FME633 - USING FUZZY LOGIC IN EDUCATION
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| USING FUZZY LOGIC IN EDUCATION | FME633 | Any Semester/Year | 3 | 0 | 3 | 8 |
| Prequisites | - | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Question and Answer Preparing and/or Presenting Reports | |||||
| Instructor (s) | Instructor | |||||
| Course objective | Explain the reasons for the emergence of the concept of fuzzy statistics, fuzzy set, fuzzy logic and fuzzy statistical concepts provide general information about the training aimed to examine the differences between the conventional methods and fuzzy methods. | |||||
| Learning outcomes |
| |||||
| Course Content | Fuzzy Logic and Fuzzy Cluster Concept and Features istatitik Concept, Concept and arithmetic average of the difference between the expected value of Asymptomatic in education to use fuzzy sets, Fuzzy logic and fuzzy to use statistical concepts, Fuzzy method to compare with the classical methods | |||||
| References | Buckley, J.J.; Fuzzy Statistics, Springer, (2004). Dubois, D. and Prade, H.; Fuzzy Sets and Fuzzy Systems, Academic Press, (1980).Buckley, J.J.; Fuzzy Probaility and Statistics, Spriger,(2006). Fuzzy articles related to the basic | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Station Subjects Mathematics Education, The Role |
| Week 2 | Fuzzy Set Concept and Properties |
| Week 3 | The concept of Fuzzy logic |
| Week 4 | Basic concepts of statistical properties of Fuzzy Concept |
| Week 5 | examples of Fuzzy Sets |
| Week 6 | Basic properties in Fuzzy Statistics |
| Week 7 | The basic methods of fuzzy statistics |
| Week 8 | Basic properties in Fuzzy Statistics |
| Week 9 | The basic methods of fuzzy statistics |
| Week 10 | The basic relationship between the classical method and the differences in the methods of fuzzy |
| Week 11 | Comparison of the classical method with fuzzy methods |
| Week 12 | Midterm exam |
| Week 13 | Semester Project Presentations |
| Week 14 | Semester Project Presentations |
| Week 15 | -- |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 2 | 20 |
| Project | 1 | 10 |
| Seminar | 0 | 0 |
| Midterms | 2 | 20 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 4 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 0 | 0 | 0 |
| Presentation / Seminar Preparation | 2 | 25 | 50 |
| Project | 0 | 0 | 0 |
| Homework assignment | 0 | 0 | 0 |
| Midterms (Study duration) | 2 | 50 | 100 |
| Final Exam (Study duration) | 1 | 48 | 48 |
| Total Workload | 19 | 126 | 240 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Has expert level of theoretical and practical knowledge in science and mathematics fields by adhering secondary science and mathematics education undergraduate programs' competencies | X | ||||
| 2. Has advanced knowledge of scientific research methods and techniques. | X | ||||
| 3. As an individual who has science expertise in the education of secondary science and mathematics develops his/her knowledge and examines broadly these knowledge. | X | ||||
| 4. Discusses the relationship between his/her field and other disciplines. | X | ||||
| 5. Uses and develops expert level of theoretical and practical knowledge in fields of science and mathematics education. | X | ||||
| 6. Proposes by using qualitative and quantitative research methods. | X | ||||
| 7. Uses advantage of advance technology in studies related to his/her field. | X | ||||
| 8. Produces new knowledge by integrating knowledge and skills obtained from his/her expertise field with the other knowledge in different fields | X | ||||
| 9. Constructs a problem within its framework with specific plan, develops solutions and evaluate the results which as a result of solution | X | ||||
| 10. Develops new approaches for solving of encountered issues related to field education and produces solution by taking responsibility | X | ||||
| 11. As an individual, who believes in lifelong learning, evaluates his/her knowledge in the field critically. | X | ||||
| 12. Assesses relations related to his/her field with critical approach and guides to develop or change these relations. | X | ||||
| 13. Makes verbal or written communications with colleagues in academic environments by using a foreign language effectively. | X | ||||
| 14. Shares knowledge related to developments and studies in his/her field with different groups as verbal and written at the national or international level | X | ||||
| 15. In field researches, controls and teaches social, scientific and ethical values in the process of data collection, interpretation and dissemination | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest