A Study of the Deconstruction of Instructional Video in the Era of Big Data

Ruo JIA, Le-qi SUN, Fang-ye LIU

Abstract


Nowadays, education has gradually stepped into the era of big data, and the study and development of instructional video carried out on the basis of this context also need the guidance of a new way of thinking. In general, data refer to the numerical information recorded through experiment, statistics, examination, measurement, and other means for purposes such as scientific research, verification of a proposal, technology research and development, and making a reasonable decision. The practice of recording, collecting, backing up, and classifying data in an accurate and comprehensive way, and then conducting a rigorous mathematical analysis of these data can effectively reveal the development pattern of the subject in concern. Somewhat different from the above concept is big data, which are massive, clustered information generated via recording, counting, and analyzing on a large scale. In the era of big data, technologies such as cloud networking, Internet of Things, online education, and social networking will be fully developed, which will exert an impact on the idiosyncrasies of traditional industrial age with richer educational resources and more comprehensive sharing, and innovation will become the main theme in the era of big data. It is necessary to constantly break through and innovate, embody the characteristics of the era of big data, and pay more attention to digital education. It follows that finding out how to acquire more types of valid data has become a key to improving teaching outcome and teaching efficiency of an instructional video, but obviously, the traditional data extraction mode for instructional video would not be able to meet the expectation, so only by theoretically re-deconstructing the instructional video can we truly provide an adequate basic data for the big data approach. The deconstruction in this paper consists of three parts: 1) A study of the structural evolution of instructional videos; 2) A contemporary study of the definition of instructional videos; 3) A study of the classification of instructional videos.

Keywords


Education, Big data, Video


DOI
10.12783/dtssehs/eiem2018/26898

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