ISC 410 - Decision Support Systems

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I. COURSE NUMBER AND CREDIT:

        ISC 410 - 3 S. H.

II. COURSE TITLE:

        Decision Support Systems

III. COURSE DESCRIPTION:

        Decision support systems and expert systems and their
        implementations are examined in this course.   This
        course discusses the manager's responsibilities for
        problem solving and decision making and about those
        areas in which computers can be used as tools to gain
       the insight needed to support selection of decision
        alternatives.

IV. PREREQUISITES:

        ISC 329 or permission of instructor.

V. JUSTIFICATION:

        This course will be an elective in the proposed CIS
        minor.  This course will be taught irregularly.  This
        course provides in-depth study of two relatively new
        areas of information systems.  Class size of 35 is
        expected.  The course is not being submitted for
        General education certification.

VI. COURSE OBJECTIVES:

        Upon completion of this course, the student will be
        able to:
        A.  Distinguish among data processing systems,
            management information systems, and decision
            support/expert systems.
        B.  Integrate the major components of decision
            support systems (DSS) and expert systems (ES), 
            including systems with the following features:
            stored data retrievable through a DBMS, manage-
            ment science models operating on the data to
            produce derived measures supporting managerial
            decision making, and expert knowledge on how to

            use available data and management tools under
            varying levels of uncertainty.
        C.  Capture decision rules based on knowledge
            provided by an acknowledged expert and codify
            those rules as assertions, rules, and ad hoc
            procedures.
        D.  Analyze how information is used to solve
            problems.
        E.  Utilize commercial spreadsheet and database
            integrated packages to develop "what if"
            simulation models to support the decision-
            making process.
        F.  Describe when/how heuristic expert systems
            models may be used to complement more
            analytic decision-making frameworks, such as
            spreadsheet models.

VII. COURSE OUTLINE:

        A.  Review of Systems Principles
            1.  Characteristics and elements of systems
                thought
            2.  The general systems model
            3.  Explore communication systems
            4.  Differentiate between data processing
                systems, management information systems,
                and decision support systems
        B.  Methods of Decision Making and Problem Solving
            1.  Elements of problem solving process
            2.  Problems versus systems
            3.  Structured, unstructured, and semi-
                structured problems
            4.  The systems approach and its relationship
                to the scientific approach
        C.  Decision Support Systems (DSS)
            1.  Development of DSS
            2.  Relationship to data processing and database
                systems
            3.  DSS development and implementation
            4.  DSS features and capabilities
            5.  DSS in the information center
        D.  Expert Systems Overview
            1.  Expert behavior in decision-making
                situations
            2.  Knowledge capture
            3.  Expert systems development process
        E.  Hands-on Experience with a Rule-based Expert
            System Software Package
            1.  Build a minimal expert system
            2.  Apply and modify the system
        F.  Knowledge Acquisition and Meta-Knowledge
            1.  Editing (supplementing, correcting,
                deleting) knowledge 
            2.  Multiple levels of knowledge representation
            3.  Multiple levels of control and search
                procedures
        G.  Spreadsheet Facilities
            1.  Modeling with a spreadsheet
            2.  Hands-on use of a spreadsheet for business
                decision-making
            3.  Spreadsheet in the information center
        H.  Manipulation of Models as a decision-making
            procedure
            1.  Effects of data manipulation to support
                decisions in pricing, production, cash flow,
                and new product evaluation models
            2.  Proficiency in utilizing expert system,
                spreadsheet, database, graphic and
                statistical software for "what if" analyses
        I.  Building Management Models
            1.  Picking a model type
            2.  Validation of models
            3.  Management models and expert systems in the
                information center

VIII. METHODS OF INSTRUCTION:

        Lectures, discussion, case studies, and classroom
        demonstration.

IX. COURSE REQUIREMENTS:

        Course requirements will include assigned readings,
        papers, and projects.

X. MEANS OF EVALUATION:

        Evaluation will include:  paper, projects, and
        examination.

XI. RESOURCES:

        No additional resources necessary.

XII. BIBLIOGRAPHY:

        Bennett, John L. Building Decision Support Systems.
           Reading, MA: Addison Wesley, 1983.
        Leigh, William E. & Michael E. Doherty.  Decision
           Support and Expert Systems.  Cincinnati: South-
           Western Publishing, 1986.
        Sprague, Ralph H., Jr., & Hugh J. Watson, eds.
           Decision Support Systems.  Englewood Cliffs, NJ:
           Prentice-Hall, 1986.
        Turban, Efraim. Decision Support and Expert System:
           Managerial Perspectives.  New York: Macmillan,
           1988.
        Young, Lawrence F. Decision Support and Idea
           Processing Systems, Dubuque, IA: Wm. C. Brown
           Publishers, 1989.