Basic Information

Course Code:

CS 1006

Course Name:

Discrete Computational Structures I

Language of Instruction:

English

Course Type:

Class

Course Level:

Bachelor

ECTS:

3.00

Instructor:

Dr. Öğr. Üyesi Aslı BAY

Course Objectives

The main objective of this course is to provide the students with a knowledge of theoretical foundations of problem solving and experience in working with discrete computational structures common in computer science and computational problems.

Course Content

Introduction to the main concepts of discrete computational structures. Overview of formal tools for mathematical reasoning and proof construction. A thorough discussion of mathematical induction and how it relates to problem solving, algorithm design and program verification. Discussion on recursion, basic counting principles and combinatorial analysis.

Prerequisites / Corequisites

None.

Course Books / Materials / Recommended Resources

DISCRETE MATHEMATICS AND ITS APPLICATIONS, KENNETH H.ROSEN, MCGRAW HİLL, 6 TH Edition, 2007.

Learning Outcomes

Code	Description
LO1	Interpret main principles of formal mathematical reasoning as applied to computational structures
LO2	Prove propositions related to discrete structures
LO3	Apply mathematical induction on discrete structures to design algorithmic solutions to combinatorial problems
LO4	Employ recursion to combinatorial problems
LO5	Analyse discrete structures common in computer science and engineering such as sets, permutations and use basic counting principles

Weekly Course Content

Week	Content
1	Face-to -face ( 2 hours )

Workload Calculation

Activity	Count	Duration (Hours)	Total
Attendance	14	2.00	28.00
Pre-Class Individual Study	14	1.00	14.00
Midterm Exam/Preparation	1	3.50	3.50
Final Exam/Preparation	1	7.50	7.50
Homework	4	8.00	32.00
Other	1	5.00	5.00
Total Workload (Hours)			90
ECTS Credit (Workload / 25)			3

Assessment

#	Assessment Type	Contribution (%)
1	Midterm Exam	%40
2	Final Exam	%60
TOTAL		%100

PO - LO Matrix

PO \ LO	LO1	LO2	LO3	LO4	LO5
PO-1
PO-2
PO-3
PO-4
PO-5
PO-6
PO-7
PO-8
PO-9
PO-10
PO-11

1

Low Contribution

2

Medium Contribution

3

High Contribution

Teaching and Learning Methods

#	Method Name	Description	Tools
1	Lecture (expository teaching), interactive discussion	Listening and taking notes.	Standard classroom technologies, multimedia tools (projector, computer, digital presentations)
2	Brainstorming	The purpose of forming pairs is to ensure that they are open to innovation during the idea generation phase	Standard classroom technologies, multimedia tools, projector, computer, overhead projector
3	Problem Solving	* Analyzing physical and physiological problems using problem-solving techniques and developing appropriate solutions.
4	Homework	Solving and analyzing homework questions using a computer and Excel.	Computer

Academic Integrity and Artificial Intelligence

Students are expected to comply with the principles of academic integrity within the scope of this course. Cheating, plagiarism, or presenting someone else’s work as one’s own is against academic ethical rules. Artificial intelligence tools may only be used for supportive purposes and should be evaluated in a way that supports the student’s own learning process.

Sustainable Development Goals