ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| Computer Technologies (Evening Education) | |||||
| Associate | TR-NQF-HE: Level 5 | QF-EHEA: Short Cycle | EQF-LLL: Level 5 | ||
Course Introduction and Application Information
| Course Code: | UNI253 | ||||
| Course Name: | Decision Making and Problem Solving Techniques | ||||
| Semester: | Spring | ||||
| Course Credits: |
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| Language of instruction: | Turkish | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | University Elective | ||||
| Course Level: |
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| Mode of Delivery: | E-Learning | ||||
| Course Coordinator: | Dr. Öğr. Üy. TAYFUN UTAŞ | ||||
| Course Lecturer(s): | Tayfun Utaş | ||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | The aim of this course is to provide students with the ability to analyze complex decision-making processes and produce solutions. Throughout the course, students will understand decision-making processes through statistical and optimization models, develop their analytical thinking skills and have the opportunity to apply problem-solving techniques. |
| Course Content: | 1. Decision Making Process and Models 2. Statistical Decision Making Techniques 3. Optimization Models and Solution Techniques 4. Problem Solving Approaches and Techniques 5. Real Life Applications of Decision Making and Problem Solving Techniques |
Learning Outcomes
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The students who have succeeded in this course;
1) Ability to understand and analyze decision-making processes and models. 2) Ability to analyze data through statistical and optimization models. 3) Developing analytical thinking abilities. 4) Ability to apply effective problem solving techniques. 5) Ability to apply decision-making and problem-solving techniques to real-life situations. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Introduction to Decision Making Process and Models | |
| 2) | Statistical Decision Making Techniques - I | |
| 3) | Statistical Decision Making Techniques - II | |
| 4) | Introduction to Optimization Models | |
| 5) | Optimization Solution Techniques - I | |
| 6) | Optimization Solution Techniques - II | |
| 7) | Introduction to Problem Solving Approaches | |
| 8) | Midterm exam | |
| 9) | Problem Solving Techniques - I | |
| 10) | Problem Solving Techniques - II |
Sources
| Course Notes / Textbooks: | 1. Bazerman, M.H. & Moore, D.A. (2012). Judgment in Managerial Decision Making. Wiley. 2. Dyer, J.S. & Watson, G. (2013). Analytic Decision Making. Springer. |
| References: | 1. Hammond, J.S., Keeney, R.L., & Raiffa, H. (2006). Smart Choices: A Practical Guide to Making Better Decisions. Broadway Business. 2. Ullman, D.G. (2010). The Mechanical Design Process. McGraw-Hill. |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
|---|---|---|---|---|---|
| Program Outcomes |
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Midterms | 1 | % 40 |
| Final | 1 | % 60 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
| Course Hours | 14 | 3 | 2 | 70 | |||
| Midterms | 1 | 20 | 2 | 22 | |||
| Final | 1 | 30 | 3 | 33 | |||
| Total Workload | 125 | ||||||