With the coming of 4G era, the popularity of various kinds of online equipment, the maturity of Web 2.0 skills, and the effects of increased ability of internet of students and teachers, Taiwan Education Cloud has been progressively emerging with the characteristics of large volume, velocity, and variety of education big data. This has made the currently familiarized techniques of statistical learning and data mining of all departments of MOE (Ministry of Education), such as news briefing, artificial retrieving and synthesizing information, and personnel experience judgment, unable to efficaciously analyze education big data that rapidly accumulate. We develop a new analytical steps and logical thinking so that, while facing such digital information accumulation trend, composedly extract information of valuable teachers and students feedback from such education big data mighty torrent. The paper is to aim for "Look Taiwan Education Big Data Research and Development", and we use the currently big data techniques to analyze the learning background of individual learners in Taiwan Education Big Market. Through the collection, conduction, and analysis of the past using experience, it was further predicted, suggested, and giving feedback on the need of Taiwan Education Big Market for teachers and students.
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