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Policy on Computer-Related Courses

The following following policy with regard to computer-related courses was approved by the Faculty Senate on October 26, 2006 in Senate Bill #06-07--3, The Four Hundred and Forty-Fourth Report of the Curricular Affairs Committee:

In very general terms, computer science as a discipline describes its content as the design, implementation, and evaluation of algorithms that can be executed on computing machinery; the study of the methods and results of computational (algorithmic) processes; and the design, implementation, and evaluation of computational (algorithmic) principles to problems that can be solved via computation.

The Computer Science Department will be consulted in the review of courses whose primary content falls into any of the areas outlined below:

1) Computer and Computational Concepts and Skills. This includes courses that teach basic computer hardware, use of computer operating systems, the working of computer networks and Internet applications, and general computer concepts for a general audience.

2) Computer Programming and Software Engineering. This includes courses that teach computer languages (programming languages, scripting languages, and markup languages), programming techniques, and the methodologies for creating computer software, scripts, and database schemas.

3) Computer Science Applications. This includes courses that teach how to create: web applications, database applications, artificial intelligence applications, computer graphics applications, bioinformatics applications, computer-based cryptography, and digital forensics--i.e., courses that that are based on the application of computational principles and concepts to problems in the various disciplines or areas.

4) Computer Software Systems. This includes courses that teach the development of computer operating systems, computer networking protocols and techniques, and computer security.

5) Computing Theory. This includes courses that teach the theory of computation and analysis of computer algorithms.



Sheila Black Grubman

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