Abstract
The recent advancement in computing technology, availability of low-cost storage devices, and popularity of Internet have empowered data acquisition that is substantially different from the traditional approach (Hand, Mannila, and Smyth, 2001;Wegman, 1995). This trend has influenced higher education in many aspects, one of which is the increasing number of large data sets as secondary data sources for academic research. It has become common for journals in higher education to present studies (e.g., Rosser, 2004; Toutkoushian and Conley, 2005) that were based on a data set of over several thousands of records from sources such as the National Center for Educational Statistics (NCES) and the American Association of Community Colleges.
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Xu, Y.J. (2006). USING DATA MINING TO ANALYZE LARGE DATA SETS IN HIGHER EDUCATION RESEARCH: AN EXAMPLE OF PREDICTION WITH NSOPF: 99. In: Smart, J.C. (eds) HIGHER EDUCATION:. Higher Education: Handbook of Theory and Research, vol 21. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4512-3_9
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