Faculty Contact Information:
E-mail: cethington@faculty.ed.umuc.edu
--> Standard policy: only text and .rtf attachments are acceptable.
-->Subject line should begin with INSs 555 followed by the subject
itself. Please choose meaningful subject titles.
Class Web-Site: http://cris-ethington.de
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Consultation:
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Consultation: by appointment.
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Required Texts and Readings:
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Turban, E., and Aronson, J. (2001). Decision Support Systems and Intelligent Systems (6th ed.). Saddle River, NJ: Prentice Hall.
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Supplementary Readings:
The standard for papers in the graduate program is the APA style. All participants in this course and all graduate INSS, MGMT, PUAD, and ECON courses should have a copy of the style guide:
American Psychological Association. (2001). Publication Manual of the American Psychological Association, 5th Edition. Washington DC: Author.All graduate students should be prepared to utilize the UMUC online library at http://www.umuc.edu/library/. The library contains a large number of full text academic journals that are free of charge and immediately available. The library homepage also contains a number of links related to improving students' research and writing skills.
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Recommended Journals:
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Publications of the various professional societies (such as ACM -- the Association for Computing Machinery, the IEEE Computing Society, and the various management professional societies) are strongly recommended. In addition, there are many trade journals (such as eWEEK) that MIS professionals should become familiar with, many of these being published both weekly and on-line.
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Course Description:
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3 semester hours credit. Prerequisite: Either INSS 510, INSS 520, or permission of the Program Director. Examines human information processing capabilities and limitations as they relate to the design, development, and implementation of information systems. Artificial intelligence methodologies for the emulation and enhancement of human information processing are examined. Expert system, neural net, and natural language processing are discussed
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Course Goals:
Upon completion of the course, participants should:
1. Understand the place of AI in cognitive science
2. Have an appreciation for the definitional difficulties
3.· Be able to define the Turing test, and discuss why it may not be sufficient
4. Understand and describe how Eliza-style systems work.
5.· Understand the capabilities and limitations of artificial neural networks
6.· Understand and be able to discuss the architecture of ANNs, and differentiate between models
7.· Understand the capabilities and limitations of expert systems
8.· Understand the design and usage of cellular automata
9.· Be able to use ANNs, CAs, and/or expert systems
10.· Understand some of the links between AI and artificial life
11.· understand some applications of genetic algorithms
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Course Objectives:
After completing this course, the student will be able to:
1. Define and discuss the phases of the decision making process
2. Research and report on major trends in a global marketplace that affect managerial decision making (information literacy, effective writing, international perspective, historical perspective)
3. Identify the characteristics and benefits of Decision Support Systems (DSS) (competence in information technology)
4. Define and illustrate with examples management science, compare structured, semi-structured, and unstructured decisions, and list and classify major decision support models
5. Define and identify characteristics of a data warehouse (competence in information technology)
6. Research and report on selection criteria for obtaining DSS software (competence in information technology, information literacy, effective writing)
7. List the characteristics, benefits, and challenges of groupwork and available supporting groupware (competence in information technology
8, Compare and contrast executive information systems (EIS) and DSS (competence in information technology)
9. Discuss intellectual assets, the characteristics and benefits of knowledge management, and the challenges and strategies for successful knowledge management (competence in information technology)
10. Define, trace the development of, and illustrate current uses of expert systems (ES), intelligent agents, and neural networks(competence in information technology, historical perspective)
11. Assess and report on domestic and global issues related to privacy and security of data and information required for use in DSS, EIS, ES (competence in information technology, civic responsibility, international perspective, information literacy, effective writing) .
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Grading Information:
...Mid Term Exam - 25%
...Research Paper- 20%(written document, format to be discussed in class).
...Research Paper Presentation - 20%(in-class, summary of the written document)
...Final Exam - 35%
Grades for this course will be assigned as follows:
A 92%
B 80 – 91%
C 70 – 79%
F Below 70%
Please note that Bowie State University does not use "D" for graduate students. The grade F(a) is used to designate academic failure. F(n) is used to designate failure for non-completion. Grades of Incomplete or Withdrawal are governed by UMUC-Europe policies. For further details, please refer to the UMUC-Europe Graduate Catalog, available in your local Education Center or online at http://www.ed.umuc.edu/general_info/publications/catalogs.
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Course Requirements:
Graduate school at the masters level focuses on helping students obtain the education needed for success as professionals in their chosen fields. Thus, UMUC-Europe Graduate Programs and Bowie State University share the common goals of promoting excellence in academic scholarship through thoughtful inquiry and the skillful application of knowledge and theory for the betterment of society.
