syllabus
1. Information regarding the programme
1.1 Higher education institution 	Babeş Bolyai University	
1.2 Faculty	Faculty of Mathematics and Computer Science	
1.3 Department	Department of Computer Science	
1.4 Field of study	Computer Science	
1.5 Study cycle	Master	
1.6 Study programme / Qualification 	Component-Based Programming	

2. Information regarding the discipline 
2.1 Name of the discipline	Decision Support Systems	
2.2 Course coordinator 	Lecturer Professor PhD. Prejmerean Vasile	
2.3 Seminar coordinator	Lecturer Professor PhD. Prejmerean Vasile	
2.4. Year of study	2	2.5 Semester	3	2.6. Type of evaluation	E	2.7 Type of discipline	Compulsory	

3. Total estimated time (hours/semester of didactic activities) 
3.1 Hours per week 	3	Of which: 3.2 course	2	3.3 seminar/laboratory	1 / -	
3.4 Total hours in the curriculum 	36	Of which: 3.5 course	24	3.6 seminar/laboratory	12 / -	
Time allotment:	hours	
Learning using manual, course support, bibliography, course notes	36	
Additional documentation (in libraries, on electronic platforms, field documentation) 	36	
Preparation for seminars/labs, homework, papers, portfolios and essays	36	
Tutorship	20	
Evaluations	24	
Other activities: Project	12	
3.7 Total individual study hours 	164	
3.8 Total hours per semester	200	
3.9 Number of ECTS credits	8	

4. Prerequisites (if necessary)
4.1. curriculum	•	Ability to work with an integrated development environment	
4.2. competencies	•	Average programming skills in a visual programming language	

5. Conditions (if necessary)
5.1. for the course	•	An LCD projector	
5.2.  for the seminar /lab activities	•	Laboratory with twelve computers; high level programming language environment	

6. Specific competencies acquired 
Professional competencies	•	Ability to apply knowledge of computing and mathematics appropriate to the discipline;
•	Ability to analyze a problem, and identify and define the computing requirements appropriate to its solution;
•	Ability to identify and to specify computing requirements of an application and to design, implement, evaluate, and justify computational solutions;
•	Ability to use current techniques and skills to integrate available theory and tools necessary for applied computing practices.	
Transversal competencies	•	Ability to apply mathematical foundations, algorithmic principles, and computer science theory;
•	Ability to apply design and development principles in the construction of software systems;
•	Ability to acquire knowledge properly in an application domain in the modeling and design;
•	Ability to work effectively in a team.	

7. Objectives of the discipline (outcome of the acquired competencies)
7.1 General objective of the discipline
	•	Good understanding of hands-on applications;
•	Be able to identify meaningful applied computing problems ;
•	Be able to apply theories, principles and concepts with technologies to design, develop, and verify computational solutions;	
7.2 Specific objective of the discipline	•	Knowledge about general theory and specific DSS theory;
•	Systematic knowledge about what the designer of a DSS needs to know;	

