Practical Teaching and Research on the Design of Below-Created Products in the Era of Big Data

Author(s):  
Pengwen Wang ◽  
Yanan Hu ◽  
Jiaofei Huo
2021 ◽  
Vol 105 ◽  
pp. 348-355
Author(s):  
Hou Xiang Liu ◽  
Sheng Han Zhou ◽  
Bang Chen ◽  
Chao Fan Wei ◽  
Wen Bing Chang ◽  
...  

The paper proposed a practice teaching mode by making analysis on Didi data set. There are more and more universities have provided the big data analysis courses with the rapid development and wide application of big data analysis technology. The theoretical knowledge of big data analysis is professional and hard to understand. That may reduce students' interest in learning and learning motivation. And the practice teaching plays an important role between theory learning and application. This paper first introduces the theoretical teaching part of the course, and the theoretical methods involved in the course. Then the practice teaching content of Didi data analysis case was briefly described. And the study selects the related evaluation index to evaluate the teaching effect through questionnaire survey and verify the effectiveness of teaching method. The results show that 78% of students think that practical teaching can greatly improve students' interest in learning, 89% of students think that practical teaching can help them learn theoretical knowledge, 89% of students have basically mastered the method of big data analysis technology introduced in the course, 90% of students think that the teaching method proposed in this paper can greatly improve students' practical ability. The teaching mode is effective, which can improve the learning effect and practical ability of students in data analysis, so as to improve the teaching effect.


2015 ◽  
Vol 13 (3/4) ◽  
pp. 354-369 ◽  
Author(s):  
Lorna Muir

Working within the framework of a hypothesised shift between Michel Foucault’s model of discipline and Gilles Deleuze’s paradigm of the control society, this article considers the cinematic expression of emerging modes of monitoring in a surveillance society in which there has been an exponential increase in, and access to, information. In order to contextualise this interplay between these two models, three related areas are considered in this article. Firstly, the growing awareness of the consequences of Big Data, not only within teaching and research institutions, but through the dissemination of (sometimes erroneous) information in popular media and various news platforms is discussed. The British government’s response to such developments with a ‘rhetoric of transparency’, which has been critically undermined with the recent ‘leaks’ from whistleblowers affecting both British and American security agencies, in particular, is considered. Secondly, a brief outline of the changing theoretical models which can be employed to aid understanding of this situation is offered and, thirdly, in examining popular cultural responses to the rise of a Big Data discourse, two films are analysed, Sam Mendes's Skyfall (2012) and Tomas Alfredson's 2011 Tinker, Tailor, Soldier, Spy, both of which seek to engage with these changing frameworks. These films in turn contribute to the fictions of transparency in relation to government espionage agencies.


Web Services ◽  
2019 ◽  
pp. 1802-1811
Author(s):  
Jameson Mbale

The ZAMREN member institutions deal with heterogeneous teaching and research materials drawn from all walks-of-life such as industry, and NRENs world over. To deal with such huge data that is in terabits for academic and economic gain becomes a mammoth task to manipulate, process, store and analyse. It is in view of that the ZAMREN Big Data and Data Management, in this work abbreviated as ZAMBiDM, is envisaged to collectively gather relevant heterogeneous large volumes of a wide variety of data from all sectors of economy. The data would be analytically managed in storage, processing and obtaining actionable insight real-time as a way to solve high-value skilled academic and industrial business problems, in order to prepare graduates for competitive future workforce. The data would be collected from all line-ministries of Zambia such as education, agriculture, health, mining, lands, communications, commerce, including industries and NRENs worldwide and be analytically analysed to exploit strategic actions that would enhance decision making in executing relevant tasks.


Author(s):  
Jameson Mbale

The ZAMREN member institutions deal with heterogeneous teaching and research materials drawn from all walks-of-life such as industry, and NRENs world over. To deal with such huge data that is in terabits for academic and economic gain becomes a mammoth task to manipulate, process, store and analyse. It is in view of that the ZAMREN Big Data and Data Management, in this work abbreviated as ZAMBiDM, is envisaged to collectively gather relevant heterogeneous large volumes of a wide variety of data from all sectors of economy. The data would be analytically managed in storage, processing and obtaining actionable insight real-time as a way to solve high-value skilled academic and industrial business problems, in order to prepare graduates for competitive future workforce. The data would be collected from all line-ministries of Zambia such as education, agriculture, health, mining, lands, communications, commerce, including industries and NRENs worldwide and be analytically analysed to exploit strategic actions that would enhance decision making in executing relevant tasks.


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