Computer Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

CENG110

Course Name:

Discrete Structures

Course Semester:

Spring

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr. FERİT TOSKA

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:

This course provides a systematic exploration of the fundamental concepts of discrete mathematics, which constitute the foundation of computer engineering. It is designed to develop students’ skills in logical reasoning and proof techniques, while fostering their ability to apply principles from set theory, relations and functions, combinatorial counting methods, recursive sequences, graph and tree structures, Boolean algebra, and finite state machines to the formulation and solution of engineering problems.

Course Content:

The purpose of the Discrete Structures course is to provide students with the basic mathematical infrastructure unique to computer engineering.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Analyzes and solves computer engineering problems by applying logical propositions and proof techniques, particularly mathematical induction and deductive reasoning.
2) Formulates and solves problems related to mathematical models by utilizing fundamental discrete structures such as sets, relations, and functions.
3) Models problems using graph and tree data structures and applies fundamental graph algorithms (e.g., traversal, spanning tree construction) to solve them.
4) Solves problems related to digital logic circuits and basic automata theory by applying Boolean algebra and finite state machines.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Logical propositions, introduction to Boolean logic, and proof techniques (including mathematical induction).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
2)	Set theory; set operations, relations, and functions.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
3)	Principles of combinatorial counting (permutations, combinations, binomial coefficients) and basic counting techniques.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
4)	Mathematical induction and recursive sequences; solving recurrence relations.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
5)	Introduction to graph theory (definitions and fundamental concepts).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
6)	Graph algorithms – traversal and search methods (BFS, DFS, etc.).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
7)	Tree structures and their types (rooted trees, binary trees, etc.).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
8)	Spanning trees and basic graph applications.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
9)	Midterm Exam
10)	Boolean algebra and fundamental concepts of logic circuits.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
11)	Algebraic structures (groups, semigroups, rings) and their applications in discrete mathematics.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
12)	Finite state machines and fundamentals of automata theory (deterministic and nondeterministic automata).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
13)	Applications of discrete mathematics and examples in algorithms (applications of graph algorithms, etc.).	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
14)	General review, problem-solving sessions, and project presentations.	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.
15)	Final Exam

Sources

Course Notes / Textbooks:	Discrete Mathematics, 2nd Ed., Kenneth Ross & Charles Wright, Prentice Hall Seymour Lipschutz, Marc Lipson, “Discrete Mathematics (Schaum’s Outlines)”
References:	Discrete Mathematics and Its Applications 4th ed. Kenneth H. Rosen, McGraw-Hill.

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4
Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in oral and written communication; at least one foreign language knowledge.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Professional and ethical responsibility.
10) Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11) Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.	5
2)	The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.	4
3)	The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4)	Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5)	Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems.
6)	The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7)	Effective communication skills in oral and written communication; at least one foreign language knowledge.
8)	Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9)	Professional and ethical responsibility.
10)	Information on project management and practices in business life such as risk management and change management; awareness about entrepreneurship, innovation and sustainable development.
11)	Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions.

Learning Activity and Teaching Methods

Expression
Brainstorming/ Six tihnking hats
Individual study and homework
Lesson
Reading
Homework
Problem Solving
Q&A / Discussion
Web Based Learning

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Observation

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Attendance	1	% 5
Quizzes	3	% 21
Midterms	2	% 34
Final	1	% 40
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Study Hours Out of Class	14	4	56
Quizzes	3	1	3
Midterms	2	10	20
Final	1	20	20
Total Workload			144