Zhou Ying

In the education context, The Motivational Strategies for Learning Questionnaire is extensively used in assessing self-regulated learning strategies. However, more research is needed to address whether it is applicable for distance education. The exploratory and confirmatory factor analysis were used to test the Chinese version of the Motivated Strategies for Learning Questionnaire part-B for distance learning using two samples totalling 385 participants. This paper substantiates MSLQ-B-DL's criterion-related, convergent, and factorial validity, as well as its internal consistency, in China. Specifically, the concurrent validity of the MSLQ-B-DL was shown from three aspects: the negative correlation of MSLQ-B-DL with trait procrastination; the positive correlation of MSLQ-B-DL with self-control; and the positive correlation of MSLQ-B-DL with instrumental help-seeking and the former's negative correlation with help-seeking avoidance and executive help-seeking. Finally, this study highlights the MSLQ-B-DL's validity and reliability in evaluating the learning strategies in adult distance education in China.

The outbreak of the COVID-19 epidemic has promoted the popularity of online learning, but has also exposed some problems, such as a lack of interaction, resulting in loneliness. Against this background, students' attitudes toward peer interaction may have become even more important. In order to explore the impact of attitude toward peer interaction on students' mindset including online learning motivation and critical thinking practice that could affect their problem-solving self-efficacy during the COVID-19 pandemic, we developed and administered a questionnaire, receiving 1,596 valid responses. The reliability and validity of the questionnaire were re-tested, and structural equation modeling was applied. It was found that attitude toward peer interaction could positively predict middle school students' online learning motivation and critical thinking. Learning motivation and critical thinking also positively supported problem-solving self-efficacy. It is expected that the results of this study can be a reference for teachers to adopt student-centered online learning in problem solving courses.

Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network security knowledge, which is then used to analyze and optimize the processing of hybrid network security situation information using cloud computing technology and co-filtering technology. Knowledge and information about the security situation of a hybrid network has been analyzed using cloud computing strategy. The simulation results show that a cyber security crash occurs in window 20, after which the protection index drops to window 500. The increase in the security index of 500 windows is consistent with the effectiveness of the concept of this document method, indicating that this document method can sense changes in the network security situation. Starting from the first attacked window, the defense index began to decrease. In order to simulate the added network defense, the network security events in the 295th time window were reduced in the original data, and the defense index increased significantly in the corresponding time period, which is consistent with the method perception results, which further verifies the effectiveness and reliability of this method on the network security event perception. This method provides high-precision knowledge of network security situations and improves the security and stability of cloud-based networks.

Interactive Whiteboard has recently been used to replace the TWB, with many of its features being observed to help teachers in educational activities. This is based on effectively and efficiently increasing the teacher-student interaction. Therefore, this study aims to analyze the determinants of Behavioral Intention and the use of interactive whiteboards by K-12 teachers, in remote and rural Chinese areas. The Modified-Unified Theory of Acceptance and Use of Technology 2 model was used in this analysis, as a learning medium to deliver the subject matter to students. The sample and population were also the teachers in the Guangxi Zhuang Autonomous Region, China, where 171 voluntary respondents participated in this study. Furthermore, the obtained data were processed using a Structural Equation Model approach, through the Smart-PLS software. The results showed that Habit and Hedonic Motivation had a significant influence on the Behavioral Intention of teachers, toward the utilization of IWB in remote and rural areas. Besides this, Facilitating Conditions and BI also had a significant positive effect on Usage Behavior. Based on these results, important information was provided to school principals, local governments, and teachers for education quality improvement, regarding the patterns of increasing IWB utilization in remote and rural areas.