Xiaotao Huang, Niannian Qin, Xiaofang Zhang, Fen Wang
{"title":"Experimental teaching design and practice on big data course","authors":"Xiaotao Huang, Niannian Qin, Xiaofang Zhang, Fen Wang","doi":"10.1109/ICCSE.2017.8085555","DOIUrl":null,"url":null,"abstract":"With the rapid development of big data technology and the rapid growth of big data industry market, big data talent demand is also a substantial increase in China. In order to cultivate more talented people satisfying the needs of the community, we have designed the big data course for undergraduates. The big data course stresses not only on many theories but also lots of practice. The project of “big data talent development trend analysis” is designed in the experimental teaching on big data. By doing this project, students can master all the technologies of big data processing lifecycle, including data collection, data preprocessing, data mining and data visualization. We evaluate students who master big data core technology with a multi-evaluation method and design the experiment evaluation system on big data. Through our two years' practice, the results show that all these designs have achieved the good effect and improved the teaching quality.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Conference on Computer Science and Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2017.8085555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the rapid development of big data technology and the rapid growth of big data industry market, big data talent demand is also a substantial increase in China. In order to cultivate more talented people satisfying the needs of the community, we have designed the big data course for undergraduates. The big data course stresses not only on many theories but also lots of practice. The project of “big data talent development trend analysis” is designed in the experimental teaching on big data. By doing this project, students can master all the technologies of big data processing lifecycle, including data collection, data preprocessing, data mining and data visualization. We evaluate students who master big data core technology with a multi-evaluation method and design the experiment evaluation system on big data. Through our two years' practice, the results show that all these designs have achieved the good effect and improved the teaching quality.