Faculty Of Engıneerıng
Industrıal Engıneerıng (Englısh)
Course Information
| MANAGEMENT SUPPORT SYSTEMS | |||||
|---|---|---|---|---|---|
| Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
| Hour / Week | |||||
| INE324 | Spring | 3 | 0 | 3 | 3 |
| Prerequisites and co-requisites | None |
|---|---|
| Language of instruction | English |
| Type | Required |
| Level of Course | Bachelor's |
| Lecturer | Lect. Volkan Kadir GÜNGÖR |
| Mode of Delivery | Face to Face |
| Suggested Subject | None |
| Professional practise ( internship ) | None |
| Objectives of the Course | The aim of this course is to teach the basic information about management support systems and skills that may be necessary to the students when they take part in product planning, industrial design and identifying customer needs. |
| Contents of the Course | This course examines the principles, categories, development and use of a specific set of information systems for supporting management decisions at all levels in an organization for faster and better decisions. It involves both theoretical and practical aspects of management support systems. The course starts with a discussion of the decision making styles and decisional needs of managers. Then it relates distinct management support systems (MSS) to those styles and needs. Among the systems studied are data-, model-, knowledge- and document-driven decision support systems (DSS): executive support systems (ESS): group decision support systems (GDSS): and Web-based DSS. In addition, the course investigates the principles and business uses of artificial intelligence (AI) applications: expert systems, fuzzy logic, pattern recognition, genetic algorithms, artificial neural networks, data-, text- and Web-mining, and intelligent software agents. Finally, a discussion of the justification and development of MSS followed by a look into their future and business intelligence trends closes the course. |
Learning Outcomes of Course
| # | Learning Outcomes |
|---|---|
| 1 | Student will get ability to use decision support systems |
| 2 | Student will get ability to investigate data structure |
| 3 | Student will gain the ability of how to implement real time applications |
| 4 |
Course Syllabus
| # | Subjects | Teaching Methods and Technics |
|---|---|---|
| 1 | Decision Support Systems | Lecturing |
| 2 | Decision Making, Systems, Modeling | Lecturing |
| 3 | Decision Support System (DSS) Concepts, Methodologies, and Technologies | Lecturing |
| 4 | Modeling and Analysis | Lecturing |
| 5 | Data Preparation and Data Exploration | Lecturing |
| 6 | Data Warehouses and Data Marts | Lecturing |
| 7 | Midterm Exam | Exam |
| 8 | Artificial Neural Networks (ANN) | Lecturing |
| 9 | Data Mining | Lecturing |
| 10 | Text and Web Mining | Lecturing |
| 11 | Business Performance Management (BPM) | Lecturing |
| 12 | Artificial Intelligence (AI) and Expert Systems (ES) | Lecturing |
| 13 | Advanced Intelligent Systems | Lecturing |
| 14 | Collaborative Computer-Supported | Lecturing |
| 15 | Technologies and Group Support Systems (GSS) | Lecturing |
| 16 | Final Exam | Exam |
Course Syllabus
| # | Material / Resources | Information About Resources | Reference / Recommended Resources |
|---|---|---|---|
| 1 | Marcomini, Antonio, Suter II, Glenn Walter, Critto, Andrea (Eds.), Decision Support Systems for Risk-Based Management of Contaminated Sites, 1st Edition,2008 |
Method of Assessment
| # | Weight | Work Type | Work Title |
|---|---|---|---|
| 1 | 40% | Mid-Term Exam | Mid-Term Exam |
| 2 | 60% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
| # | Learning Outcomes | Program Outcomes | Method of Assessment |
|---|---|---|---|
| 1 | Student will get ability to use decision support systems | 9 | 1͵2 |
| 2 | Student will get ability to investigate data structure | 2͵9 | 1͵2 |
| 3 | Student will gain the ability of how to implement real time applications | 4͵9 | 1͵2 |
| 4 |
Work Load Details
| # | Type of Work | Quantity | Time (Hour) | Work Load |
|---|---|---|---|---|
| 1 | Course Duration | 14 | 3 | 42 |
| 2 | Course Duration Except Class (Preliminary Study, Enhancement) | 14 | 2 | 28 |
| 3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
| 4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
| 5 | Document/Information Listing | 0 | 0 | 0 |
| 6 | Workshop | 0 | 0 | 0 |
| 7 | Preparation for Midterm Exam | 1 | 3 | 3 |
| 8 | Midterm Exam | 1 | 3 | 3 |
| 9 | Quiz | 0 | 0 | 0 |
| 10 | Homework | 1 | 5 | 5 |
| 11 | Midterm Project | 0 | 0 | 0 |
| 12 | Midterm Exercise | 0 | 0 | 0 |
| 13 | Final Project | 0 | 0 | 0 |
| 14 | Final Exercise | 0 | 0 | 0 |
| 15 | Preparation for Final Exam | 1 | 6 | 6 |
| 16 | Final Exam | 1 | 3 | 3 |
| 90 | ||||