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Artificial Neural Networks: A New Approach to Predicting Application Behavior

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Abstract

In this article we examine how predictive modeling can be used to study application behavior. We apply a relatively new technique, artificial neural networks, to help us predict which students are likely to apply to a large Research I institution in the Midwest. We compare the results of these new techniques to the traditional analysis tool, logistic regression modeling. The addition of artificial intelligence models is an exciting new area and this article encourages other institutional researchers to use this technique to explore the complex processes found in our educational institutions.

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Authors and Affiliations

  1. Educational Policy and Leadership Studies, The University of Iowa, Iowa City, IA

    Julie M. Byers González

  2. Educational Policy and Leadership Studies, The University of Iowa, N491 Lindquist Center, Iowa City, IA, 52242-1529

    Stephen L. DesJardins

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  1. Julie M. Byers González
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  2. Stephen L. DesJardins
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Correspondence to Stephen L. DesJardins.

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González, J.M.B., DesJardins, S.L. Artificial Neural Networks: A New Approach to Predicting Application Behavior. Research in Higher Education 43, 235–258 (2002). https://doi.org/10.1023/A:1014423925000

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