Industrial Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 15251512 | Free Research 1 | 2025 | Autumn | 7 | 3+0+0 | 0 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | Danışman yönlendirmesi ile |
| Mode of Delivery | Face to Face |
| Prerequisites | Yok |
| Coordinator | Prof. Murat DARÇIN |
| Instructor(s) | Prof. Murat DARÇIN |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Şule ERYÜRÜK | A-306 | [email protected] | 7537 |
Course Content
Based on the fundamental knowledge and practices students have acquired, the aim is to define the research process (problem identification, data collection, data analysis, and interpretation of results), to understand the main scientific research methods, and to grasp the techniques necessary for students to conduct research on a specific topic, including literature review, data collection, data evaluation, and report writing.
Objectives of the Course
This course aims to examine the research process (problem identification, data collection, data analysis, and interpretation of results), review fundamental scientific research methods (qualitative and quantitative), and enable students to learn practical techniques such as literature review, data collection, data evaluation, and report writing necessary for conducting research on a specific topic.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P1 | Knowledge of mathematics, natural sciences, fundamental engineering, computational sciences, and industrial engineering-specific subjects; the ability to apply this knowledge to solve complex industrial engineering problems. | 5 |
| P2 | The ability to define, formulate, and analyze complex industrial engineering problems using fundamental science, mathematics, and engineering knowledge, while keeping in mind the relevant UN Sustainable Development Goals. | 5 |
| P4 | The ability to select and utilize appropriate techniques, resources, and modern engineering and information tools, including estimation and modeling, for the analysis and solution of complex industrial engineering problems, while being aware of their limitations. | 5 |
| P5 | The ability to use research methods, including literature review, experimental design, experiment execution, data collection, analysis, and interpretation of results, to investigate complex industrial engineering problems. | 5 |
| P9 | The ability to communicate effectively, both verbally and in writing, on technical topics, taking into account the diverse differences of the target audience (education, language, profession, etc.). | 5 |
| P11 | Lifelong learning skills encompass the ability to learn independently and continuously, adapt to new and emerging technologies, and think critically about technological change. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Demonstrate knowledge of data collection and data analysis. | P.1.30 | 5,7 |
| O2 | Demonstrate knowledge of data collection and analysis. | P.2.27 | 5,7 |
| O3 | Demonstrate knowledge of data collection and analysis. | P.4.24 | 5,7 |
| O4 | Demonstrate knowledge of data collection and analysis. | P.5.9 | 5,7 |
| O5 | Demonstrate knowledge of academic writing rules for articles and reports. | P.9.8 | 5,7 |
| O6 | Explain the basic concepts of science and research and the research process. | P.11.6 | 5,7 |
| O7 | Discuss scientific methods and their differences. | P.11.7 | 5,7 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Fundamental Concepts of Science and Research |
| 2 | Article Analysis – Part 1 (Literature Review) |
| 3 | Steps in the Research Process |
| 4 | Research Designs - 1 - Qualitative Research Designs |
| 5 | Research Designs - Part 2 - Quantitative Research Designs |
| 6 | Universe and Sample |
| 7 | Data Collection Methods and Tools |
| 8 | Midterm |
| 9 | Data Organization |
| 10 | Statistical Methods in Data Analysis |
| 11 | Reporting of Research Findings |
| 12 | Research and Publication Ethics |
| 13 | Article Analysis |
| 14 | Article Analysis |
| 15 | Presentation |
Textbook or Material
| Resources | Sait Gürbüz ve Faruk Şahin, Sosyal Bilimlerde Araştırma Yöntemleri: Felsefe, Yöntem, Analiz (Ankara: Seçkin, 2018) |
| Ali Yıldırım ve Hasan Şimsek, Sosyal Bilimlerde Nitel Araştırma Yöntemleri (Ankara: Seçkin, 2018) | |
| İ. Esen Yıldırım, İstatistiksel Araştırma Yöntemleri (Ankara: Seçkin, 2017) |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 30 | 30 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 36 | 36 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 150 | ||
| Total Work Load / 30 | 5 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P1 | P2 | P4 | P5 | P9 | P11 |
|---|---|---|---|---|---|---|---|
| O1 | Demonstrate knowledge of data collection and data analysis. | 5 | - | - | - | - | - |
| O2 | Demonstrate knowledge of data collection and analysis. | - | 5 | - | - | - | - |
| O3 | Demonstrate knowledge of data collection and analysis. | - | - | 5 | - | - | - |
| O4 | Demonstrate knowledge of data collection and analysis. | - | - | - | 5 | - | - |
| O5 | Demonstrate knowledge of academic writing rules for articles and reports. | - | - | - | - | 5 | - |
| O6 | Explain the basic concepts of science and research and the research process. | - | - | - | - | - | 5 |
| O7 | Discuss scientific methods and their differences. | - | - | - | - | - | 5 |