Notice of Retraction: Research and Practice on Training Teaching Model in Chinese Higher Undergraduate Education of Computer Science

Author(s):  
Huadong Wang ◽  
Haitao Li
2013 ◽  
Vol 273 ◽  
pp. 18-21
Author(s):  
Bing Zhong

To counter the current situation that undergraduate course teaching separates from the real enterprise producing, and the terrible capacity for work in the undergraduates trained by university, the paper is to explore the "Case-run through type" Teaching Model of Machinery Manufacturing. The model depends on a certain mechanical product, according to the production task to decompose and build a practice teaching system, then to design practice teaching content by the production technology process and sequence. By use of the model, the students can well understand the theoretical knowledge. And it further can help students stimulate the learning interest. Therefore, the students' operation skills and comprehensive ability were greatly improved. In the meantime, the teaching abilities of teachers were also improved.


2010 ◽  
Vol 33 ◽  
pp. 571-574 ◽  
Author(s):  
C.M. Liu ◽  
Zu Lin Wang ◽  
Ji Li Chen

This paper utilizes the method of synthetic analysis to summarize the characteristics and models of China’s cooperative education, which shows the distinctive research and practice of China’s Co-op according to 113 thesis and 27 reports presented on Summit of China’s Cooperative Education in 2009. Co-op (short for "cooperative education") in graduate education is particular, diversified in undergraduate education and perfect in vocational college. The reform and development of CIAR (short for cooperation of industry-academy-research) becomes much more prosperous. Finally we make the following conclusion: Co-op in China will develop from “three cooperation” to “four cooperation”, which is the cooperation in education, school-running, employment and mutual development.


2016 ◽  
Vol 15 (1) ◽  
pp. 59-63
Author(s):  
Morgan Stuart

Abstract Sports informatics and computer science in sport are perhaps the most exciting and fast-moving disciplines across all of sports science. The tremendous parallel growth in digital technology, non-invasive sensor devices, computer vision and machine learning have empowered sports analytics in ways perhaps never seen before. This growth provides great challenges for new entrants and seasoned veterans of sports analytics alike. Keeping pace with new technological innovations requires a thorough and systematic understanding of many diverse topics from computer programming, to database design, machine learning algorithms and sensor technology. Nevertheless, as quickly as the state of the art technology changes, the foundation skills and knowledge about computer science in sport are lasting. Furthermore, resources for students and practitioners across this range of areas are scarce, and the new-release textbook Computer Science in Sport: Research and Practice edited by Professor Arnold Baca, provides much of the foundation knowledge required for working in sports informatics. This is certainly a comprehensive text that will be a valuable resource for many readers.


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