With the growing recognition and acceptance of virtual online education, more and more educational institutions are switching from offline business to online business. However, users differ in their willingness to use virtual online education platforms. This paper explores the factors affecting user willingness to use such platforms, laying a theoretical basis for promoting virtual online education. The main findings are as follows: college students are positive and in favor of extracurricular learning; the students’ demand for online learning contents varies with gender, grade, and major; the long-term willingness to use depends on perceived usefulness, satisfaction, and perceived switching cost, of which the last factor is the key contributor to increasing user resistance; the long-term willingness to use online education platforms is influenced by perceived usefulness, expected confirmation, content quality, service quality, system quality, satisfaction, and perceived switching cost, etc.

To satisfy the demand of virtual simulation (VS) teaching system for storage capacity and computing power, it is of great significance to probe deep into the VS system oriented to cloud service (CS). This paper designs a CS-based VS teaching system, drawing on the relevant results on distributed VS system, the formalization of VS system architecture, and the semantic organizability of VS system. Firstly, the functional requirements of the CS-based VS teaching system were analyzed, and decomposed into three layers, namely, goal, function type, and function name. Then, a dynamic model of CS-based VS teaching system was constructed, whose simulation accuracy and precision were verified through experiments. The experimental results demonstrate the excellent simulation performance of the proposed system. The research findings provide reference for applying CS system design in other fields.

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Establishing and optimizing an integrated central heating information monitoring and energy conservation system can not only help reduce the waste of resources, but also allow us to identify and solve the instability and safety problems in the heating process, and thus this system is of certain research value. Existing automated heating equipment fail to truly monitor and regulate heating due to various reasons like the lack of comprehensive parameter measurement and serious hydraulic imbalance of the system. To this end, this paper studies the design and implementation of an integrated central heating information monitoring system for smart cities. First, the big data of central heating temperature monitoring in smart cities was reconstructed, and then three different central heating regulation modes were introduced. The experimental results verified the effectiveness of the proposed algorithm. With an example of central heating monitoring shown, the energy efficiency analysis results regarding the energy conservation optimization of the system were given.