Teaching Artificial Intelligence Panel--CCSC:SW 2010

Teaching Methodology of Artificial Intellignece and Related Subjects:
Meeting Industry's Needs

Panel Discussion

Stephanie E. August, Ph. D.
Associate Professor
Electrical Engineering and Computer Science Department
Loyola Marymount University, Los Angeles
saugust@lmu.edu 		Jim Blythe, Ph.D.
Research Scientist
Information Sciences Institute
University of Southern California
blythe@isi.edu 		Peter N. Gabrovsky, Ph. D.
Associate Professor
Department of Computer Science
California State University Northridge
peter.gabrovsky@csun.edu
Abstract
The discussion will begin by describing the current state of the art in industry-ready AI and the increasing call for AI in the job market. Then we will shift the focus to consider the content of the AI curriculum and that of related disciplines; availability of textbooks and other forms of teaching materials, including case studies to increase the interpersonal orientation of the classroom experience and the use of immersive environments; the design of homework and exams; the choices of programming languages for programming projects; the relation to other computer science and engineering disciplines to AI; and the perspectives for designing an introductory AI course for majors outside Engineering/Computer Science, keeping in mind both undergraduate and the graduate levels of instruction throughout the discussion. We will conclude by asking what the best ways are to prepare our students for industry's needs, given the available resources and maturity of teaching methodologies.

Biography
Stephanie August is an Associate Professor of Computer Science at LMU, where she teaches courses in AI, database management systems, and software engineering. Her research interests include new media applications, natural language understanding, analogical reasoning, immersive learning environments, the use of case studies in teaching AI, and increasing the interpersonal orientation of the classroom experience. Her industry experience includes software and system engineering for several defense C3I programs, and applied artificial intelligence research for military and medical applications.

Peter Gabrovsky has taught AI and related courses almost every semester at CSUN for 20 years and has also taught various AI subjects through UCLA extension for several years. Presently, he is responsible for the AI computer lab at CSUN. Peter has several publications on AI topics and is active in advising industry on AI-related subjects.

Jim Blythe is a research scientist in the Intelligent Systems Division of the Information Sciences Institute at USC. His research interests include knowledge acquisition, planning, uncertainty and applications of AI to security and grid systems. He has published over 50 articles and papers on AI, with funding from several agencies including DARPA and NSF. He was a visiting fellow at the UK E-Science center in 2005 and has served on the program committees of several conferences including AAAI, UAI, IUI and ICAPS.

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