Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Introductory programming, criterion-referencing, and bloom
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
Machine Learning
First year programming: let all the flowers bloom
ACE '03 Proceedings of the fifth Australasian conference on Computing education - Volume 20
Using course portfolios to create a disciplinary commons across institutions
Journal of Computing Sciences in Colleges
Three fun assignments for an Artificial Intelligence class
Journal of Computing Sciences in Colleges
Poker as a group project for artificial intelligence
Proceedings of the 37th SIGCSE technical symposium on Computer science education
Teaching artificial intelligence using web-based applications
Journal of Computing Sciences in Colleges
Creating significant learning experiences in introductory artificial intelligence
Proceedings of the 38th SIGCSE technical symposium on Computer science education
Give students a clue: a course-project for undergraduate artificial intelligence
Proceedings of the 38th SIGCSE technical symposium on Computer science education
Teach scheme, reach Java: introducing object-oriented programmming without drowning in syntax
Journal of Computing Sciences in Colleges
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One of the great challenges of teaching is managing a wide range of educational backgrounds, learning styles, aptitudes, and time/energy constraints in the same classroom. Aiming down the middle is a poor strategy; it is unacceptable to write off the lower half of a class, and we risk extinguishing the enthusiasm of the best and brightest by moving too slowly. We present a set of workbook-style lab assignments for an undergraduate course on artificial intelligence. By designing them carefully in accordance with Bloom's taxonomy, they can span learning styles and aptitudes. With them, we hope to establish a disciplinary commons -- a public repository of source code, notes, questions, and exercises.