{"title":"教育中的大数据分析:数据驱动的文献综述","authors":"Negar Shabihi, Mi Song Kim","doi":"10.1109/ICALT52272.2021.00053","DOIUrl":null,"url":null,"abstract":"In the past decade, the applications of big data and learning analytics in education have made significant headways resulting in new opportunities for educational research. However, big data analytics (BDA) has brought new challenges to educational analytics. This paper conducts a systematic data-driven Literature review of BDA in education. Using a topic modeling approach, we have identified six topics and 19 subtopics and performed a network analysis to explore the links between the topics. Based on the results, we investigate the challenges in the field and conclude a three-dimensional model for educational BDA to address these challenges.","PeriodicalId":170895,"journal":{"name":"2021 International Conference on Advanced Learning Technologies (ICALT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Big Data Analytics in Education: A Data-Driven Literature Review\",\"authors\":\"Negar Shabihi, Mi Song Kim\",\"doi\":\"10.1109/ICALT52272.2021.00053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past decade, the applications of big data and learning analytics in education have made significant headways resulting in new opportunities for educational research. However, big data analytics (BDA) has brought new challenges to educational analytics. This paper conducts a systematic data-driven Literature review of BDA in education. Using a topic modeling approach, we have identified six topics and 19 subtopics and performed a network analysis to explore the links between the topics. Based on the results, we investigate the challenges in the field and conclude a three-dimensional model for educational BDA to address these challenges.\",\"PeriodicalId\":170895,\"journal\":{\"name\":\"2021 International Conference on Advanced Learning Technologies (ICALT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Advanced Learning Technologies (ICALT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALT52272.2021.00053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Advanced Learning Technologies (ICALT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT52272.2021.00053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big Data Analytics in Education: A Data-Driven Literature Review
In the past decade, the applications of big data and learning analytics in education have made significant headways resulting in new opportunities for educational research. However, big data analytics (BDA) has brought new challenges to educational analytics. This paper conducts a systematic data-driven Literature review of BDA in education. Using a topic modeling approach, we have identified six topics and 19 subtopics and performed a network analysis to explore the links between the topics. Based on the results, we investigate the challenges in the field and conclude a three-dimensional model for educational BDA to address these challenges.
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