NSF Award
0716338
Computer Science (31)<br/><br/>It is generally recognized that an introductory Artificial Intelligence (AI) course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core AI topics that are typically covered. This project addresses this problem and enhances the student learning experience in the introductory Artificial Intelligence course by (1) introducing machine learning elements into the AI course, (2) implementing a set of unifying machine learning laboratory projects to tie together the core AI topics, and (3) developing, applying, and testing an adaptable framework for the presentation of core AI topics which emphasizes the strong tie between AI and computer science. This is a multi-institutional effort that engages a community of 20 scholars from a broad range of universities working together on the development, implementation, and testing of curricular material, in a manner that fosters the integration of research and education. The target audience is juniors and seniors in Computer Science, Computer Engineering, and Computer Information Systems enrolled in an introductory Artificial Intelligence course. The project deliverable is a laboratory manual consisting of a suite of adaptable, self-contained, hands-on laboratory projects that can be closely integrated into a one-term AI course and which would supplement introductory AI texts. The curricular material builds on existing successful work, funded by NSF CCLI A&I. It involves further development and testing of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. Through the design and implementation of learning systems that enhance commonly-deployed applications, the innovative model for teaching artificial intelligence provides a simple and elegant means to communicate the power of the core ideas of AI in a manner that engages students in experiential education.
