DECISION SUPPORT SYSTEMS

A KNOWLEDGE-BASED APPROACH

PREPARING TO TEACH WITH THIS TEXTBOOK

Introduction
Course Synopsis
Course Objectives
Instructional Methods
Student Evaluation Methods
Schedule of Activities
Sample Course Syllabus

 

Introduction
We advocate that each student should have the opportunity to develop and demonstrate a prototype system as a hands-on learning experience to complement the textbook. We leave it to the instructor to select the development tool(s) most suitable to student backgrounds, available computing facilities, curriculum requirements, and individual preferences. In cases where students are not already familiar with the selected tool(s), coverage of the textbook will need to be supplemented by coverage of the tool(s). Various softbound workbooks that focus on particular tools can be helpful supplements to the textbook. Thus, preparing to teach a course with this textbook will typically involve the selection of a development tool(s) and, in some cases, a supplemental workbook(s).

In addition to (or maybe even instead of) having students develop their own systems, an instructor can consider procuring or building systems for the students to view and/or use. This gives students exposure to DSSs from a user's perspective. Indeed, such systems could be made available to students in follow-up, capstone types of courses where they play the roles of decision makers in dealing with case studies or simulated managerial environments. The availability of DSSs in such settings can enhance the realism of the educational experience.

Having settled on the development tool(s), workbook supplement(s), and/or sample decision support system(s), creation of a syllabus is a way of structuring one's thoughts about what the course will accomplish and how it will be accomplished. We recommend that the syllabus should contain a brief course synopsis, a statement of specific course objectives, an explanation of the methods of instruction to be used, a clear indication of how student learning will be evaluated, and a schedule of course activities.

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Course Synopsis

A course synopsis may simply be the official description of the course as stated in the institution's catalog of courses. Or, using that description as a starting point, the synopsis may provide additional detail, offer an updated view, and emphasize certain aspects of the course. Broadly speaking, it should indicate the overall goal of the course, briefly characterize the main topics covered, point out why the course is important to students, identify any special instructional methods to be used, and comment on what background students should have in order to best appreciate the course content.

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Course Objectives

Having characterized the course in broad terms, the instructor needs to determine more specifically what he/she wants to accomplish. Specific learning objectives may have been established already (e.g., by a curriculum committee) or they may be at the full discretion of the instructor. In any event, the objectives stated in the syllabus should be constructed to answer the question: "By the end of the course, what knowledge, skills, and experiences will each student have gained?" The answer to this question will influence which parts of the textbook are to be covered and how intensively they are to be covered. The objectives must, of course, be consistent with the software and supplemental workbook (if any) selected for the student use. The number of specific objectives will typically be in the 6 to 12 range.

Part of the first class session may be devoted to gathering student ideas about the stated objectives. They may suggest additional objectives that can be incorporated readily in the course. Or, the discussion may suggest that certain objectives should receive a particular emphasis. Near the end of the semester and/or shortly before the students evaluate the course, it can be instructive to spend a bit of class time reviewing the objectives to impress upon students a realization of how far they have progressed.

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Instructional Methods

Having determined what will be accomplished, the instructor needs to settle on how to accomplish the objectives. The methods of instruction will be influenced by institutional constraints, class size, class meeting length, course length, and individual instructor style. Usually, student interest and learning is enhanced by the use of multiple instructional methods. Aside from the traditional assignment of textbook readings and presentation of lectures based on these readings, methods of instruction might include the following:

  1. discussion of the DSS Insights mini-case before and/or after each chapter (e.g., with students answering related application questions appearing at the end of the chapter),
  2. presentation and discussion of relevant news items beyond the "DSS in the News" readings included in the textbook, perhaps even assigning students to locate them (the daily Computers and Technology page of Investor's Business Daily is an especially rich source for such items)
  3. demonstrations of DSSs (e.g., on the first day of class and/or shortly before students are required to propose their own DSS development projects),
  4. student participation, individually or as groups, in the development of prototype DSSs (for application domains and tools selected by students or prescribed by the instructor),
  5. student performance of knowledge management exercises (e.g., provided in a workbook supplement) to acquaint them with usage of a specific tool,
  6. for advanced courses, student preparation and presentation of research or tutorial papers on topics/tools related to knowledge management and decision support (e.g., see the textbook's Directory of Publications for sources for such papers and for sample topics),
  7. video presentations of decision support systems (e.g., the video available with the textbook) and tools available to develop them (e.g., videos from vendors of EIS tools, GDSS tools, multimedia tools, solver management tools),
  8. student reports on the usage of DSSs in the local business community.

The syllabus should identify which of these (or other) instructional methods will be used.

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Student Evaluation Methods

The syllabus should clearly explain the grading policies that will be followed in the course. The test bank in this Instructor's Manual provides a starting point for constructing evaluation instruments in the form of quizzes and exams. It consists of over 1000 test items. Other dimensions for gauging student performance include evaluation of their participation in class discussion (e.g., see instructional methods 1 and 2 above), their work on knowledge management exercises (e.g., see instructional method 5), their papers and reports in terms of the quality of both written and verbal presentations (e.g., see instructional methods 6 and 8), and their hands-on system development projects (e.g., see instructional method 4). When evaluating written or verbal aspects of papers, reports, or projects, we are inclined to assess not only the content but also the clarity and organization of the presentation. That is, students are given incentives to work on their communication skills as well as the course content.

