The Communist Party of China's 19th National Congress underlined the necessity of speeding the development of a manufacturing powerhouse and advanced manufacturing sector by supporting the deep integration of the Internet, big data, artificial intelligence, and the real economy. This study employed principal component analysis to extract the prominent risk factors from questionnaire data in order to manage the risks connected with the Internet strategic transformation of manufacturing firms. To confirm the major risk factors, a structural equation modeling was created using Amos-24 software. The findings revealed that risk factors of Internet strategic transformation in manufacturing businesses are mostly expressed in equipment flexibility risks, organizational versatility risks, smart technology risks, Internet technology risks, flexible management risks, and financing management risks. The paper offers useful theoretical and practical insights into the risks of China's manufacturing businesses' Internet strategic transformation. The findings can assist manufacturing firms in better identifying and managing these risks, supporting their smooth transition to the Internet economy.
Internet , Manufacturing Industry , Manufacturing Industry/organization & administration , China , Humans , Commerce , Surveys and Questionnaires , Risk Factors , Principal Component Analysis
The goal of critical thinking for students is to help them learn how to think critically and systematically so they can solve problems and make informed decisions. It aids students in developing their capacity for independent thought, allowing them to generate their own conclusions and base those decisions on facts and evidence. Therefore, one of the key goals of this study was to explore the factors affecting critical thinking of English as foreign language (EFL) learners. This article used social cognitive theory (SCT) to investigate how personal and cognitive factors affect EFL learners' critical thinking. Data from 305 Chinese EFL learners were collected online, and structural equation modeling (SEM) was used to evaluate the data. The results showed that metacognitive learning strategies (MLS) were positively related to critical thinking and that self-efficacy, self-oriented learning perfectionism, and learner anxiety were significantly related to MLS. Moreover, MLS mediated the link between self-efficacy, self-oriented learning perfectionism, learner anxiety, and critical thinking. The findings further indicated that learner proactivity moderated the association between MLS and critical thinking. By applying social cognitive theory to examine the variables influencing EFL learners' critical thinking, this study adds uniqueness. It does this by emphasizing the moderating influence of learner proactivity and the mediating function of metacognitive learning strategies. The findings of the research have significant ramifications for educators since they emphasize how vital it is to support metacognitive strategies for learning in order to improve EFL learners' critical thinking abilities. Additionally, to create an atmosphere that is favorable for the development of critical thinking skills in EFL education, policymakers should think about implementing support systems and interventions that focus on learner anxiety, learner proactivity, and self-efficacy.
For manufacturing enterprises to successfully enter the "Industry 4.0" era and establish advantages in the new wave of the Industrial Revolution, they must use Internet thinking to transform manufacturing enterprises and promote the in-depth integration of informatization and industrialization under the premise of managing and controlling risks, to achieve transformation and upgrading. Research on and management of the risks of manufacturing enterprises' Internet strategic transformation directly affects the success or failure of enterprises' transformation. This study constructed a risk evaluation model for a manufacturing enterprise's Internet strategic transformation based on the back propagation (BP) artificial neural network and conducted a case study on one enterprise.
Social media has always been described as the channel through which knowledge is transmitted between communities, students, and learners. This social media has been utilized by university students in a way to encourage collaborative learning and social interaction. This study explores the use of social media in the process of collaborative learning among university students in China using a survey method, a total of 583 students from different universities were surveyed in this study. Through this investigation, different factors enhancing collaborative learning among university students in the context of using social media are going to be examined. Structural equation modeling (SEM) and hierarchical regression were used to analyze the suggested hypothesis. Results show that perceived benefit, active learning, and interaction with students are significantly related to social media collaboration. However, perceived ease of use and perceived usefulness have an insignificant effect on social media collaborative learning. Additionally, students' academic self-efficacy significantly moderates the relationship between social media collaboration and learning performance. The implication and limitations of the study are also discussed in the last section.
Most studies have shown that reading is an important source of incidental vocabulary learning, and repeated reading may have a positive effect on learning gains. However, the study of incidental vocabulary learning through listening is still limited, and the immediate and long-term effects on different vocabulary knowledge dimensions are unclear. Furthermore, no empirical studies have been conducted to investigate the association between learning gains and preexisting vocabulary knowledge in listening. This article examines the effects of listening to English songs on unintentional vocabulary learning and vocabulary retention through three different vocabulary knowledge dimensions: word recognition, meaning association, and grammar identification. A total of 114 Chinese college students participated in the study, and they were given vocabulary evaluations at different times based on three separate components of vocabulary knowledge. The effects of repeated listening (one, three, and five times) and learners' prior vocabulary knowledge were also investigated. According to the findings, listening to songs can improve vocabulary knowledge, particularly in the area of word recognition, which can be retained 4 weeks later. Furthermore, the effect of listening three times (with exposure frequencies ranging from three to nine) was superior than listening one or five times, which provides teachers and learners with guidance for teaching or learning vocabulary more effectively. Finally, for low, intermediate, and high-level learners, there was an immediate and positive effect on the dimensions of word recognition and meaning connection after listening, and this knowledge is likely to be preserved 4 weeks later.
