I F S M   4 2 5

UNIVERSITY OF MARYLAND 
                                                                   
Lecturer: Wendy Davis-Gruber               

Course Name:                     DECISION SUPPORT AND EXPERT SYSTEMS
                                             3 s.h. credit            Prerequisite: IFSM 202

Course                  This course covers a wide range of issues in decision support
Description           systems. We will analyze information support systems that serve managers  with quantitative information for making decisions. During our course you will learn the concepts and applications of decision support systems within organizations, understand the structure levels of information within an organization, develop a perspective for designing and implementing decision support systems that are valuable for both managers and computer specialists.

Since this course covers descriptive material on how organizations utilize their computer environment, case studies are an important part of the course, and class assignments will involve extensive analysis of case studies, discussion, and presentation of a term paper or a student project. While our course requires no prior programming background as a prerequisite, it does require general mathematics knowledge to include algebra, exponents and graphing. A general knowledge of spreadsheet and database management systems is also useful for the development of student projects.

Text:                     Decision Support and Expert Systems, 5th ed.,
                              by E. Turban, Jay E. Aronson, Prentice Hall, 1998.

Course                   Grades for this course will be based on:
Evaluation                   mid-term exam                       25%
                                     homework                             20%
                                     class presentation & paper     25%
                                     final exam                              30%

                             and will be assigned as follows:
                                     A         93   to  100
                                     B         82   to   92
                                     C         72   to   81
                                     D         60   to   71
                                     F(A)    Less than 60

Student Responsibilities /Requirements

Class attendance is expected.  More than six one hour un-excused absences may lead to a grade of FN.  It is expected that students participate in class discussion.  Your comments are important.  It also shows me you’ve been doing the reading !   Be active, this is your class.
Students should be prepared to spend a substantial amount of time outside of class preparing assignments Grades on assignments submitted after the due date will be reduced  by 10%.  Attendance for all exams is mandatory.  A makeup exam will not be scheduled unless PRIOR arrangements have been made with the instructor.  Students are expected to complete all assignments individually unless otherwise specified.  Any form of academic dishonesty will result in a failing grade for that assignment.

Students might find the following useful for class research and homework:

   a.  Reliable e-mail
   b.  Internet Access
   c.  Web Access and browser

Office Hours:  Office hours for student assistance will be before and after class.  Students can
                         set up other appointments when needed.
 
Instructor:      Wendy Davis-Gruber earned her Master of Science degree from the University of Southern California in Systems Management - Logistics and Information Systems Management.  Her experience for the last fifteen years has been in the field of adult education working as a university lecturer, community college administrator, and a training and management seminar workshop leader.  She is currently lecturing for the University of Maryland in the Computer Studies and Management Studies discipline.
 Ms Davis-Gruber has developed and conducted training seminars throughout Europe.  These seminars have been in the areas of Performance management, instructional techniques, ethics, and goal setting and planning.
 

 Time Schedule
 
Session                        Topic                                                                Text Assignment
 

   1  & 2                        Overview of management support systems        CH 1
                                     Decision making and modeling                          CH 2
                                     Intro. to decision support systems                     CH 3

   3 & 4                         Data Management                                            CH 4
                                     Modeling and Analysis                                      CH 5
                                     Knowledge-based DS and AI                           CH 6
                                     User Interfaces and Decision Visualization         CH 7

 

   5 & 6                         Constructing a DSS                                           CH 8
                                      Networked Decision Support                           CH 9
                                      Group DSS systems                                         CH 10

   7                                Executive Information and Support Systems       CH 11
   8                                Midterm exam                                                   Feb 8th

 

   9 & 10                     Intro. to AI and expert systems                             CH 12
                                   Knowledge acquisition and representation             CH 13,14

  11& 12                     Inferences, Explanations, and Uncertainty              CH 15
                                   Building expert systems                                         CH 16

 

 13  & 14                     Neural Computing                                                 CH 17, 18
                                    Intelligent Agents                                                   CH 19
                                    Integrating management support systems                CH 20
                                    Organizational and Societal Impacts of                   CH 21
                                    Management Support Systems
 
 15                                Final exam

 16                                Student Presentations
                                      ( Final Papers due by Mar 8th )
 

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