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Schedule of Activities

The syllabus should contain a planned schedule of activities, including an indication of the timing for coverage of the textbook's contents. Generally, we suggest the book's contents be covered in sequence, realizing that some material may be skipped or skimmed to meet an instructor's objectives. The textbook's preface gives some guidance along these lines, as well as suggestions about pacing, from the perspectives of four different course offerings.

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Sample Course Syllabus

Decision Support Systems and Knowledge Management

Professor xxxxxxxxxxxxxxxxxxx Course #: xxxxxxxxxxxxx

Office: xxxxxxxxxxxxxxxxxxxxx Spring 1996

Phone: xxx-xxxx Day/Time: MW/4:30-5:45

Office Hours: xxxxxxxxxxx and by appointment Room: xxxx-xxx

Course Synopsis

This course is designed to foster a comprehensive understanding of decision support system (DSS) concepts and possibilities, impart practical DSS development skills, and point out the important role these systems play in business today. Such an understanding is valuable for prospective application developers, managers of business computing technology, and decision makers. Coverage includes the DSS field's historic roots, its theoretical foundations, various DSS applications, contexts for DSS usage, and multiparticipant decision support systems. The focus is on how techniques for managing knowledge can be applied, enhanced, extended, and integrated in the development of computer based DSSs. Each student will work on a project to develop a decision support system. Familiarity with business problems, computers, and common knowledge management techniques is assumed.

Course Objectives
By the end of the semester you will:
be able to describe the generic characteristics of DSSs
appreciate the difference between a decision support system and a managementinformation system
recognize various special classes of DSSs
be clear about the distinction between a DSS and a DSS development tool
be conversant with basic DSS terminology including language system, knowledge system, presentation system, and problem processing system
have studied a variety of knowledge management techniques that can be used in decision support systems
know about the various types of multiparticipant DSSs and their uses
have developed your own decision support system
be prepared for independent, critical study and assessment of publications about DSSs

Methods of Instruction

Readings: Decision Support Systems: A Knowledge-Based Approach (Holsapple and Whinston, West, 1996).

Lectures: Attendance to all lectures is strongly recommended and active participation is encouraged. A set of transparency masters used in lectures is available for duplication. You should prepare for class by reading the assigned materials and developing answers to the application case questions at the ends of chapters.

Project: You will develop a prototype decision support system in an application area of your own choosing. This includes analysis, design, and implementation of the DSS. You will select the development tool that furnishes needed knowledge management techniques. In most cases, this will be a tool about which you already have a working knowledge. A written prospectus describing your project will be submitted for review and approval.

Exams: There will be three exams covering lectures and discussions.

Presentations: You will make two presentations in class. The first will be a presentation of your project prospectus. The second will be a presentation/demonstration of the DSS prototype you develop.

Grading Policy

To receive full credit, work must be submitted/presented by the assigned date. There is a reduction of 10% of the total credit for each day it is late. There are no make-up exams without prior consent of the instructor.

Graded work will receive a numeric score reflecting the quality of performance. Relative weights assigned to graded work are as follows:

Exams 60% (20 % each)
Project
Prospectus Presentation 5%
Final Presentation 15%
Written/Software 15%
Participation in Discussions 5%
Your overall course grade will be determined according to the following scale:

90-100% A
80-89% B
70-79% C
60-69% D
Schedule of Activities

The anticipated schedule of classroom activities is shown below. Exam dates may vary slightly from the scheduled times, but will be announced at least one week in advance. You are expected to have read the indicated materials in advance of the corresponding class sections. Exact dates for submitting project proposals and final project reports will be announced in class.

Wed Jan 10 Introduction (Syllabus and DSS Overview)
Wed Jan 17 DSS demonstration, Chapter 1
Mon Jan 22 Chapters 1, 2
Wed Jan 24 Chapter 3
Mon Jan 29 Chapter 4
Wed Jan 31 Chapters 4, 5
Mon Feb 5 Chapter 5
Wed Feb 7 Chapter 6
Mon Feb 12 Chapter 6, Review
Wed Feb 14 EXAM I
Mon Feb 19 Chapter 7
Wed Feb 21 Chapters 7, 8
Mon Feb 26 Chapter 8, Submit project prospectus
Wed Feb 28 Chapter 9, Hypertext demonstration
Mon Mar 4 Chapter 10, IFPS demonstration
Wed Mar 6 Chapter 11, Expert System demonstration
Mon Mar 18 Project prospectus presentations, Review
Wed Mar 20 EXAM II
Mon Mar 25 Chapter 16
Wed Mar 27 Chapter 16
Mon Apr 1 Chapter 17
Wed Apr 3 Chapter 17
Mon Apr 8 Chapter 18
Wed Apr 10 Chapter 19
Mon Apr 15 Course summary, Review
Wed Apr 17 EXAM III
Mon Apr 22 Final Project Presentations
Wed Apr 24 Final Project Presentations

Home Page Top of Page Course Synopsis Course Objectives
Instructional Methods Student Evaluation Methods Schedule of Activities Sample Syllabus