Engagement plays an essential role in the learning process. Recognition of learning engagement in the classroom helps us understand the student’s learning state and optimize the teaching and study processes. Traditional recognition methods such as self-report and teacher observation are time-consuming and obtrusive to satisfy the needs of large-scale classrooms. With the development of big data analysis and artificial intelligence, applying intelligent methods such as deep learning to recognize learning engagement has become the research hotspot in education. In this paper, based on non-invasive classroom videos, first, a multi-cues classroom learning engagement database was constructed. Then, we introduced the power IoU loss function to You Only Look Once version 5 (YOLOv5) to detect the students and obtained a precision of 95.4%. Finally, we designed a bimodal learning engagement recognition method based on ResNet50 and CoAtNet. Our proposed bimodal learning engagement method obtained an accuracy of 93.94% using the KNN classifier. The experimental results confirmed that the proposed method outperforms most state-of-the-art techniques.
At present, China regards supply chain innovation and application as a new national strategy, which leads to a large demand for applied supply chain professionals. In order to provide useful references for applied universities that have already set up the supply chain management (SCM) program and promote the healthy development of Chinaʼs application-oriented SCM for undergraduates, this paper discussed the necessity and feasibility of setting up the SCM program in Chinese universities. In addition, it analyzes the current situation of SCM programs from three aspects involving approval, type of universities, and issues of application-oriented undergraduate. Based on practical experience in specialty development, in this paper, specific measures were shown from three dimensions: requirements of knowledge, ability, and quality, curriculum setting, and teaching material design.
Numerous barriers, including distance, language, culture, scale, and unfamiliar business practices obstruct cross-border trade between SME buyers and sellers. Alibaba's cross-border electronic commerce (e-commerce) platform connects businesses, generating leads and quotations quicker than ever with request for quotation, or RFQ (request for quotation). The commercialization of RFQ market intensifies the competition between suppliers, which requests traditional enterprises to response more quickly and efficiently to improve their business. The purpose of this paper is to provide a case study of small OEM (Original Equipment Manufacturer) company using electronic commerce as part of their business strategy in Alibaba.com, and how to improve its business on the Alibaba.com platform by RFQ. The themes are clearly not unique to one company, but a part of a greater ecosystem that includes cross-border trade not only between SMEs, but also involves a multitude of companies and customers around the world.Keywords: cross-border e-commerce, RFQ, OEM IntroductionIn Asia, there is a dramatic change fueled by a very rapid increase in Internet penetration, particularly in China. The numbers of Internet users grew from 20 million to 460 million only within a decade. China's rapid growth as a manufacturing center since opening up 30-plus years ago spawned countless small businesses and factories, transforming the country into the world's manufacturing center. With the rapid growth of the Internet and e-commerce, more and more companies do their business online. During the past decade, China's overall trade increased rapidly with e-commerce making an ever-growing contribution. China's total cross-border e-commerce trade, including exports and imports, grew 28.6% in 2015, to US$776 billion from US$603 billion in 2014. About 90% of the 2015 volume was in business-to-business (B2B) transactions, the remainder in business-to-consumer (B2C) transactions. With the development of One Belt, One Road, China will be the biggest market because of its population size and the early adoption of e-commerce. Yet, to be the world's largest in cross-border e-commerce requires overseas transactions, markets, and business partners. As China's market grows, so will other markets.Tremendous growth stories for sure, but small and medium enterprises increasingly found themselves lacking sufficient scale in the trading process on one hand, and lacking the leverage based on a good credit rating to obtain financing to grow their business on the other hand. Besides these challenge, SMEs lacked the capabilities and expertise to manage each stage of the supply chain-sourcing, customs clearance, inspection, taxation, foreign exchange, insurance, trade finance, risk management and so on. A business process solution was needed too. In terms of e-commerce development, websites were just a little more than information display platforms at beginning. Now they are highly sophisticated interfaces that act as a doorway to attract business and service providers. Aliba...
Began with Computer-Assisted Language Learning (CALL) in the 1960s and extended to the widespread use of various Mobile-Assisted Language Learning (MALL) tools in education, language learning has embraced technology early on, achieved noticeable results, and found extensive practical use. However, due to the challenges in accessing user data from various language learning platforms, the measurement and assessment of language-related variables continue to rely on self-reporting and peer evaluations. This reliance hampers researchers to observe language learning from alternative perspectives, especially when it comes to analyzing raw behavioral data. To explore potential correlations between different learning modes, this study analyzed 2 million samples from Chinese students using an English language learning application. The study quantified the effectiveness of English vocabulary learning using the economic concept of return on investment (ROI) as an evaluation metric and identified four distinct learning strategies. It observed significant differences in learning ROI among learners who adopted different strategies. Based on this analysis, we recommend the following suggestions for improving language learning ROI: when memorizing new vocabulary, investing excessive amounts of time may be counterproductive; a more effective approach is to "eat less but more often," which means arranging review sessions at a reasonable pace and shortening the interval between each review.
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