New Course Proposal – Page 1/8
NEW COURSE PROPOSALS: Lecture/Lab or Lecture/Activity COMBINATION PROPOSAL
College: [ Engineering and Computer Department: [ Computer Science ]
Science ]
Note: Use this form to request two courses that are co-requisites with each other such as Lecture/Lab or
Lecture/Activity combinations. These are routinely published together in the printed Catalog and SOC as in BIOL
101/L (3/1). However, these are technically two entries in the Solar Catalog: BIOL 101 (3) and BIOL 101L (1).
This form allows you to request both the lecture/lab and lecture/activity courses together.
1. Course information for Catalog Entry
Subject Abbreviation and Number: (ie, BIOL 101/L General Biology and Lab (3/1)L) [ COMP 256/L ]
Course Title: ( BIOL 101 General Biology (3)) [ Discrete Structures for Computer Science ]
Lecture Units: [ 3 ] units
Course Prerequisites: [ MATH 150A, PHIL 230, COMP 182/L] (if any)
Course Corequisites: [] (if any)
Recommended Preparatory Courses: [
] (if any)
Laboratory/Activity Title: ( General Biology Lab (1)) [ Discrete Structures for Computer Science Lab ]
Laboratory/Activity Units: [ 1 ] units
Course Prerequisites: [MATH 150A, PHIL 230, COMP 182/L] (if any)
Course Corequisites: [] (if any)
Recommended Preparatory Courses: [
] (if any)
2. Course Description for Printed Catalog: Notes: If grading is NC/CR only, please state in course description.
If a course
numbered less than 500 is available for graduate credit, please state “Available for graduate credit in the catalog description.”
[Study of discrete mathematical structures and proof techniques as used in computer science.
Discrete structures such as functions, relations, sets, graphs, and trees. Proof techniques such as
proof by induction, proof by contradiction, and proof by cases. Counting techniques. Lab: three
hours per week. ]
3. Date of Proposed Implementation: (Semester/Year): [ Fall ] / [ 2011 ] Comments
4. Course Level
[ ]Undergraduate Only
[
]Graduate Only
[
]Graduate/Undergraduate
5. Course Abbreviation “Short title” (maximum of 17 characters and spaces)
Lecture Short Title: [ D•I•S•C• •S•T•R•U•C•T ]
Lab/Activity Short Title: [ D•I•S•C• •S•T•R•U•C•T• •L•A•B• • • ]
6. Basis of Grading:
[ ]Credit/No Credit Only
[
]Letter Grade Only
[
]CR/NC or Letter Grade
7. Number of times a courses may be taken:
[
] May be taken for credit for a total of [1] times, or for a maximum of [4] units
[
] Multiple enrollments are allowed within a semester
8. C-Classification: (e.g., Lecture-discussion (C-4).)
Lecture [ 3 ] units @ [C] [4]
Lab/Activity [ 1 ] units @ [C] [16]
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9. Replaces Current Experimental Course?
[
] YES
[
] NO
Replaces Course Number/Suffix:[ COMP 296FCS/FCL ]
Previously offered [ 3 ] times.
10. Proposed Courses Use: (Check all that apply)
[
]Own Program:
[
]Major
[
]Minor
[
]Masters
[
] Requirement or Elective in another Program
[
] General Elective
[
] General Education, Section [
]
[
] Meets GE Information Competence (IC) Requirement
[
] Meets GE Writing Intensive (WI) Requirement
[
] Community Service Learning (CS)
[
] Cross-listed with: (List courses) [
]
[
]Credential
[
]Other
11. Justification for Request: Course use in program, level, use in General Education, Credential, or other. Include
information on overlap/duplication of courses within and outside of department or program. (Attach)
12. Estimate of Impact on Resources within the Department, for other Departments and the
University. (Attach)
(See Resource List)
13. Course Outline and Syllabus (Attach) Include methods of evaluation, suggested texts, and selected bibliography.
Describe the difference in expectations of graduates and undergraduates for all 400 level courses that are offered to both.
14. Indicate which of the PROGRAM’S measurable Student Learning Outcomes are addressed in
this course. (Attach)
15. Assessment of COURSE objectives (Attach)
A. Identify each of the course objectives and describe how the student performance will be
assessed
(For numbers 14 and 15, you can use, as a guide, the Course Alignment Matrix and the Course Objectives Chart)
16. If this is a General Education course combination, indicate how the General Education
Measurable Student Learning Outcomes (from the appropriate section) are addressed in this
course. (Attach)
17. Methods of Assessment for Measurable Student Learning Outcomes (Attach)
A. Assessment tools
B. Describe the procedure dept/program will use to ensure the faculty teaching the course will be
involved in the assessment process (refer to the university’s policy on assessment.)
18. Record of Consultation: (Normally all consultation should be with a department chair or program coordinator. ) If
more space is needed attach statement and supporting memoranda.
