GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
DECISION SUPPORT SYSTEMS/IE464
Course Title: DECISION SUPPORT SYSTEMS
Credits 3 ECTS 4
Course Semester 8 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  English
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
He/she knows what a decision making means and ist application.
He/she knows what a model or data based decision support system
He/she knows spreadsheet-based model building
He/she knows how a solution is produced from a spreadsheet-based environment
He/she knows how to produce user forms
He/she knows designing, development, installation, and application of DSS
He/she knows the applications of what-if analysis
He/she knows the conceptual and applicational difference between DSS and MIS

 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face and laboratory applications
 --WEEKLY SCHEDULE
1. Week  Introduction. Definition of basic concepts about DSS. Decision making and problem solving.
2. Week  Overall structure of the DSS and definition of its components. A framework for DSS. Definition of Excel spreadsheet environment and VBA applications.
3. Week  Knowledge management systems. Expert sistems. Artificial neural networks. Creating subroutines (Procedure or macro) in an VBE environment.
4. Week  Decision making systems, modelling and support. Using VBA's, generating macros and their applications.
5. Week  DSS configurations, characteristics abilities and components. Data management sub-systems. User interface sub-systems. Using VBA's, generating macros and their applications. Knowledge base management sub-systems. Using VBA's, generating macros and their applications.
6. Week  Modeling and analysis. Modeling of management support systems. Certainty, uncertainty and risk. Modeling of management support systems via spreadsheets. Using VBA's, generating macros and their applications.
7. Week  Modelling of mathematical programming and its representation in a spreadsheet environment
8. Week  Midterm
9. Week  What-if (sensitivity) analysis
10. Week  Generating user (dialog) forms
11. Week  Project study- Construction of DSS model base
12. Week  Project study- Construction of DSS model base
13. Week  Project study- Obtaining Solver aided solution and What-if analysis
14. Week  Project study- Obtaining Solver aided solution and What-if analysis
15. Week  Project study- Building DSS structures in VBE
16. Week  Project study- Building DSS structures in VBE
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
2
20
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
14
1
14
 Searching in Internet and Library
14
1
14
 Material Design and Implementation
6
1
6
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
2
5
10
 Final Exam and Preperation for Final Exam
1
5
5
 Other (should be emphasized)
5
2
10
 TOTAL WORKLOAD: 
101
 TOTAL WORKLOAD / 25: 
4.04
 Course Credit (ECTS): 
4
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.X
2Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purposeX
3Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose...X
4Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectivelyX
5Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questionsX
6Ability to work efficiently in intradisciplinary and multi-disciplinary teams; ability to work individuallyX
7Ability to communicate effectively in Turkish, both orally and in writing knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructionsX
8Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herselfX
9Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice .X
10Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable developmentX
11Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions .X
 -- NAME OF LECTURER(S)
   (Assoc.Prof. Mehmet ATAK)
 -- WEB SITE(S) OF LECTURER(S)
   (www.gazi.edu.tr/~matak)
 -- EMAIL(S) OF LECTURER(S)
   (matak@gazi.edu.tr)