{"title":"机构研究与分析数据库的开发与应用","authors":"Yuen-Hsien Tseng","doi":"10.6151/CERQ.2016.2401.04","DOIUrl":null,"url":null,"abstract":"This article elaborates on the possible best practice of developing databases for institutional research and analysis, based on the knowledge of Educational Science, Library Science, and Information Engineering, years of experience in developing educational databases, and a recent survey of related technology and products. Several developing options are compared to show their benefits and disadvantages under different conditions. Three representative analysis tasks are reported to verify and show the synergy of the mentioned ideas and experience. In particular, this article proposes a sustainable workflow: (1) data collection and aggregation, (2) cataloguing, (3) regulation, (4) archiving, and (5) usage, and describes their must-known caveats. The application situations of data normalization and de-normalization are described. Capability of domestic vendors of related products is briefly mentioned based on a proof-ofconcept testing. And finally, real-world institutional analyses are conducted to share our experience. Overall, the first four processes in the above workflow are most timeconsuming and costly. Once data have been well prepared, recent visualization analysis tools allow users to easily discover meaningful patterns and inspire hypotheses, and allow them to explore the database to find evidence to support their hypotheses and decisions. In the future, we expect that event evolution simulation techniques, which allow users to foresee the results given various input scenarios, could play an important role in educational data analysis, in addition to the maturing data visualization tools.","PeriodicalId":38533,"journal":{"name":"Contemporary Educational Research Quarterly","volume":"40 1","pages":"107-134"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Development and application of databases for institutional research and analysis\",\"authors\":\"Yuen-Hsien Tseng\",\"doi\":\"10.6151/CERQ.2016.2401.04\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article elaborates on the possible best practice of developing databases for institutional research and analysis, based on the knowledge of Educational Science, Library Science, and Information Engineering, years of experience in developing educational databases, and a recent survey of related technology and products. Several developing options are compared to show their benefits and disadvantages under different conditions. Three representative analysis tasks are reported to verify and show the synergy of the mentioned ideas and experience. In particular, this article proposes a sustainable workflow: (1) data collection and aggregation, (2) cataloguing, (3) regulation, (4) archiving, and (5) usage, and describes their must-known caveats. The application situations of data normalization and de-normalization are described. Capability of domestic vendors of related products is briefly mentioned based on a proof-ofconcept testing. And finally, real-world institutional analyses are conducted to share our experience. Overall, the first four processes in the above workflow are most timeconsuming and costly. Once data have been well prepared, recent visualization analysis tools allow users to easily discover meaningful patterns and inspire hypotheses, and allow them to explore the database to find evidence to support their hypotheses and decisions. In the future, we expect that event evolution simulation techniques, which allow users to foresee the results given various input scenarios, could play an important role in educational data analysis, in addition to the maturing data visualization tools.\",\"PeriodicalId\":38533,\"journal\":{\"name\":\"Contemporary Educational Research Quarterly\",\"volume\":\"40 1\",\"pages\":\"107-134\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Educational Research Quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6151/CERQ.2016.2401.04\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Educational Research Quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6151/CERQ.2016.2401.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development and application of databases for institutional research and analysis
This article elaborates on the possible best practice of developing databases for institutional research and analysis, based on the knowledge of Educational Science, Library Science, and Information Engineering, years of experience in developing educational databases, and a recent survey of related technology and products. Several developing options are compared to show their benefits and disadvantages under different conditions. Three representative analysis tasks are reported to verify and show the synergy of the mentioned ideas and experience. In particular, this article proposes a sustainable workflow: (1) data collection and aggregation, (2) cataloguing, (3) regulation, (4) archiving, and (5) usage, and describes their must-known caveats. The application situations of data normalization and de-normalization are described. Capability of domestic vendors of related products is briefly mentioned based on a proof-ofconcept testing. And finally, real-world institutional analyses are conducted to share our experience. Overall, the first four processes in the above workflow are most timeconsuming and costly. Once data have been well prepared, recent visualization analysis tools allow users to easily discover meaningful patterns and inspire hypotheses, and allow them to explore the database to find evidence to support their hypotheses and decisions. In the future, we expect that event evolution simulation techniques, which allow users to foresee the results given various input scenarios, could play an important role in educational data analysis, in addition to the maturing data visualization tools.
期刊介绍:
"Contemporary Education Research" is an educational academic journal aimed at disseminating educational research results, promoting academic exchanges, and improving educational research standards. The magazine was originally published in the "Teaching Research Information" of the National Taiwan Normal University Education Research Center. It was included in the Taiwan Social Science Citation Index in the Humanities Department of the Ministry of Science and Technology in 1992 and 1993 respectively. In the TSSCI) database watch list, it was selected as a journal in the TSSCI database in the 1994 school year. It also became the world''s largest citation index database Scopus ( www.scopus.com ) in March 2001 . Journal.