Date:
[ 3/8/2010 ]
[ 2/6/2010 ]
[ 3/12/2010 ]
[ 3/12/2010 ]
[ 3/12/2010 ]
NC – 9/29/05
Dept/College:
[ Mathematics ]
[ Computer Science ]
[ CEAM ]
[ ECE ]
[ MSEM ]
Department Chair/ Program
Coordinator
[ Werner Horn ]
[Dept vote; Steven Stepanek ]
[ Steve Gadomski ]
[ Ali Amini ]
[ Behzad Bavarian ]
Concur
(Y/N)
[Y]
[Y]
[Y ]
[Y]
[Y ]
New Course Proposal – Page 2/8
[ 3/12/2010 ]
[ ME]
[ Hamid Johari ]
[Y ]
Consultation with the Oviatt Library is needed to ensure the availability of appropriate resources to
support proposed course curriculum.
Collection Development Coordinator, Mary Woodley
Date
Please send an email to: [email protected]
[3/8/2010]
19. Approvals:
11.
Department Chair/Program Coordinator:
Date:
College (Dean or Associate Dean):
Date:
Educational Policies Committee:
Date:
Graduate Studies Committee:
Date:
Provost:
Date:
[ 3/8/2010 ]
[
]
[
]
[
]
[
]
Justification for Request
An important development in computer science disciplines is to move the coverage of discrete structures
to the lower division and to form a tighter integration with the computer science data structure courses.
This integration should help improve the pass rates in sophomore level data structures classes and should
facilitate the retention of discrete math concepts needed throughout the major. The department developed
an experimental sophomore level discrete structures course in Fall 2008. Over the past two years
computer science majors have been able to take an experimental version of a sophomore level discrete
structures course but it was not a required for the major. Having this course at the lower division will
improve articulation relationships with local community colleges and provide a closer fit with the CSU
LDTP for computer science.
The Computer Science Department is proposing (in a related Program Modification Proposal) that the
experimental discrete structures be replaced with a permanent course (Comp 256/L) and proposes to
modify the computer science program to require Comp 256/L and to drop Math 326.
12.
Estimate Impact on Resources within the Department, for other Departments, and the
University
Facilities: Existing computer sciences labs will suffice for this class. The lab software is either free or
covered by existing College/University licenses. There will be no training costs associated with
installation of the additional software. The support staff is already familiar with many of the proposed
software tools so no new support will be required.
The department has sufficient full-time faculty to provide leadership and instructors to teach this course.
There would be a small FTES impact (approximately 4  6 FTES per semester) on the Math Department
as this course would be replacing MATH 326 in the computer science curriculum.
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13.
Course Outline and Syllabus
COMP 256 (lecture)
Lecture Course Objectives
1. Demonstrate knowledge of basic terms and operations associated with sets, functions, and relations
such as basic algebra of sets and logics, basic properties of arbitrary functions, and identify common
classes of relations, e.g., equivalence relations.
2. Study various proof techniques and problems appropriate to them.
3. Relate the ideas of mathematical induction to recursion and recursively defined structures.
4. Solve counting problems involving combinations, permutations, including counting problems with
restrictions.
5. Know the basic definitions, theorems, and algorithms of graph theory, and be able to apply them to
specific graphs.
6. Know basic algorithms for traversing trees, and be able to apply them to specific trees
Potential Textbooks
Discrete Mathematics: Elementary and Beyond by L. Lovasz, J. Pelikand, and K. Vesztergombi. (ISBN:
978-0-387-95585-8) 2003.
Discrete Structures, Logic, and Computability, Second Edition_James L. Hein, Portland State University
(ISBN-13: 9780763718435) 2002
Discrete Mathematics, by Kenneth A. Ross and Charles R. B. Wright., Prentice Hall, (ISBN: 0-13065247-4) 2002.
Lecture Grading (Plus/Minus letter grading will be used)
Three Quizzes
30%
Participation
5%
Midterm
30%
Final
35%
Lecture Topics
Functions, relations, and sets (2 weeks)
Functions (surjections, injections, inverses, composition)
Application on functional paradigm on bijections, inverses and composition
Relations (reflexivity, symmetry, transitivity, equivalence relations)
Sets (Venn diagrams, complements, Cartesian products, power sets)
Cardinality and countability
Proof techniques (4 weeks)
Notions of implication, converse, inverse, contrapositive, negation, and contradiction
The structure of formal proofs
Direct proofs
Proof by counterexample
Proof by contrapositive
Proof by contradiction
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Mathematical induction
Strong induction
Recursive mathematical definitions
Well orderings
Basics of counting (3 weeks)
Counting arguments
Sum and product rule
Inclusion-exclusion principle
Arithmetic and geometric progressions
Fibonacci numbers
The pigeonhole principle
Permutations and combinations
Basic definitions
Pascal's identity
The binomial theorem
Solving recurrence relations
Common examples
The Master theorem
Discrete probability (2 weeks)
Finite probability space, probability measure, events
Conditional probability, independence
Integer random variables, expectation
Graphs and trees (3 weeks)
Trees
Undirected graphs
Directed graphs
Spanning trees
Traversal strategies
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COMP 256L (lab)
Lab Course Objectives
1. Be able to formulate, analyze, and solve problems in discrete mathematics.
2. Be able to recognize and utilize appropriate proof techniques for solving problems.
3. Model problems in computer science using combinations, permutations, including counting problems
with restrictions.
