Online Course Syllabus CS460 Decision Support Systems Important Notes: This document provides an overview of expectations for this online course and is subject to change prior to the term start. Changes may also occur during the term due to faculty or SPS Distance Learning course updates. Some links may only be active once the term starts. For this course you must check the Regis Bookstore: http://www.efollett.com for the most current online course material information. Course Description Prerequisites Course Outcomes Required Course Materials Grading Criteria Assignments Course Description Study recent advances in decision support systems (DSS, also known as business intelligence or BI) and computer-based information systems. Study how the decision support system, which is highly interactive, targets on top management, and makes information available in a heuristic system. Artificial intelligence (AI) is addressed and students will perform on-line research to share major topics, scope, and theme(s) throughout the course and research cutting-edge developments by software vendors and user success stories. Course Outline Week 1: Introduction to Management Support Systems (MSS) Week 2: Decision Support Systems: An Overview Week 3: Data Warehousing, Access, Analysis, Mining and Visualization Week 4: Collaborative Computing: Group Support Systems and Enterprise Decision Support Systems
Week 5: Knowledge-based Decision Support and Artificial Intelligence Week 6: Fundamentals of Intelligence Systems Week 7: Knowledge Acquisition and Validation Week 8: Summary and Conclusion Note: Specific course outcomes for each week are located in the Week by Week area of this course. Course Prerequisites In order to successfully complete this course, students are expected to have completed the course prerequisites. The prerequisites for CS437 are: MT270 (Statistics) or MT 320 (Introduction to Discrete Mathematics), AND CS484 (Technical Aspects of CIS) or CS341 (Data Structures; for CIS minors only). Course Outcomes Upon completion of this course, students should be able to achieve the following three outcomes: Identify the decision making process: intelligence, design, and choice, Research and analyze current commercial off-the-shelf (COTS) software systems that implement business intelligence and management support systems (MSS), and Understand the modeling process and artificial intelligence (AI) that is used extensively in MSS and that models can be iconic, analog, or mathematical. COTS products that support AI will also be research and analyzed. Required Course Materials Required Text Turban, E. & Aronson, J. (2004). Decision support systems and intelligent systems (7th ed.). Upper Saddle River: Prentice Hall. Additional Resources
The World Wide Web and the Regis Library databases will be utilized. Grading Criteria Grades in the course are based on points earned by the student and will be awarded according to the following components: Case Study Analysis - 10%. Each student or team (facilitator's choice) to select and post on the forum a SWOT (strength, weakness, opportunities and threats) analysis of a case from the text. Midterm and final exams - 15% each. Written Project - 25%. This is an individual real world DSS project from your workplace, a case from the text, or from outside research. A six-page paper with references in APA format is required during the last week of class. On-line Search - 10%. Students are to search the Internet for new developments or software tools recently developed to support BI and AI and post their findings on the forum. No paper is required. Class Participation and Communication - 25%. Each workshop will include the opportunity to post a case study, case analysis, on-line search, or written project on the Forum. Your activity, including responses, will be graded. TOTAL = 100% Grade Structure Letter grades will be awarded according to the number of points earned as indicated in the following scale: Letter Grade Numerical Grade Range Quality Points Description A 100-93 4.00 Outstanding Scholarship A- 92-90 3.67 B+ 89-87 3.33 B 86-83 3.00 Superior Work B- 82-80 2.67 C+ 79-77 2.33 C 76-73 2.00 Satisfactory
C- 72-70 1.67 D+ 69-67 1.33 D 66-63 1.00 Unsatisfactory D- 62-60 0.67 F Below 60 0.00 Failure Incomplete ("I/F") grades: Only in extreme emergencies will a student be given an incomplete grade. An incomplete grade results when a student is unable to complete any exam by the last day of class, or turn in assignments that would otherwise result in a passing grade, DUE TO EXTENUATING CIRCUMSTANCES. The reason supporting such a grade MUST be provided to the instructor, IN WRITING, before the last day of class. In all cases, the incomplete grade will indicate an "F" status. If the grade is approved, the requirements must then be completed within the following 30 days. Failure to complete the requirements within this time frame will result in a permanent grade of "F". While not mandatory, missing homework assignments, still eligible for partial credit, should also be completed during this time. Please note that the instructor will be occupied with other courses during succeeding terms and WILL not be available for help after the end of the current term. Descriptions of Forum and other Assignments The Forum is your primary link to other students and to your facilitator. Your facilitator will post any information and/or additional assignments to the Forum. You will communicate with your facilitator and the other students in the class via the Forum. Each student is expected to participate in the Forum weekly in the following three ways: By responding to instructor-initiated questions, By posting questions about the course materials, and By responding to the postings of other students. Forum Tips You should always check the Forum first thing Monday morning. It is advisable to check the Forum every time you log in. Online Course Assignments CS460 Week: 1 2 3 4 5 6 7 8
About this Page The Course Assignments page does not provide all of the specific details and instructions that you need to complete assignments. For specific information about each assignment, go to the Week by Week. Course Dynamics Your understanding of decision support systems will come from four sources: Your reading of the required Sections in the text, Your reading of the Week-by-Week discussion of the subject matter, Your participation in the class discussions using the Forum, and Outside sources that you use for your discussions on the Forum and for your research for the term paper. Use the questions at the end of each chapter to help you review the material of the previous presentation. Although this is not required to be written and turned in, it will increase your understanding and confirm your comprehension of previously learned material. Course Deadlines This course is organized around an eight-week program. An online week correlates to a sevenday work week, beginning on Monday and ending on the following Sunday. Thus, Week 1 begins on the first day of the semester, which is always Monday. These are the weekly assignments that you must work on and complete: 1. Initial Reading & Assignment Prior to the start of each week, by Monday, complete the offline (i.e., textbook) reading assignment. Also check the first page of the weekly content in the Week by Week section for any additional initial weekly assignments that need to be completed. 2. Week by Week Read the online content pages in the Week by Week and check the Forum for any Weekly Discussion Questions or additional postings from the facilitator. 3. Exercises To check your understanding of the concepts presented in this course and to prepare for the Midterm and Final exams, complete the exercises provided in the Week by Week. Correct answers are provided to help you check your work.
