe, was inspired by the desire to foster a deeper understanding and appreciation of different cultural perspectives. It seemed to resonate with the Confucian teaching of “emulating the virtuousVirtuous” (见贤思齐), encouraging participants to recognize the strengths in others’ cultures while critically examining the limitations of their own.

The topic for this session is ritual, civilityCivility, and harmony for good governance. Arguably, one of the most distinctive features of Confucianism as a cultural, philosophical, and political tradition is that it takes ritual really seriously. And in the Confucian tradition, ritual is important, especially in relation to civility and harmonyHarmony. Moreover, ritual as we understand it is one of the key valuesValues that define and undergird the ideas and practicesPractice not only of the Chinese society but also of Indian and Japanese societies.

Advances in artificial intelligence have raised a basic question about human intelligence: Is human reasoning best emulated by applying task‐specific knowledge acquired from a wealth of prior experience, or is it based on the domain‐general manipulation and comparison of mental representations? We address this question for the case of visual analogical reasoning. Using realistic images of familiar three‐dimensional objects (cars and their parts), we systematically manipulated viewpoints, part relations, and entity properties in visual analogy problems. We compared human performance to that of two recent deep learning models (Siamese Network and Relation Network) that were directly trained to solve these problems and to apply their task‐specific knowledge to analogical reasoning. We also developed a new model using part‐based comparison (PCM) by applying a domain‐general mapping procedure to learned representations of cars and their component parts. Across four‐term analogies (Experiment 1) and open‐ended analogies (Experiment 2), the domain‐general PCM model, but not the task‐specific deep learning models, generated performance similar in key aspects to that of human reasoners. These findings provide evidence that human‐like analogical reasoning is unlikely to be achieved by applying deep learning with big data to a specific type of analogy problem. Rather, humans do (and machines might) achieve analogical reasoning by learning representations that encode structural information useful for multiple tasks, coupled with efficient computation of relational similarity.

The author intends to investigate the role of social distancing laws in the new normal as well as the effectiveness of forced shift to media online learning. This research indicates that student involvement had a moderating influence during the epidemic. This study is based on social learning theory, which endeavors to emulate the behavior, perceptions, and emotions of other individuals. The data were obtained from various Chinese universities. We gathered data utilizing the stratified sample approach as well as Google Form. A total of 256 students enrolled in a variety of programs at Chinese universities completed a questionnaire for this investigation. The direct, mediating, and moderating effects of the variables were evaluated using partial least square structural equation modeling in this study, using the Smart-PLS software 3.0. According to the findings, forced shift to media online learning acts as a mediator between the lack of social interaction, perceived harm, perception of maintaining social distancing, and the law, and the effectiveness of media online learning has a significant effect on the effectiveness of media online learning. In addition, student engagement appears to be a moderator between the forced shift to media online learning and its effectiveness. A future study might concentrate on gaining a deeper understanding of the numerous online engagement-promoting behaviors. Teachers must go above and above to provide themes that enable pupils to connect while learning. Instructors and educational institutions will benefit from the research since it will allow them to define methods for boosting social interaction in online learning and analyze methods for enhancing the efficacy of media in online learning.