Psychology
Bachelor	Length of the Programme: 4	Number of Credits: 240	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF: Level 6

ECTS Course Information Package

School/Faculty/Institute

Faculty of Engineering

Course Code

COMP 201

Course Title in English

Data Structures and Algorithms

Course Title in Turkish

Veri Yapıları ve Algoritmalar

Language of Instruction

Type of Course

Exercise,Flipped Classroom,Lecture

Level of Course

Introductory

Semester

Fall

Contact Hours per Week

Lecture: 3

Recitation: none

Lab: 2

Other: none

Estimated Student Workload

152 hours per semester

Number of Credits

6 ECTS

Grading Mode

Standard Letter Grade

Pre-requisites

COMP 109 - Computer Programming (JAVA)

Co-requisites

None

Expected Prior Knowledge

Basic object-oriented programming knowledge

Registration Restrictions

Only undergraduate students

Overall Educational Objective

To learn fundamentals of data structures and how to design and implement data structures to solve basic engineering problems in Java programming language.

Course Description

This course covers the fundamentals of data structures and algorithms such as lists, stacks, queues, heaps, trees, hashing, sorting algorithms, and application of these concepts using Java programming language.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) Comprehend basic data structure concepts;
2) Design algorithms using data structures;
3) Implement data structures to solve engineering problems;
4) Analyze and report the results of implemented solution.

Program Learning Outcomes/Course Learning Outcomes	1	2	3	4
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None	S Supportive	H Highly Related

	Program Outcomes and Competences	Level	Assessed by
1)	Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.	N
2)	Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.	N
3)	Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.	H	Exam,HW,Participation
4)	Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.	N
5)	Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.	N
6)	Internalization and dissemination of professional ethical standards.	N
7)	Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.	N
8)	Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).	N
9)	Recognition, understanding, and respect for the complexity of sociocultural and international diversity.	S	Participation
10)	Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.	S	HW,Participation
11)	Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.	N
12)	Ability to acquire knowledge independently, and to plan one’s own learning.	S	Exam,HW
13)	Demonstration of advanced competence in the clarity and composition of written work and presentations.	H	Exam,HW

Prepared by and Date	, October 2024
Course Coordinator	YASSINE DRIAS
Semester	Fall
Name of Instructor	Asst. Prof. Dr. YASSINE DRIAS

Course Contents

Week	Subject
1)	Introduction to Data Structures
2)	Abstract Classes and Interfaces
3)	Generics
4)	Lists (Part 1)
5)	Lists (Part 2)
6)	Stacks
7)	Queues
8)	Algorithmic complexity
9)	Heaps and Priority Queues
10)	Hashing
11)	Recursion
12)	Trees (Part 1)
13)	Trees (Part 2)
14)	Algorithm design using data structures
15)	Final Exam/Project/Presentation Period
16)	Final Exam/Project/Presentation Period

Required/Recommended Readings

Intro. to Java Programming: Comprehensive Ed. (11th Ed., Pearson, 2019), Daniel Liang. Data Structures and Algorithms in Java, Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, Adison Wesley 6th Edition

Teaching Methods

Flipped classroom. Students work individually for assignments.

Homework and Projects

Assignments

Laboratory Work

Laboratory study

Computer Use

Required

Other Activities

None

Assessment Methods

Assessment Tools	Count	Weight
Homework Assignments	1	% 15
Midterm(s)	2	% 50
Final Examination	1	% 35
TOTAL		% 100

Course Administration

driasy@mef.edu.tr
0 212 395 37 45
Instructor’s office: 5th floor, Phone number: 0 212 395 37 45 Office hours: After the lecture hours. E-mail address: driasy@mef.edu.tr Exams: Closed book and closed notes. Rules for attendance: YÖK regulations. Missing a midterm: You are expected to be present without exception and to plan any travel around these dates accordingly. Medical emergencies are of course excluded if accompanied by a doctor’s note. A note indicating that you were seen at the health center on the day of the midterm/quiz is not a sufficient documentation of medically excused absence from the midterm/quiz. The note must say that you were medically unable to take the midterm/quiz. Provided that proper documents of excuse are presented, a make-up for the missing midterm/quiz will be given. If you fail to take the midterm/quiz on the assigned day and do not have a valid excuse, you will be given zero (0) on the midterm/quiz. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Eligibility to take the final exam: No final exam. Missing a final: No final exam. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations

ECTS Student Workload Estimation

Activity	No/Weeks	Hours			Calculation
	No/Weeks per Semester	Preparing for the Activity	Spent in the Activity Itself	Completing the Activity Requirements
Course Hours	14	1	5		84
Project	4	1	16		68
Total Workload					152
Total Workload/25					6.1
ECTS					6