8. Content
8.1 Course	Teaching methods	Remarks	
1. The concept of Decision Support Systems (DSS)
  - The Steps of Decision Support, Classification of Problems
  - The Components of a DSS.
  - Some Computerized Tools for Decision Support	Expositions: description, explanation, introductive lectures, 
Other methods: case study; company examples.		
2. Computerized Decision Support
  -  Decision Making - Rational Decisions, Definitions of Rationality, Bounded Rationality and Muddling Through
  - Models, The Facilities of Models , Phases of the Decision-Making Process	Expositions: description, explanation, class lectures,
Use of problems: use of problem questions, problems and problem situations. 
Other methods: company examples.		
3. The Nature of Managers, Appropriate Data Support, Information Processing Models. 
Group Decision Making	Expositions: description, explanation, dialog-based lectures, current lectures, 
Use of problems: problems and problem situations. 		
4. Decisions and Decision Modeling - Types of Decisions.
  - Human Judgment and Decision Making. 
  - Modeling Decisions. Components of Decision Models	Expositions: description, explanation, class lectures, dialog-based lectures, current lectures. 
Other methods: case study; company examples, discussion of material.		
5. Normative Systems 
  - Normative and Descriptive Approaches. 
  - Decision-Analytic Decision Support Systems. 
  - Equation-Based and Mixed Systems	Expositions: description, explanation, class lectures, dialog-based lectures, lectures.
Other methods: discussion of material.		
6. Data Component 
  - Characteristics of Information. 
  - Databases to Support Decision Making. 
  - Database Management Systems	Expositions: description, explanation, class lectures, dialog-based lectures, current lectures. 
Use of problems: use of problem questions, problems and problem situations. 		
7. Data Warehouses. 
  - Data Mining and Intelligent Agents	Expositions: description, explanation, class lectures.
Use of problems: use of problem questions.		
8. Model Component 
  - Models, Representation, Methodology	Expositions: description, explanation, class lectures, current lectures. 
Other methods: case study; company examples, discussion of 		
9. Model Based Management Systems, Access to Models, and Understandability of Results. 
  - Integrating Models, Sensitivity of a Decision	Expositions: description, explanation, class lectures.
Other methods: discussion of material (using and managing information and decision support systems)		
10. Intelligence and Decision Support Systems 
  - Programming Reasoning 
  - Backward Chaining Reasoning and Forward Chaining Reasoning. 
    Knowledge Representation for Decision Support Systems  
  - Computational Intelligence for Decision Support, 
  - Expert Systems and Artificial Intelligence in Decision Support Systems	 Expositions: description, explanation, class lectures, dialog-based lectures.
Conversations: debate, dialog, conversations for knowledge consolidation, conversations to systematize and synthesize knowledge. 
Discovery: inductive discovery, deductive discovery. 
Other methods: case study; cooperation, company examples.		
11. User Interfaces to Decision Support Systems. 
  - Support for Model Construction and Model Analysis.
  - Support for Reasoning about the Problem Structure in Addition to Numerical Calculations. 
  - Support for Both Choice and Optimization of Decision Variables	Expositions: description, explanation, class lectures, dialog-based lectures, current lectures. 
Other methods: case study; cooperation, company examples, discussion of material.		
12.	Graphical Interface 
  - The Action Language, Menus. 
	 Mail Component 
  - Integration of Mail Management. 
  - Implications for DSS Design	Expositions: description, explanation, class lectures, current lectures, synthesis lectures. 
Conversations: conversations for knowledge consolidation, conversations to systematize and synthesize.		
Bibliography
1. Alter, S. L. Decision support systems: current practice and continuing challenges. Reading, Mass., Addison-Wesley Pub., 1980.
2. Delic, K.A., Douillet,L. and Dayal, U. "Towards an architecture for real-time decision support systems:challenges and solutions, 2001.
3. Druzdzel, M. J. and R. R. Flynn. Decision Support Systems. Encyclopedia of Library and Information Science. A. Kent, Marcel Dekker, Inc., 1999 
4. Finlay, P. N., Introducing decision support systems. Oxford, UK Cambridge, Mass., NCC Blackwell; Blackwell Publishers, 1994.
5. French, S. and Geldermann, J. The varied contexts of environmental decision problems and their implications for decision support. Environmental Science and Policy 8 (2005), 378-391.
6. French, S., Carter, E., and Niculae, C. Decision support in nuclear and radiological emergency situations: Are we too focused on models and technology? International Journal of Risk Assessment and Management (2007).
7. Gachet, A. Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF, 2004. 
8. Gadomski, A.M. at al.An Approach to the Intelligent Decision Advisor (IDA) for Emergency Managers.Int. J. Risk Assessment and Management, Vol. 2, Nos. 3/4., 2001.
9. Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications By Publisher: Addison Wesley Professional Pub Date: February 25, 2003 Print ISBN-10: 0-201-78420-3 Print ISBN-13: 978-0-201-78420-6 Pages: 576 Slots: 2.0
10. Little, J.D.C. "Models and Managers:The Concept of a Decision Calculus." Management Science, Vol.16, NO.8, April, 1970.
	
8.2 Seminar 	Teaching methods	Remarks	
1.		
The first two seminars are dedicated to surveying information sources available on Internet and Intranet, and planning of the papers and projects.  
	Expositions: description, explanation, introductive lectures.
Conversations: debate, dialog, introductive conversations. 
Other methods: individual study, exercise, homework study.		
2.					
3.		The next seven seminars (from three to nine) are dedicated to paper presentations.
	Conversations: debate, dialog, introductive conversations, conversations for knowledge consolidation, conversations to systematize and synthesize knowledge. 
Use of problems: use of problem questions, problems and problem situations. 
Discovery: directed and independent rediscovery, creative discovery, deductive discovery, discovery by documenting. 
Other methods: case study; cooperation, individual study, exercise, homework study, company examples, discussion of material.		
4.					
5.					
6.					
7.					
8.					
9.					
10.		
The project demos will be scheduled in the last three seminars.	Conversations: debate, dialog.
Use of problems: use of problem questions. 
Discovery: experimental discovery, discovery by documenting. 
Other methods: discussion of material.		
11.					
12.					
Bibliography
	
