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ICI Scientific Research ║ICI work with ECNU survey and data centre on data-driven scientific research innovation

2023-05-30



In order to strengthen data-driven support for curriculum and teaching-related research, East China Normal University’s Institute of Curriculum and Instruction and Survey and Data Center of the Academy of Humanities and Social Sciences held a data-driven scientific research innovation seminar on the morning of May 24. The seminar was presided over by Professor Lei Hao, deputy director of ICI, and invited Mrs. Deng Luxiang and Dai Liyang from Survey and Data Center to attend and guide the meeting. An Guiqing, Cui Yunhuo, Ke Zheng, Liu Junyan, Wang Zhe, Xiao Sihan, Yang Xiaozhe, Zhang Wei, Zhou Wenye, Zhou Yong and other teachers attended the seminar.




Ms. Deng Luxiang systematically introduced various platforms and data resources that Survey and Data Center has built in terms of data-driven scientific research innovation, as well as the development of other data-driven related work. Mr. Dai Liyang introduced the various functions of the survey and data center survey platform, as well as typical survey cases based on the survey platform.






ICI has participated in the second round of construction of the school's new liberal arts innovation platform. There are a large amount of video data in the built data resources, and ICI has also accumulated a large amount of curriculum data. It plans to build a course teaching database and carry out long-term construction on this basis in order to better support the development of relevant research. However, there are problems. For instance, how data should be shared and digital transformation is difficult. At the meeting, the two sides discussed and exchanged issues such as database construction, data sharing mode, and special data support research.


Finally, Professor Cui Yunhuo, the director, pointed out that ICI can make full use of various data platforms, data resources, and data services in the survey and data center, so that the data-driven research paradigm can better support innovative research and promote more high-quality innovative results output.