4. Forum Questions/Assignments During this course, you will be asked to discover and analyze DSS or BI applications and software vendor demonstrations on the Web. You should analyze your discovery using Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis and post your findings on the Forum for comment by your classmates. Assignments By midnight Saturday, complete any Forum Questions posted by your facilitator and post your answers. These questions may be assignments from the Week by Week pages, additional questions posted by your facilitator, or include materials assigned by the facilitator for each student to summarize. (Note: in some weeks, there may be no Forum questions.) 5. Exams At the end of Week 4 there will be a Midterm exam, and at the end of Week 8 there will be a Final exam. Access to these exams is available on the course Homepage. The Midterm will be available anytime Thursday through Sunday. The Final exam will be available anytime Tuesday through Sunday during Week 8. Note that while the exams are available for several days, you will have limited time to complete the exam once you begin. (two bullets follow) The Midterm exam will cover chapters 1-4 of the text. The Final exam will cover chapters 7-10 of the text. 6. Term paper A term paper is required and due during the last week of the class. See the course syllabus and Week 1 for the details of the paper. Below is a list of all assignments by week. For additional details about individual assignments, see the Week by Week. Week1: Introduction to Management Support Systems (MSS) Getting Started Orient yourself to the course Web site. In particular, explore the Homepage. If you have not done so, take the Forum Tour which is linked from the first page of the Study Guide. By midnight Wednesday, post your introduction to the Forum in the topic Introduction: Tell a little about yourself and your nickname, if you use one.
Tell a little about your current occupation and your hobbies. Mention any relevant experience you might have related to decision support systems. Comment on what you would like to get out of this course. Reading: Turban, Part 1, chapters 1-2, pp. 1-98. Week by Week: Read the Week 1 content pages and complete the Exercises for each topic in the Week by Week (Note: The exercises are not graded.). Assignment and Forum: Select topic for written project and identify your selection on the Forum. Week 2: Decision Support Systems: an Overview Reading: Turban, Part 2, chapter 3, pp. 100-139. Week by Week: Read the Week 2 content pages and complete all exercises. Assignment: Analyze Case Application 3.1, pp. 140-141. Identify the issues, analyze the proposal, and answer the five questions on p. 127. Week 3: Data Warehousing, Access Analysis, Mining and Visualization Reading: Turban, Part 2, chapter 5, pp. 211-299. Note: skip Chapters 4 and 6. Week by Week: Read the Week 3 content pages and complete all exercises. Assignment: Search the Web for a data warehousing, OLAP, data mining, data visualization, graphic information systems, visual reality examples, or a software vendor demonstration of one of these.
Week 4: Collaborative Computing: Group Support Systems and Enterprise Decision Support Systems Reading: Turban, Part 3, chapters 7-8, pp. 361-365. Week by Week: Read the Week 4 content pages and complete all exercises. Assignment: Review the opening vignette; Chrysler Scores with Groupware, pp. 362-365. Complete the Midterm exam and submit the answers online. Week 5: Knowledge Management Reading: Turban, Part 3, chapter 9, pp.487-531. Week by Week: Read the Week 5 content pages and complete all exercises. Assignment: Review Case Applications, Chrysler Ebok & Chevron, 9.1 and 9.2 and analyze using the SWOT analysis. Forum: Post your SWOT analysis of the assignment on the Forum. Week 6: Fundamentals of Intelligence Systems Reading: Chapter 10, pp. 538-573. Week by Week: Read the Week 6 content pages and complete all exercises. Assignment: Review Case Applications 10.1 p. 574 and complete a SWOT analysis. Forum: Post your SWOT analysis of the assignment on the Forum. Week 7: Knowledge Acquisition and Validation
Reading: Turban, Part 4, chapter 11, pp. 575 & chapter 14 pp. 744. Week by Week: Read the Week 7 content pages and complete all exercises. Week 8: Summary and Conclusion Reading: Review chapters 9, 10, 11, & 14. Week by Week: Read the Week 8 content pages. Assignment: Submit a term paper to facilitator by mail, include a return envelope. Answer questions on the Final exam and submit for grading. Forum: Post your oral presentation PowerPoint slides on the Forum. Complete online evaluation located at the bottom of the content in the Week by Week. Contact techsupport@regis.edu to report technical problems with this website. 2003 Regis University. All rights reserved.