1.	French, S. and Geldermann, J. The varied contexts of environmental decision problems and their implications for decision support. Environmental Science and Policy 8 (2005), 378–391.
2.	Gadomski, A.M. at al.An Approach to the Intelligent Decision Advisor (IDA) for Emergency Managers.Int. J. Risk Assessment and Management, Vol. 2, Nos. 3/4., 2001.
3.	Hackathorn, R. D., and P. G. W. Keen. (1981, September). "Organizational Strategies for Personal Computing in Decision Support Systems." MIS Quarterly, Vol. 5, No. 3. 
4.	Holsapple, C.W., and A. B. Whinston. (1996). Decision Support Systems: A Knowledge-Based Approach. St. Paul: West Publishing. ISBN 0-324-03578-0 
5.	Jiménez, Antonio; Ríos-Insua, Sixto; Mateos, Alfonso. Computers & Operations Research. 
6.	Jintrawet, Attachai (1995). A Decision Support System for Rapid Assessment of Lowland Rice-based Cropping Alternatives in Thailand. Agricultural Systems 47: 245-258. 
7.	Joyce E. Berg, Thomas A. Rietz, Prediction Markets as Decision Support Systems, Kluwer Academic Publishers. Manufactured in The Netherlands, 2003.
8.	Keen, P. G. W. (1978). Decision support systems: an organizational perspective. Reading, Mass.,
9.	Keen, P. G. W. (1980). Decision support systems: a research perspective. Decision support systems : issues and challenges. G. Fick and R. H. Sprague. Oxford ; New York, Pergamon Press. 
10.	Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications By Publisher: Addison Wesley Professional Pub Date: February 25, 2003 Print ISBN-10: 0-201-78420-3 Print ISBN-13: 978-0-201-78420-6 Pages: 576 Slots: 2.0
11.	Little, J.D.C. "Models and Managers:The Concept of a Decision Calculus." Management Science, Vol.16,NO.8, April, 1970. 
12.	Sauter, V.L.  Decision Support Systems: An Applied Managerial Approach, New York: John Wiley & Sons, 1997.
13.	Sprague, R. H. and H. J. Watson. Decision support systems: putting theory into practice. Englewood Clifts, N.J., Prentice Hall, 1993. 
14.	Turban, E. and Aronson, J.E. Decision Support Systems and Intelligent Systems, Prentice Hall, Upper Saddle River, NJ, 2001, ISBN-0-13-089465-6
15.	Turban, E. Decision support and expert systems: management support systems. Englewood Cliffs, N.J., Prentice Hall, 1995. ISBN 0-024-21702-6
16.	Weick, K.E. and Sutcliffe, K. Managing the Unexpected: Assuring High Performance in an Age of Complexity. Jossey Bass, San Francisco, CA, 2001.
17.	Delic, K.A., Douillet,L. and Dayal, U. "Towards an architecture for real-time decision support systems:challenges and solutions, 2001.
18.	Druzdzel, M. J. and R. R. Flynn. Decision Support Systems. Encyclopedia of Library and Information Science. A. Kent, Marcel Dekker, Inc., 1999 
19.	Gachet, A. Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF, 2004. 
20.	Marakas, G. M. Decision support systems in the twenty-first century. Upper Saddle River, N.J., Prentice Hall, 1999. 
21.	Power, D.J. A Brief History of Decision Support Systems DSSResources.COM, World Wide Web, version 2.8, May 31, 2003. 
22.	Reich, Yoram; Kapeliuk, Adi. Decision Support Systems., Nov2005, Vol. 41 Issue 1, p1-19, 19p.
23.	Decision Support Systems. Elsevier B.V., 2007. [http://www.sciencedirect.com/science/journal/01679236]

9. Corroborating the content of the discipline with the expectations of the epistemic community, professional associations and representative employers within the field of the program

•	This course exists in the curriculum of many universities in the world;
•	The results of course are considered by companies of software particularly useful and topical.	

10. Evaluation
Type of activity	10.1 Evaluation criteria	10.2 Evaluation methods	10.3 Share in the grade (%)	
10.4 	Course	- know the basic elements and concepts of an Dss;	Written exam	50%	
10.5 	Seminar
	/
	Project	- complexity, importance and degree of timeliness of the synthesis made	Paper presentation	15%	
	- apply the course concepts
- problem solving	Project presentation	35%	
10.6 Minimum performance standards	
•	At least grade 5 at written exam, paper presentations and project realised.	

Date				Signature of course coordinator 	Signature of seminar coordinator
26 Sept. 2012			Lect. Dr.  PREJMEREAN Vasile		Lect. Dr.  PREJMEREAN Vasile

Date of approval  					  Signature of the head of department
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