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Designing An Artificial Intelligence Course For Electrical And Computer Engineering Technology Students

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Conference

2006 Annual Conference & Exposition

Location

Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006

ISSN

2153-5965

Conference Session

Programming for Engineering Students

Tagged Division

Computers in Education

Page Count

8

Page Numbers

11.417.1 - 11.417.8

DOI

10.18260/1-2--1005

Permanent URL

https://peer.asee.org/1005

Download Count

241

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Paper Authors

biography

Michael Filsinger University of Cincinnati

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MICHAEL D. FILSINGER is an Assistant Professor of Electrical and Computer Engineering Technology at the University of Cincinnati. He received a BA in Mathematics and MS degrees in Mathematics and Computer Science from the University of Cincinnati in 1990, 1992, and 1994, respectively. In addition to teaching, he has served as a computer system administrator. He is a member of IEEE, ASEE, and the Phi Beta Kappa honor society.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Designing an Artificial Intelligence Course for Electrical and Computer Engineering Technology Students

Abstract

Undergraduate students in our Electrical and Computer Engineering Technology programs have the option to take an artificial intelligence (AI) course as a junior/senior level technical elective. This course is currently structured as a modified version of a typical computer science AI course, offering a survey of various theoretical techniques presented in a more mathematically accessible way. While the first offering of this course was moderately successful, it should have been tailored more specifically to engineering technology students. This paper discusses lessons learned from this first attempt, and presents a more technology-based project-oriented approach to such a course, outlining a ten week AI course tailored to the needs of our ECET students as well as providing samples of possible projects.

Introduction

Once considered a topic for purely theoretical computer science, the field of artificial intelligence (AI) has found its way into a large number of real-world technology applications, particularly in the area of control systems. As such, a course in AI is becoming increasingly important for electrical and computer engineering technology students. The key features of a technology- based AI course are that it must deal with students who lack the extensive mathematical background of a typical computer science student, and that it should focus on real-world applications, with at most a short survey of the full range of theory.

In the Spring Quarter of 2005 our Electrical and Computer Engineering Technology department introduced an AI course offered as a technical elective for junior/senior level students. This paper describes the first attempt, which was structured as a modified version of a typical computer science AI course, offering a survey of various theoretical techniques presented in a more mathematically accessible way. While this course was moderately successful, it should have been tailored more specifically to engineering technology students.

The focus of such a course should be to show both the capabilities and the limitations of AI in industrial applications. Given the focus of our curriculum, the principle topic would be rule- based expert systems with obvious applicability to industrial control systems, including probabilistic and “fuzzy” extensions to rule-based systems. To illustrate techniques in which computer systems can “learn” and adapt to their environment, advanced topics such as artificial neural networks and genetic algorithms could be introduced if time permits, using real-world case studies as examples. The paper outlines a proposed structure of a ten week AI course as well as samples of possible projects.

Filsinger, M. (2006, June), Designing An Artificial Intelligence Course For Electrical And Computer Engineering Technology Students Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--1005

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