IE 304 SimulationMEF UniversityDegree Programs PsychologyGeneral Information For StudentsDiploma SupplementErasmus Policy Statement
Psychology
Bachelor Length of the Programme: 4 Number of Credits: 240 TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF: Level 6

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Faculty of Engineering
Course Code IE 304
Course Title in English Simulation
Course Title in Turkish Simülasyon
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Select
Semester
Contact Hours per Week
Lecture: 3 Recitation: Lab: 1 Other:
Estimated Student Workload 155 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites MATH 222 - Probability and Statistics for Engineering II | MATH 228 - Probability and Statistics for Engineering II
Expected Prior Knowledge Basic probability and statistics knowledge
Co-requisites None
Registration Restrictions MATH 228
Overall Educational Objective To learn the basic simulation modeling and programming concepts
Course Description This is a hands-on course on simulation for undergraduate students. The course includes simulation modeling and programming in general-purpose languages. The use of simulation for estimation, comparison of alternatives and optimization will be addressed. The course covers random number generation and testing, input data analysis, simulation model validation and verification, discrete event simulation, statistical output analysis and experimental design.
Course Description in Turkish Lisans öğrencileri için uygulamalı bir simülasyon dersidir. Genel-amaçlı diller kullanarak simülasyon modelleme ve programlamayı içerir. Tahmin, alternatiflerin karşılaştırılması ve optimizasyon için simülasyonun kullanımı anlatılacaktır. Bu ders şu konuları içerir; rassal sayı yaratma ve test etme, girdi verisi analizi, simülasyon model doğrulama ve kanıtlama, ayrık vaka simülasyonu, istatistiksel çıktı analizi ve deney tasarımı.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) understand basic concepts in real systems to translate them into simulation models;
2) design conceptual representations of real systems to describe simulation models;
3) validate and verify discrete event simulation models using modern tools;
4) analyze and compare simulation outputs using statistical tools;
5) create what-if scenarios for evaluating alternatives for the systems models are built;
6) conduct experiments in simulation according to established procedures and report the results;
7) function effectively as a member of a team; organize and deliver effective verbal, written, virtual, and graphical communications;
8) suggesting solution alternatives for problems in systems and creating and evaluating performance metrics;
9) expressing simulation models and their outputs with different levels of detail for user needs;
10) transforming, analyzing and interpreting data collected for simulation model building.
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6 7 8 9 10
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 UTKU KOÇ , December 2020
Course Coordinator UTKU KOÇ
Semester
Name of Instructor Asst. Prof. Dr. UTKU KOÇ

Course Contents

Week Subject
1) Introduction to simulation modeling
2) Random number generation
3) Testing random number generators
4) Random variate generation
5) Input data analysis
6) Simulation model validation and verification
7) Discrete Event Simulation using software (basic operations)
8) Discrete Event Simulation using software (detailed operations)
9) Discrete Event Simulation using software (intermediate modeling)
10) Discrete Event Simulation using software (Entity Transfer)
11) Statistical output analysis for terminating simulations
12) Statistical output analysis for steady state simulations
13) Experimental design and simulation optimization
14) Project presentations
15) Final Exam/Project Presentation Period
16) Final Exam/Project Presentation Period
Required/Recommended Readings• Kelton, W. D., Sadowski, R. P., and Zupick, N. B., Simulation with Arena, 6th Ed., McGraw Hill, 2015 • Banks, J., Carson, J. S., Nelson, B. L., and Nicol, D. M., Discrete-Event System Simulation, 4th Ed., Prentice Hall, 2005 - J.Shalliker, C.Ricketts (2009) An Introduction to Simulation in the Manufacturing Industry using SIMUL8 2008. E-Book.
Teaching MethodsLectures/contact hours using “flipped classroom” as an active learning technique/Implementation at a Computer Laboratory
Homework and ProjectsA complete simulation project will be completed in groups of students
Laboratory WorkImplementation of the methods learned in class
Computer UseSIMUL8 software
Other Activities
Assessment Methods
Assessment Tools Count Weight
Quiz(zes) 4 % 15
Project 1 % 30
Midterm(s) 1 % 25
Final Examination 1 % 30
TOTAL % 100
Course Administration

Exams and quizzes: Closed book and closed notes. Homework: N/A Rules for attendance: YÖK regulations. You are responsible for the announcements made in class. Rules for late submission of assignments: N/A Missing a quiz: No make-up will be given for the missed quizzes. For certain excuses (decided by the instructor) the percentage of the missed quiz may be added to the midterm or to the final. 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 exam is not a sufficient documentation of medically excused absence from the exam. The note must say that you were medically unable to take the exam. Provided that proper documents of excuse are presented, missed midterm by the student will be given the grade of the final exam. No make-up will be given. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Eligibility to take the final exam: YÖK regulations. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations (http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf)

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 3 56
Laboratory 14 1 1 28
Project 1 20 1 21
Quiz(zes) 4 3 1 16
Midterm(s) 1 10 2 12
Final Examination 1 20 2 22
Total Workload 155
Total Workload/25 6.2
ECTS 6