Study on the Influencing Factors of Online Learning and Its Operation Mechanism among Chinese College Students during the COVID-19 Pandemic-An Empirical Analysis Based on a Mixed Method.

Online learning has gradually become a mainstream teaching method to replace traditional classroom teaching during the COVID-19 pandemic. However, there are some issues such as the lack of theoretical guidance on online learning, and the influencing factors of online learning effect are not well proven. On this basis, this study aimed to construct and test a theoretical model of online learning influencing factors among college students through a mixed-method approach in China to further explore the influencing factors of online learning and the relationship between these influencing factors. First, 130 college students were interviewed from May 2021 to November 2021, and the collected data were coded to a theoretical model through grounded theory. Second, we tested and verified the theoretical model through the analysis of survey data of 225 college students from January 2022 to July 2022. Lastly, the results indicate that the learning expectation influences the learning result through learning quality or learning interaction and their combined effects. These findings can help educators around the world gain insight into the process of online learning and improve the quality of online learning during the COVID-19 pandemic.

Risk-Averse Two-Stage Stochastic Minimum Cost Consensus Models with Asymmetric Adjustment Cost.

In the process of reaching consensus, it is necessary to coordinate different views to form a general group opinion. However, there are many uncertain factors in this process, which has brought different degrees of influence in group decision-making. Besides, these uncertain elements bring the risk of loss to the whole process of consensus building. Currently available models not account for these two aspects. To deal with these issues, three different modeling methods for constructing the two-stage mean-risk stochastic minimum cost consensus models (MCCMs) with asymmetric adjustment cost are investigated. Due to the complexity of the resulting models, the L-shaped algorithm is applied to achieve an optimal solution. In addition, a numerical example of a peer-to-peer online lending platform demonstrated the utility of the proposed modeling approach. To verify the result obtained by the L-shaped algorithm, it is compared with the CPLEX solver. Moreover, the comparison results show the accuracy and efficiency of the given method. Sensitivity analyses are undertaken to assess the impact of risk on results. And in the presence of asymmetric cost, the comparisons between the new proposed risk-averse MCCMs and the two-stage stochastic MCCMs and robust consensus models are also given.

Experience in Neurosurgery During the Prevalence of COVID-19.

In order to summarize the experience of neurosurgery in The Third People's Hospital of Hubei Province after the outbreak of COVID-19 in 2019, 28 patients were admitted from January 5, 2020 to February 17, 2020. A series of department formulates and constant improvements were made, including elective operation cancellation, altered conventional outpatient service into online outpatient service, strict control of inter department consultation prevention and entering the department, improvements in operation and treatment processes, and strict ward management. As a result, 1 patient with hypertensive cerebral hemorrhage and deep vein thrombosis of the right lower extremity died suddenly due to pulmonary embolism during anticoagulation treatment. Two patients with deep coma gave up treatment and died. No patient was confirmed to be infected with COVID-19 in hospital. One doctor had a low fever and cough in January, and CT showed a small nodule in the lower left lung. After 2 weeks isolation and oral anti-infective drugs, the chest nodule disappeared. One nurse was isolated as a close contact with infected parents. One nurse was confirmed to be infected with COVID-19 in a mild symptom. She was discharged after being cured in the infected department. In conclusion, measures like sufficient theoretical training and protection upgrading for medical staff, continuous improvement on the understanding of COVID-19 characteristics and transmission routes, formulation of strict department management system, monitoring of patients and their families, could effectively deal with the epidemic situation in the neurosurgery department.