- GENERAL
SCHOOL | Faculty of Social, Political and Economic Sciences | ||||
ACADEMIC UNIT | Department of Economics | ||||
LEVEL OF STUDIES | Undergraduate | ||||
COURSE CODE | ΝΕ88 | SEMESTER | 8th | ||
COURSE TITLE | Decision Support Systems | ||||
INDEPENDENT TEACHING ACTIVITIES if credits are awarded for separate components of the course, e.g. lectures, laboratory exercises, etc. If the credits are awarded for the whole of the course, give the weekly teaching hours and the total credits |
WEEKLY TEACHING HOURS | CREDITS | |||
4 | 6 | ||||
Add rows if necessary. The organisation of teaching and the teaching methods used are described in detail at (d). | |||||
COURSE TYPE
general background, |
Special Background | ||||
PREREQUISITE COURSES:
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LANGUAGE OF INSTRUCTION and EXAMINATIONS: | HELLENIC | ||||
IS THE COURSE OFFERED TO ERASMUS STUDENTS | YES (ESSAY IN ENGLISH) | ||||
COURSE WEBSITE (URL) | |||||
- LEARNING OUTCOMES
Learning outcomes | |
The course learning outcomes, specific knowledge, skills and competences of an appropriate level, which the students will acquire with the successful completion of the course are described.
Consult Appendix A · Description of the level of learning outcomes for each qualifications cycle, according to the Qualifications Framework of the European Higher Education Area · Descriptors for Levels 6, 7 & 8 of the European Qualifications Framework for Lifelong Learning and Appendix B · Guidelines for writing Learning Outcomes |
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The course introduces the student to the field of decision support methods and systems.
The learning outcomes are as follows: – Ability to perceive the characteristics of the decision models in real time or not. – Ability to locate and select appropriate data to support decision models. – Ability to analyze, investigate and evaluate a decision model. – Ability to analyze and draw conclusions on: o Characteristics and variables in the standardization of decision models o The characteristics and type of data required to develop and support decision models o Characteristics and methodological approach to developing decision support systems Upon completion of the course, students should be able to: – Know basic principles, methodologies and features in decision making models – Understand the features of decision support systems on the basis of: o Big Data Management, (Big Data) o Selecting appropriate data, (Data Mining) o Development of Management Information Systems, (MIS) o Decision Support Systems Development (DSS). |
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General Competences | |
Taking into consideration the general competences that the degree-holder must acquire (as these appear in the Diploma Supplement and appear below), at which of the following does the course aim? | |
Search for, analysis and synthesis of data and information, with the use of the necessary technology
Adapting to new situations Decision-making Working independently Team work Working in an international environment Working in an interdisciplinary environment Production of new research ideas |
Project planning and management
Respect for difference and multiculturalism Respect for the natural environment Showing social, professional and ethical responsibility and sensitivity to gender issues Criticism and self-criticism Production of free, creative and inductive thinking …… Others… ……. |
Search for, analysis and synthesis of data and information, with the use of the necessary technology
Working independently
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- SYLLABUS
The content of the course includes the following sections:
i. Data management for the development of decision models: a. Data Mining b. Data Blending c. Big Data ii. Introduction to Management Information Systems: a. Management Information Systems (MIS) b. Geographic Information Systems (GIS) c. Data Visualization Systems (DVS) d. Negotiation Support Systems (NSS) e. Decision Support Systems (DSS)
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- TEACHING and LEARNING METHODS – EVALUATION
DELIVERY Face-to-face, Distance learning, etc. |
Face-to-face | ||||||||||||
USE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY Use of ICT in teaching, laboratory education, communication with students |
E-mail and e-class | ||||||||||||
TEACHING METHODS
The manner and methods of teaching are described in detail. Lectures, seminars, laboratory practice, fieldwork, study and analysis of bibliography, tutorials, placements, clinical practice, art workshop, interactive teaching, educational visits, project, essay writing, artistic creativity, etc.
The student’s study hours for each learning activity are given as well as the hours of non-directed study according to the principles of the ECTS |
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STUDENT PERFORMANCE EVALUATION
Description of the evaluation procedure
Language of evaluation, methods of evaluation, summative or conclusive, multiple choice questionnaires, short-answer questions, open-ended questions, problem solving, written work, essay/report, oral examination, public presentation, laboratory work, clinical examination of patient, art interpretation, other
Specifically-defined evaluation criteria are given, and if and where they are accessible to students. |
Written examination (70%):
– Assignments (30%)
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- ATTACHED BIBLIOGRAPHY
– Suggested bibliography:
1. Ι.Κ.Μουρμούρης, «Εφαρμογές Θεωρίας Αποφάσεων Πολλαπλών Κριτηρίων: Μεταφορές, Χωροθέτηση και Ανάπτυξη», ISBN 9789603516880, Εκδόσεις: Α. Σταμούλης, 2007.
2. Ν. Ματσατσίνης – Κ. Ζοπουνίδης, “Συστήματα αποφάσεων με πολλαπλά κριτήρια”, ISBN 9604610686, Εκδόσεις: Κλειδάριθμος, 2007.
– Related academic journals: International Journal of Management and Decision Making International Journal of Decision Support Systems Decision-Making for Supply Chain Integration-Springer International Journal of Multicriteria Decision Making Multiple Criteria Decision Making-Springer Journal of Multi-Criteria Decision Analysis Decision Support Systems Journal of Decision Systems Journal of Soft Computing and Decision Support Systems
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