In the past few years, many universities have experienced a dramatic decline in undergraduate Computer Science enrollments. Although the dot-com bust and job off-shoring have often been cited as causes for this decline, there is also mounting evidence that Computer Science is being equated simply with "programming" and is losing its intellectual excitement to students who are unaware of the wide variety of options in the discipline.

In reality, the field of Computer Science now offers far more options than it did even a decade or two ago. Moreover, many of these diverse options are rooted in AI and are potentially quite exciting to students. Examples include robotics, game-playing, machine learning, and work overlapping computational biology and economics.

Such a rich set of AI-related directions for study provides the opportunity to greatly enhance the appeal of Computer Science to new students. The challenge lies in finding appropriate means for exposing students to such options, providing curriculum to stimulate their interest in the field, and disseminating successful educational materials to other educators.

The goal of this symposium is to identify ways that topics in AI may be used to motivate greater student participation in Computer Science by highlighting fun, engaging, and intellectually challenging developments in AI-related curriculum. We seek to examine AI-related programs and curriculum that can capture student interest early in their undergraduate years and/or be suitable for deployment at an even earlier stage in the education pipeline (e.g., high schools).

The symposium aims to bring together educators, researchers, and curriculum designers to discuss successful tactics and strategies in using AI-based educational resources to help increase the intellectual excitement of CS and promote greater participation in the field. In addition to paper presentations, the symposium will include invited speakers, panels, and hands-on demonstrations.

Some specific topics that contributors are invited to address include (but are not limited to):

  • AI-themed assignments in introductory curricula
  • The use of robotics and other tangible media in CS curricula
  • Generating interest through game playing and machine learning
  • Motivating CS-based multi-disciplinary work with AI (e.g. computational biology, algorithmic game theory, computational economics, etc.)
  • The relationship of AI to the rest of the CS curriculum
  • Means for disseminating educational materials outside the university
  • The use of AI in special teaching environments for introductory courses (e.g., Karel the Robot, Alice, etc.)
  • Other planned or deployed educational initiatives involving AI

Organizing Committee

Mehran Sahami (chair), Stanford University
Marie desJardins, University of Maryland, Baltimore County
Zachary Dodds, Harvey Mudd College
Jeffrey Forbes, Duke University
Timothy T. Huang, Middlebury College
Caitlin Kelleher, Carnegie Mellon University
Tom Lauwers, Carnegie Mellon University
Todd W. Neller, Gettysburg College
Illah R. Nourbakhsh, Carnegie Mellon University