4. Model problems in computer science using graphs, trees and traversal methods.
Lab Grading (Plus/Minus letter grading will be used)
Eight homework assignments
60%
Two programming projects
40%
Lab Topics
Introduction to program design of integer related problems (3 weeks)
Numbers, expressions and simple programs
Word problems
Errors
Design programs
Functions and relations (5 weeks)
Recursive functions and programming
Induction and recursion
Induction on lists and sets
Problem solving
Representing Graphs and Trees (3 weeks)
Symbolic form of a graphs and trees
Programming algorithms on graphs, trees and traversals
Graph, vertex, edge coloring
Shortest path, B-trees
Problem solving
Functions for counting (3 weeks)
Programming algorithms to solve counting problems
Binomial approximation of a random variable
Random tree aggregation
Nearest neighbor network
Problem solving
Sample programming problems (thoughout)
1. Write a program to help find formulae for summations of integer powers and then verify results
using induction.
2. Write a program to count the number of strings of a’s and b’s that do not contain aa. Recognize
the pattern. Write a recursive program to do the same thing. Formally derive and prove the number
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of such strings.
3. Write iterative and recursive programs to create the binomial coefficients and compare with
iterative and inductive proofs of the correctness of these values.
14.
Indicate which of the PROGRAM’S measurable Student Learning Outcomes are addressed
in this course
Demonstrate an ability to apply knowledge of computing and mathematics appropriate to the
discipline. (SLO a) This SLO is addressed particularly in the lecture portion of the class. A strong
background in discrete mathematics is necessary to be successful in computer science.
Demonstrate an ability to analyze a problem, and identify and define the computing requirements
appropriate to its solution. (SLO b) This SLO is mainly addressed in the lab portion of the class. It is
in the lab that students will be able to explore different ways of solving problems under the guidance
of the instructor.
COURSE ALIGNMENT MATRIX
Directions: Assess the how well COMP 256/L contributes to the program’s student learning outcomes by
rating each course objective for that course with an I, P or D.
1. Demonstrate knowledge of basic terms.
2. Demonstrate knowledge of proof techniques.
3. Be able to relate the ideas of induction and recursion.
4. Be able to solve counting problems.
5. Demonstrate knowledge of graph theory and its algorithms.
6. Demonstrate knowledge of trees and algorithms to traverse trees.
7. Be able to formulate and solve problems in discrete math
8. Be able to recognize and utilize proof techniques to solve
problems
9. Be able to model problems in computer science using
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Student Learning Outcome b
Lecture Course Objectives (1-6)
Lab Course Objectives ( 7-10)
Student Learning Outcome a
I=introduced (basic level of proficiency is expected)
P=practiced (proficient/intermediate level of proficiency is expected)
D=demonstrated (highest level/most advanced level of proficiency is expected)
D
P
D
D
D
P
P
I
P
P
I
P
P
P
P
P
P
P
New Course Proposal – Page 7/8
combinations and permutations
10. Be able to model problems in computer science using graphs and
trees
15.
P
P
Assessment of COURSE objectives
Lecture Course Objectives (1-6)
Lab Course Objectives (7 -10)
Assessments of Student Performance
1. Demonstrate knowledge of basic terms.
Exams, quizzes, and homework assignments
2. Demonstrate knowledge of proof techniques.
Exams, quizzes, and homework assignments
3. Be able to relate the ideas of induction and
recursion.
Exams, quizzes, and programming assignments
4. Be able to solve counting problems.
Exams, quizzes, programming assignments and
homework assignments
Exams, quizzes, and homework assignments
5. Demonstrate knowledge of graph theory and its
algorithms.
6. Demonstrate knowledge of trees and
algorithms to traverse trees.
Exams, quizzes, and programming assignments
11. Be able to formulate and solve problems in
discrete math
12. Be able to recognize and utilize proof
techniques to solve problems
13. Be able to model problems in computer
science using combinations and permutations
14. Be able to model problems in computer
science using graphs and trees
Exams, quizzes, and programming assignments
17.
Exams, quizzes, and programming assignments
Exams, quizzes, and programming assignments
Exams, quizzes, and programming assignments
Methods of Assessment for Measurable Student Learning Outcomes
The methods will include pre-tests, post-tests, surveys and other assessment activities as
determined by the department committee responsible for monitoring SLO5 and SLO6 for
compliance of ABET requirements.
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