PSYCHOLOGY
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
SEN2211	Data Structures and Algorithms I	Spring	2	2	3	7

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR
Course Lecturer(s):	Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR RA MERVE ARITÜRK Prof. Dr. NAFİZ ARICA Instructor DUYGU ÇAKIR YENİDOĞAN RA SEVGİ CANPOLAT
Recommended Optional Program Components:	None
Course Objectives:	This is an introductory course on common data structures that are used in software engineering. After completing the course, the student will have knowledge of applying, implementing and analysis of basic data structures, including, lists, stacks and queues. Certain fundamental techniques, such as sorting, searching and recursion are also taught.

Learning Outcomes

The students who have succeeded in this course;
1) Describe and apply basic object oriented programming principles.
2) Implement basic data structures such as linked lists, stacks and queues.
3) Analyze the complexity and efficiency of algorithms.
4) Choose and design data structures for writing efficient programs.
5) Implement recursive algorithms.
6) Describe and implement sorting algorithms on common data structures.
7) Describe and implement search algorithms on common data structures.

Course Content

The course content is composed of object oriented Java review, the complexity and efficiency of algorithms, introduction to list-stack-queue structures, implementing list-stack-queue structures, recursion, searching algorithms and sorting algorithms.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Data Structures and Algorithms Complexity Analysis
2)	Introduction to Linked Lists
3)	Doubly Linked Lists Ordered Linked Lists
4)
5)	Stacks
6)	Stacks for Algebraic Operations
7)	Queues
8)	Queues
9)	Data Structure Classes in Java
10)	Recursion
11)	Recursive Complexity
12)	Searching Algorithms
13)	Sorting Algorithms
14)	Sorting algorithms

Sources

Course Notes / Textbooks:	Data Structures & Problem Solving Using Java (Mark Allen Weiss) Data Structures and Algorithm Analysis in Java (Mark Allen Weiss) Data Structures and Abstractions with Java (Frank Carrano)
References:	Yok

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Laboratory	4	% 20
Quizzes	5	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	28
Laboratory	14	28
Study Hours Out of Class	12	24
Midterms	10	52
Final	5	32
Total Workload		164

Contribution of Learning Outcomes to Programme Outcomes

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

	Program Outcomes	Level of Contribution
1)	To develop an interest in the human mind and behavior, to be able to evaluate theories using empirical findings, to understand that psychology is an evidence-based science by acquiring critical thinking skills.
2)	To gain a biopsychosocial perspective on human behavior. To understand the biological, psychological, and social variables of behavior.
3)	To learn the basic concepts in psychology and the theoretical and practical approaches used to study them (e.g. basic observation and interview techniques).
4)	To acquire the methods and skills to access and write information using English as the dominant language in the psychological literature, to recognize and apply scientific research and data evaluation techniques (e.g. correlational, experimental, cross-sectional and longitudinal studies, case studies).
5)	To be against discrimination and prejudice; to have ethical concerns while working in research and practice areas.
6)	To recognize the main subfields of psychology (experimental, developmental, clinical, cognitive, social and industrial/organizational psychology) and their related fields of study and specialization.
7)	To acquire the skills necessary for analyzing, interpreting and presenting the findings as well as problem posing, hypothesizing and data collection, which are the basic elements of scientific studies.
8)	To gain the basic knowledge and skills necessary for psychological assessment and evaluation.
9)	To acquire basic knowledge of other disciplines (medicine, genetics, biology, economics, sociology, political science, communication, philosophy, anthropology, literature, law, art, etc.) that will contribute to psychology and to use this knowledge in the understanding and interpretation of psychological processes.
10)	To develop sensitivity towards social problems; to take responsibility in activities that benefit the field of psychology and society.
11)	To have problem solving skills and to be able to develop the necessary analytical approaches for this.
12)	To be able to criticize any subject in business and academic life and to be able to express their thoughts.