Developing students' self-regulation skills within and outside academic modules

COVID-I9 has accelerated the adoption of online learning, and the authors' university (like many others) is settling into a blended learning approach. In this chapter, the authors share their experiences in improving students' self-regulation of online learning. The first learning experience for most students at the Singapore Institute of Technology is in online, self-paced courses in Mathematics, Physics, and Chemistry. Beyond content, these courses provide students opportunities to embrace the 'norm' of self-paced, self-directed online learning and to expose and encourage them to develop self-regulation skills. Students are required to self-assess and refer to different learning resources independently, based on their identified needs. The authors have also developed another intervention based on Zimmerman's self-regulated learning model, guiding students to plan, monitor, and adjust their learning plans and develop self-efficacy through this process. For students to transfer these skills into their actual studies, the authors provide individual coaching sessions to facilitate students' implementation. © 2023, IGI Global.

Effects of the COVID-19 lockdown in Hubei, China: cessation of incense burning reduces regional landscape fire

Both anthropogenic and climatic factors are important determinants of landscape fire. Because the two groups of factors are intertwined and often act simultaneously, dissecting their effects on landscape fire is challenging. We used the COVID-19 lockdown event in Hubei, in which all immediate influences of anthropogenic factors were effectively removed, to quantify the effects of anthropogenic factors on landscape fire occurrence. We hypothesized that outdoor incense burning is the main causal factor of landscape fire. To test the hypothesis, we used random forest algorithm to model fire occurrence, including fire frequency, total area burned, and area of forest burned, for the lockdown period. We then estimated the differences between historical, simulated, and observed values of landscape fire and used the differences to represent the effects of anthropogenic activities on landscape fire. Our results showed that during the lockdown, landscape fire frequency was reduced by 77%, total area burned by 80%, and area of forest burned by 63%. By month, fire frequency decreased the most in April (85%), followed by February (80%), coinciding with the Qingming and Spring Festivals of 2020. The cessation of outdoor incense burning during the festival season was likely to be the most important factor that decreased fire occurrence, confirming our hypothesis about the causal relationship between outdoor incense-burning and landscape fire. Thus, educational programs encouraging people to stop outdoor incense burning during the festival season could reduce the occurrence of landscape fire.

Big Data Mining and Analysis of Hot Issues in International Education-Based on K-means algorithm of cluster analysis

in the era of big data, international education has accumulated a lot of relevant data, which can produce various research values. The Corona Virus Disease 2019 (COVID-19) seriously affects the development of international education. This paper starts with the hot spots of international education and international higher education. Moreover, based on xinhuanet.com database and CSSCI database, and through K-means algorithm in data mining clustering analysis algorithms, the Cite Space visual software is used to make keywords analysis, emotional color analysis, and centrality analysis, thus getting the hot issues in international education and the frontier focus. Furthermore, combined with COVID-19 spread globally, these problems are analyzed, the future direction and development of international education are discussed, and reasonable and scientific suggestions and thinking are proposed. © 2020 IEEE.