Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences

In recent years, AI-based applications have increasingly been used in real-world domains. For example, game theory-based decision aids have been successfully deployed in various security settings to protect ports, airports, and wildlife. This article describes our unique problem-to-project educational approach that used games rooted in real-world issues to teach AI concepts to diverse audiences. Specifically, our educational program began by presenting real-world security issues, and progressively introduced complex AI concepts using lectures, interactive exercises, and ultimately hands-on games to promote learning. We describe our experience in applying this approach to several audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluated our approach based on results from the games and participant surveys.

[1]  Peter Norvig,et al.  A Survey of Current Practice and Teaching of AI , 2016, AAAI.

[2]  Michael Wollowski Teaching With Watson , 2014, AAAI.

[3]  Milind Tambe,et al.  Using Science Fiction in Teaching Artificial Intelligence , 2008, AAAI Spring Symposium: Using AI to Motivate Greater Participation in Computer Science.

[4]  Milind Tambe,et al.  From the Lab to the Classroom and Beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences , 2016, AAAI.

[5]  Daniel L. Schwartz,et al.  Doing with Understanding: Lessons from Research on Problem- and Project-Based Learning , 1998 .

[6]  Roy,et al.  The Social and Technological Dimensions of Scaffolding and Related Theoretical Concepts for Learning , Education , and Human Activity , 2004 .

[7]  Leon Sterling,et al.  Teaching AI algorithms using animations reinforced by interactive exercises , 1997, ACSE '97.

[8]  M. Segers,et al.  Effects of problem-based learning: a meta- analysis , 2003 .

[9]  A. Palincsar,et al.  Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning , 1991 .

[10]  John DeNero,et al.  Teaching Introductory Artificial Intelligence with Pac-Man , 2010, AAAI 2010.

[11]  Roy D. Pea The Social and Technological Dimensions of Scaffolding and Related Theoretical Concepts for Learning, Education, and Human Activity , 2004 .

[12]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[13]  Cynthia E. Irvine,et al.  A video game for cyber security training and awareness , 2007, Comput. Secur..

[14]  J. Bruner,et al.  The role of tutoring in problem solving. , 1976, Journal of child psychology and psychiatry, and allied disciplines.

[15]  P. Rybski,et al.  Interacting with the real world : a way of teaching , 2007 .

[16]  Elizabeth Sklar,et al.  Teaching AI using LEGO Mindstorms , 2004 .

[17]  Julie E. Mills Engineering Education, Is Problem-Based or Project-Based Learning the Answer , 2003 .

[18]  Milind Tambe,et al.  Comparing human behavior models in repeated Stackelberg security games: An extended study , 2016, Artif. Intell..

[19]  Milind Tambe,et al.  Robust Protection of Fisheries with COmPASS , 2014, AAAI.

[20]  Sven Koenig,et al.  Teaching Artificial Intelligence and Robotics Via Games , 2010 .

[21]  Juliane Hahn Security And Game Theory Algorithms Deployed Systems Lessons Learned , 2016 .

[22]  Milind Tambe,et al.  "A Game of Thrones": When Human Behavior Models Compete in Repeated Stackelberg Security Games , 2015, AAMAS.

[23]  Rong Yang,et al.  Adaptive resource allocation for wildlife protection against illegal poachers , 2014, AAMAS.

[24]  Milind Tambe,et al.  When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing , 2015, IJCAI.

[25]  Milind Tambe,et al.  Patrol Strategies to Maximize Pristine Forest Area , 2012, AAAI.