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Progress On The Crcd Experiences At The University Of Central Florida: An Nsf Project

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2005 Annual Conference


Portland, Oregon

Publication Date

June 12, 2005

Start Date

June 12, 2005

End Date

June 15, 2005



Conference Session

Undergraduate Research & New Directions

Page Count


Page Numbers

10.1031.1 - 10.1031.31



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Paper Authors

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Michael Georgiopoulos

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

Session XXXX

Progress on the CRCD Experiences at the University of Central Florida: An NSF Project Michael Georgiopoulos*, Erol Gelenbe**, Ronald Demara*, Avelino Gonzalez*, Marcella Kysilka*, Mansooreh Mollaghasemi*, Annie Wu*, Georgios Anagnostopoulos***, Ingrid Russell****, Jimmy Secretan*

(*) University of Central Florida (**) Imperial College (***) Florida Institute of Technology (****) University of Hartford

Abstract Machine Learning has traditionally been a topic of research and instruction in computer science and computer engineering programs. Yet, due to its wide applicability in a variety of fields, its research use has expanded in other disciplines, such as electrical engineering, industrial engineering, civil engineering, and mechanical engineering. Currently, many undergraduate and first-year graduate students in the aforementioned fields do not have exposure to recent research trends in Machine Learning. This paper reports on a project in progress, funded by the National Science Foundation under the program Combined Research and Curriculum Development (CRCD), whose goal is to remedy this shortcoming. The project involves the development of a model for the integration of Machine Learning into the undergraduate curriculum of those engineering and science disciplines mentioned above. The goal is increased exposure to Machine Learning technology for a wider range of students in science and engineering than is currently available. Our approach of integrating Machine Learning research into the curriculum involves two components. The first component is the incorporation of Machine Learning modules into the first two years of the curriculum with the goal of sparking student interest in the field. The second is the development of new upper level Machine Learning courses for advanced undergraduate students. In the past, we have reported on our experiences of introducing Machine Learning modules in sophomore and junior undergraduate classes, in an effort to recruit students for our senior level classes (Current Topics in Machine Learning I (CTML-I) and Current Topics in Machine Learning II (CTML-II)). This paper focuses on discussing our experiences in teaching these senior level classes of CTML-I and CTML-II.

1. Introduction

In the last decade there has been an explosion of research in machine learning. A contributing factor is that traditionally independent research communities in symbolic machine learning,

Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society For Engineering Education

Georgiopoulos, M. (2005, June), Progress On The Crcd Experiences At The University Of Central Florida: An Nsf Project Paper presented at 2005 Annual Conference, Portland, Oregon. 10.18260/1-2--14669

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