At the end of this course, the students; 1) Have an ability to select and practice the appropriate methods and technologies on decision problems 2) Have an ability to design a decision support system and its components to meet the requirements 3) Have skill to determine, formulate and solve the semistructured decision problems systematically. 4) Capable of exercising qualitative and quantitative methods within decision support systems 5) Develope a decision support system based on a teamwork
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Decision, data and information in multi-media. Information and knowledge. Structured and semi-structured decisions. Decision making process and cognitive styles of decision makers. Types of DSS. Model management and Solver-based model management in Excel. Data and information management and development of information management in Excel. Diyalog management and user interface implementations in Excel. Data export and import between Access and Excel. Implementation issues.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Decision making process
2nd Week
Decision support systems (DSS)
3rd Week
DSS and Excel - Introduction to Excel, functions, graphics, referencing, pivot tables,...
4th Week
Excel and macros
5th Week
DSS, Model management - Excel object model and VBE
6th Week
DSS, Model management - Excel, modelling and solver addin
7th Week
DSS, Model management - Excel VBA
8th Week
Midterm
9th Week
DSS, Data and information management - Excel range objects
10th Week
DSS, Data and information management - Excel, controls, loops
11th Week
DSS, Data and information management - Excel, user defined fınctions, relational databases
DSS, Diyalog (user interface) management - Excel, forms
14th Week
DSS developement and ve application developement with VBA
RECOMENDED OR REQUIRED READING
Turban, Sharda, Delen, Decision Support Systems and Business Intelligence Systems, 9th edition, Pearson Pub., 2011 Korkmaz, T., Excel 2000 ile Programlama ve Makrolar, ExcelTim, 2003
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture, Homeworks, Lab studies, Project
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
25
Assignment
1
13
Practice
1
13
Project
1
14
Attendance
1
5
Total(%)
70
Contribution of In-term Studies to Overall Grade(%)
70
Contribution of Final Examination to Overall Grade(%)
30
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
Individual or group work
14
2
28
Preparation for Final exam
1
25
25
Course hours
14
3
42
Preparation for Midterm exam
1
25
25
Laboratory (including preparation)
Final exam
1
2
2
Homework
2
8
16
Total Workload
140
Total Workload / 30
4,66
ECTS Credits of the Course
5
LANGUAGE OF INSTRUCTION
English
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)