Artificial Intelligence Techniques for an Interdisciplinary Science Course

  • C. L. Karr
  • C. Sunal
  • C. Smith
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 36)


This chapter describes an innovative course developed and taught at The University of Alabama in which students in the College of Education are given an overview of artificial intelligence (AI) techniques including expert systems, fuzzy systems, neural networks, and genetic algorithms. The class, ESM 130: Artificial Intelligence Systems in Science, was developed and is team-taught by professors from the Colleges of Engineering and Education. When artificial intelligence techniques are taught in an engineering or computer science curriculum, the focus is generally on the mathematical or algorithmic details of the various techniques. In ESM 130, however, the focus is on the biological systems upon which most artificial intelligence techniques are based, and the subsequent modeling of the biological paradigm. The goal of the class is to provide future educators with enough information about the science of the twenty-first century to effectively educate, motivate, and stoke the fires of inquiry burning in their future students. To do this, they must have at least a fundamental understanding of artificial intelligence: what it is, where it comes from, and what it can be used for.


Genetic Algorithm Fuzzy Logic Scientific Problem Future Teacher Artificial Intelligence Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • C. L. Karr
    • 1
  • C. Sunal
    • 2
  • C. Smith
    • 2
  1. 1.Department of Aerospace Engineering and MechanicsThe University of AlabamaTuscaloosaUSA
  2. 2.Area of Teacher EducationThe University of AlabamaTuscaloosaUSA

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