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Tools for Educational Researchers Working With Big Data

Tools for Educational Researchers Working With Big Data

Copyright: © 2018 |Pages: 23
ISBN13: 9781522551614|ISBN10: 1522551611|EISBN13: 9781522551621
DOI: 10.4018/978-1-5225-5161-4.ch004
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MLA

Peggy Semingson, et al. "Tools for Educational Researchers Working With Big Data." The Community of Inquiry Framework in Contemporary Education: Emerging Research and Opportunities, IGI Global, 2018, pp.53-75. https://doi.org/10.4018/978-1-5225-5161-4.ch004

APA

P. Semingson, P. Smith, & H. Anderson (2018). Tools for Educational Researchers Working With Big Data. IGI Global. https://doi.org/10.4018/978-1-5225-5161-4.ch004

Chicago

Peggy Semingson, Pete Smith, and Henry I. Anderson. "Tools for Educational Researchers Working With Big Data." In The Community of Inquiry Framework in Contemporary Education: Emerging Research and Opportunities. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5161-4.ch004

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Abstract

Among the foremost challenges with big data is how to go about analyzing it. What new tools are needed to be able to properly investigate and model the large quantities of highly complex, often messy data? Chapter 4 addresses this question by introducing and briefly exploring the fields of Machine Learning, Natural Language Processing, and Social Network Analysis, focusing on how these methods and toolsets can be utilized to make sense of big data. The authors provide a broad overview of tools, ideas, and caveats for each of these fields. This chapter ends with a look at how one major public university in the United States, the University of Texas at Arlington, is beginning to address some of the questions surrounding big data in an institutional setting. A list of additional readings is provided.

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