Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
DECISION SUPPORT SYSTEMS AYBS304 6. Semester 0 + 0 0 5.0

Prerequisites None

Language of Instruction Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Mode of delivery Computer applications to make concrete the learned basic concepts and examples to strengthen after introducing them
Course Coordinator
Instructors
Assistants
Goals Founding the necessary theoretical background undergraduate and graduate teaching, helping decision makers to use structured and semi-structured data and models, teaching students how to solve problems of a decision support system that is computer based and interactive system in their duties.
Course Content Data-information-decision theory and their properties, decision structures, information systems, decision support system, components of decision support system, the method of data and model, relationship between decision support system and managerial information system in decision making, operation research in decision support system, analytical, hierarchy method,introduction to expert systems, the use of data mining and data warehouses for decision process.
Learning Outcomes 1) Produces the connection between decision support system and managerial information system in decision making
2) Plays an active role in the using of data mining and data stocks for decision process
3) Analytical tools (mathematical models and algorithms), information based intuitive approaches special to the problem at the hand to solve the problem in the decision support system, equipped with theory and application to analyze and interpreting the same structures which permit to use them together
4) Creates a course of action by combining data, models, software interface and users in effective decision making system
5) Generates effective decisions by keeping to the course of action
6) Interpretations by generating solutions which support the administrative provisions

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Data-information-decision theories Lecture

 Presentation (Including Preparation Time)
2. Week Decision structures Lecture

 Presentation (Including Preparation Time)
3. Week Information systems Lecture

 Presentation (Including Preparation Time)
4. Week Decision support system Lecture

 Presentation (Including Preparation Time)
5. Week Components of decision support system Lecture

 Presentation (Including Preparation Time)
6. Week Data and model management Lecture

 Presentation (Including Preparation Time)
7. Week The connection between decision support system and managerial information system Lecture

 Presentation (Including Preparation Time)
8. Week The connection between decision support system and managerial information system Lecture

 Presentation (Including Preparation Time)
9. Week Operational research in decision support system Lecture

 Presentation (Including Preparation Time)
10. Week Analytic, hierarchy management Lecture

 Presentation (Including Preparation Time)
11. Week Introduction to expert systems Lecture

 Presentation (Including Preparation Time)
12. Week Data stocks Lecture

 Presentation (Including Preparation Time)
13. Week The importance of data mining in decision support system Lecture

 Presentation (Including Preparation Time)
14. Week The use of data mining and data stocks for decision support systems Lecture

 Presentation (Including Preparation Time)

Sources Used in This Course
Recommended Sources
Mockler, R.J., (1992). Developing Knowledge-Based Systems Using an Expert System Shell, Maxwell Macmillan.
Olson, D.L., and Courtney, J.F., (1992). Decision Support Models and Expert Systems, Maxwell Macmillan International Editions.
Turban, E., (1988). Decision Support and Expert Systems: Managerial Perspectives, Macmillan, London

Assessment
Measurement and Evaluation Methods and Techniques
Capturing students’ constant interest by giving homework and asking questions which require knowledge and skill in mid term and final exams
Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3DK4DK5DK6
PY15555555
PY25555555
PY35555555
PY45555555
PY75555555

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 4
Work Hour outside Classroom (Preparation, strengthening) 14 3
Homework 1 28
Midterm Exam 1 2
Time to prepare for Midterm Exam 1 14
Final Exam 1 2
Time to prepare for Final Exam 1 16
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
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Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload