Information Package / Course Catalogue
IE 104 Computational Methods for IE
MEF University
Degree Programs
Psychology
General Information For Students
Diploma 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 104
Course Title in English Computational Methods for IE
Course Title in Turkish Endüstri Mühendisliği için Hesaplama Yöntemleri
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Select
Semester Spring
Contact Hours per Week
Lecture: 3 Recitation: 0 Lab: 0 Other: 0
Estimated Student Workload 152 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites COMP 103 - Computer Programming | COMP 105 - Computer Programming (C) | COMP 109 - Computer Programming (JAVA)
Expected Prior Knowledge Prior knowledge on computer programming fundamentals and structures
Co-requisites None
Registration Restrictions Only Undergraduate Students
Overall Educational Objective
Course Description This course explores the design and implementation of decision support systems (DSS) using Excel & VBA. The following topics are covered: Excel basics & formatting; referencing & names for cells, worksheets, workbooks; R1C1 notation; functions & formulas; auditing; creating charts & sparklines; chart tools; pivot tables & charts; performing statistical analysis & solving mathematical models using Excel; working with large data in Excel; Visual Basic environment; recording macros; properties, methods, referencing & formulas in VBA; objects & variables; sub & function procedures; programming structures; arrays; debugging; creating user interface; DSS development process; graphical user interface design; case studies in DSS
Course Description in Turkish Bu ders, Excel & VBA kullanarak karar destek sistemlerinin (KDS) tasarımını ve uygulamaya konulmasını inceler. Ders boyunca Excel’in temel öğeleri & biçimlendirme; hücre, çalışmasayfası, çalışma kitabı için referanslama & isimler; R1C1 notasyonu; fonksiyonlar & formüller; denetim; şema & küçük grafikler oluşturma; şema araçları; özet tablo & şemalar; Excel kullanarak istatistiksel analiz yapma & matematiksel modeller çözme; Excel’de büyük veri ile çalışma; Visual Basic ortamı; makro kaydetme; VBA’da özellikler, yöntemler, referanslama & formüller; nesne & değişkenler; alt & fonksiyon prosedürleri; programlama yapıları; dizinler;hata ayıklama; kullanıcı arayüzü oluşturma; KDS geliştirme süreci; grafiksel kullanıcı arayüzü tasarımı; KDS’de vaka çalışmaları konuları işlenir.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) Identify, define and explain key concepts and problem-solving processes in a given complex business case
2) Design a spread-sheet based solution framework to a given engineering problem;
3) Prepare a project report to demonstrate his/her spread-sheet knowledge and analysis skills
4) Function effectively as a member of a team and demonstrate team leadership during term project
5) Present the report and the results of the project
6) Apply, use and show basic spreadsheet features, functions, and methods
7) Demonstrate his/her coding skills using VBA.
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6 7
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 EVREN GÜNEY , April 2021
Course Coordinator EVREN GÜNEY
Semester Spring
Name of Instructor Assoc. Prof. Dr. EVREN GÜNEY

Course Contents

Week Subject
1) Introduction to decision support systems (DSS), Excel Basics and Formatting
2) Referencing and Names, Functions and Formulas
3) Functions and formulas (continued)
4) Charts and Sparklines, Pivot Tables
5) Statistical Analysis
6) The Solver & other tools, working with large data
7) Introduction to VBA, Recording Macros
8) Objects and Variables
9) Objects and Variables, Sub procedures and function procedures
10) Programming structures
11) Programming structures, Arrays
12) User Interface
13) DSS Development Process, GUI Design
14) GUI Design and case studies
15) Final Exam/Project/Presentation Period
16) Final Exam/Project/Presentation Period
Required/Recommended ReadingsEkşioğlu, S. D., Şeref, M.M.H., Ahuja, R.K., Winston, W.L. (2011). Developing Spreadsheet-Based Decision Support Systems (2nd Edition). Belmont, Massachusetts: Dynamic Ideas
Teaching MethodsLectures/contact hours using “flipped classroom” as an active learning technique
Homework and Projectsweekly assignments over Pearson My ITLAB, 1 group project (consisting of 2-3 students
Laboratory WorkComputer laboratory
Computer UseMS Excel (preferably 2016 or later version), Visual Basic for Applications
Other Activitiesnone
Assessment Methods
Assessment Tools Count Weight
Quiz(zes) 10 % 20
Homework Assignments 10 % 20
Midterm(s) 1 % 30
Final Examination 1 % 30
TOTAL % 100
Course Administration guneye@mef.edu.tr

Rules for attendance: Minimum attendance requirement is 70%. Missing a Homework/Project: N/A. Missing the 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, a make-up exam will be given for each missed midterm. 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. Missing the Final: Faculty regulations. Eligibility to enter the final exam: Students are required to achieve 40% success rate in midterm and assignment. 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 ) Disclaimer: The instructor reserves the right, when necessary, to alter the grading policy, change examination dates, and modify the syllabus and course content. Modifications will be announced in class. Students are responsible for the announced changes.

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 1 70
Project 1 20 10 30
Homework Assignments 10 1 2 30
Midterm(s) 1 20 2 22
Total Workload 152
Total Workload/25 6.1
ECTS 6