With the rapid development of information technology in contemporary times,the blended teaching mode that blends online and offline courses has become an international trend in higher education.Taking blended tourism ...With the rapid development of information technology in contemporary times,the blended teaching mode that blends online and offline courses has become an international trend in higher education.Taking blended tourism management courses at Chongqing Three Gorges University as an example,we explored the impact of such teaching reform on student satisfaction based on the SERVPERF model.Empirical analysis of 179 valid questionnaires revealed that five elements of the reform,namely,reliability,assurance,valuableness,responsiveness,and empathy,have a significant positive impact on students’learning satisfaction.Specifically,in the context of blended courses,factors such as a stable and reliable teaching environment,comprehensively guaranteed educational conditions,teaching content that highly aligns with students’demands and value expectations,prompt responses to students’needs and feedback,and empathetic consideration of students’perspectives are critical for enhancing student satisfaction.Based on these conclusions,we propose several strategies and methods for improving the effectiveness of blended teaching in the hope of propelling its continuous improvement and optimization,thus further elevating the quality of higher education.展开更多
经典的高效全局优化(efficient global optimization,EGO)算法搜寻得到的最优解,受代理模型精度及过早收敛等问题的制约,其精度仍存在进一步改善的空间。围绕最优解精度进一步改善的问题,研究了面向精确最优解的EGO算法。该算法基于Krig...经典的高效全局优化(efficient global optimization,EGO)算法搜寻得到的最优解,受代理模型精度及过早收敛等问题的制约,其精度仍存在进一步改善的空间。围绕最优解精度进一步改善的问题,研究了面向精确最优解的EGO算法。该算法基于Kriging代理模型,涉及的最优加点策略采用考虑Kriging信任的改善期望函数法,使得优化迭代后期更偏向于局部寻优。此外,文中还考虑了与成熟的拟牛顿法和Powell法等局部优化方法协同的算法,以提高最优解的搜寻精度。选用了若干典型的检验函数,对优化算法的具体实施过程进行了模拟与分析,发现改进后的优化算法能以相对较少的额外函数评估次数得到比经典的EGO算法更精确的全局最优解,从而验证了算法的有效性和准确性。最后,把发展的算法应用到具体的跨音速翼型优化问题,算例表明,改进后的EGO算法翼型阻力较原EGO算法减小了1.11%,显示了其工程实用性。展开更多
基金funded by the 2021 Chongqing Three Gorges University Higher Education Reform Project“Research on the Improvement of Teaching Quality in Blended Courses for Tourism Management”(JGZC2146)the Science and Technology Research Plan Project of Chongqing Municipal Education Commission“Research on the Effectiveness and Intrinsic Mechanisms of Virtual Spokespersons in Tourism Marketing in the Context of Digital Economy”(KJQN202301240)the Project of Chengdu-Chongqing Research Center for Coordinated Development of Education and Economic Society“Research on the Implementation Effect of the‘Double Reduction’Policy in Ethnic Regions in Sichuan and Chongqing:Based on the Parents’Perspective”(CYJXF23022).
文摘With the rapid development of information technology in contemporary times,the blended teaching mode that blends online and offline courses has become an international trend in higher education.Taking blended tourism management courses at Chongqing Three Gorges University as an example,we explored the impact of such teaching reform on student satisfaction based on the SERVPERF model.Empirical analysis of 179 valid questionnaires revealed that five elements of the reform,namely,reliability,assurance,valuableness,responsiveness,and empathy,have a significant positive impact on students’learning satisfaction.Specifically,in the context of blended courses,factors such as a stable and reliable teaching environment,comprehensively guaranteed educational conditions,teaching content that highly aligns with students’demands and value expectations,prompt responses to students’needs and feedback,and empathetic consideration of students’perspectives are critical for enhancing student satisfaction.Based on these conclusions,we propose several strategies and methods for improving the effectiveness of blended teaching in the hope of propelling its continuous improvement and optimization,thus further elevating the quality of higher education.
文摘经典的高效全局优化(efficient global optimization,EGO)算法搜寻得到的最优解,受代理模型精度及过早收敛等问题的制约,其精度仍存在进一步改善的空间。围绕最优解精度进一步改善的问题,研究了面向精确最优解的EGO算法。该算法基于Kriging代理模型,涉及的最优加点策略采用考虑Kriging信任的改善期望函数法,使得优化迭代后期更偏向于局部寻优。此外,文中还考虑了与成熟的拟牛顿法和Powell法等局部优化方法协同的算法,以提高最优解的搜寻精度。选用了若干典型的检验函数,对优化算法的具体实施过程进行了模拟与分析,发现改进后的优化算法能以相对较少的额外函数评估次数得到比经典的EGO算法更精确的全局最优解,从而验证了算法的有效性和准确性。最后,把发展的算法应用到具体的跨音速翼型优化问题,算例表明,改进后的EGO算法翼型阻力较原EGO算法减小了1.11%,显示了其工程实用性。