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Other Information:
-->Class attendance is expected.
-->Please carefully evaluate your current workload (given current world events) to ensure you will have the necessary time to invest in the course.
--> As a general rule of thumb, students should expect to spend 3-4 hours outside of class (studying the material + working on programming assignments) for every 1 hour spent in class.
-->Attendance: This is a very fast paced course and failure to participate in class will likely result in a significant burden to keep pace with the course.
-->Make-up Examinations: Need to be arranged prior to absences unless caused by an emergency.
......In any case appropriate documentation will be required.
......It is the student's responsibility to make an agreeable arrangement with the instructor prior to a missing deadline. Such arrangement must be in a written format (typed letter or e-mail).
-->Late Assignments- assignments are expected to be turned in on time.
.......If a student is unable to submit the project on time due to work related circumstances or circumstances out of the student's control, then it is the student's responsibility to make an agreeable written arrangement with the instructor prior to the corresponding deadline.
........Grades on assignments submitted after the due date will be reduced by according to the table below. Appropriate documentation will be required.
..........1-7 days late - 10%
..........7-14 days late - 20%
..........over 14 days late - 40%
This shows that it is always worth to submit a project, even if late.
-->Class Participation
....... I expect and encourage students to ask questions and present comments in class.
-->Student Responsibilities
........Class Participation
........Students are responsible for all material covered in class and corresponding textbook chapters.
........If a student miss a class, it is the student's responsibility to obtain the class notes and material covered from a fellow classmate.
-->Teaching Philosophy
..... Par and parcel with attending the classes is the effort students place when solving assignments.
...... Effort can be demonstrated by:
.............following the assignment format as specified
............ discussing problems with the instructor
.............asking meaningful questions
.............identifying suspected problems with assignments before approaching the instructor -- this helps students to think through a problem.
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Description of Course Requirements:
Participate in classroom discussions: You are expected to come to class prepared to engage in all discussions in a professional and informed manner. Usually this requires two to three hours for every hour of a face-to-face class and approximately ten hours of preparation per week for a DE class.
Complete graduate level projects or programming assignments, write graduate level papers or case studies: You are required to conduct professional-level research, including appropriately citing works of others and avoiding plagiarism. Plan on committing approximately 150 hours over the duration of this course to producing professional level deliverables, to include programs, projects, papers, and/or case studies.
Orally/visually present prepared material: You are required to present your results in a professional manner. In a face-to-face course, this typically means an oral presentation accompanied by appropriate visual material. In a DE class, this means creating a visual/textual presentation for your instructor and classmates.
Complete one or more written examination(s): The examination process in this class will assist you in developing the writing and critical thinking skills necessary for successfully passing the comprehensive exam required of all graduate students. The examination questions used for this course will either be taken directly from past comprehensive exams or written as though to be included on a comprehensive exam.
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Course Schedule:
This is a tentative schedule and it is subject to changes.
Week 1:
...Sat Morning:
.........Introductions
.........Review of syllabus
.........Chapter 1
Week 1:
...Sat Afternoon:
.........Chapter 2
.........Chapter 3
Week 1:
...Sun Morning:
.........More on Chapter 3
.........Chapter 4
Week 1:
...Sun Afternoon:
.........Chapter 5
.........Discussion: Research Paper
Week 2:
...Sat Morning:
.........Review first weekend
.........Chapter 12
.........Chapter 13
Week 2:
...Sat Afternoon:
.........More on Chapter 13
.........Chapter 14
Week 2:
...Sun Morning:
.........More on Chapter 14
.........Chapter 15
Week 2:
...Sun Afternoon
.........Chapter 16
.........Review for the mid term
Week 3:
...Sat Morning:
.........Mid Term Exam (open book)
Week 3:
...Sat Afternoon
.........Chapter 17
Week 3:
...Sun Morning:
.........Chapters 18 & 19
Week 3:
...Sun Afternoon:
.........Chapter 6
.........Chapter 8
Week 4:
...Sat Morning
.......Chapters 9 & 10
Week 4:
...Sat Afternoon
.......Chapters 11 & 20
.......Review for the Final Exam
Week 4:
...Sun Morning
......Student presentations
......Course evaluations
Week 4:
...Sun Afternoon
.......Final Exam -open book.
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Academic Policies:
Please refer to the UMUC - Europe Graduate Catalog, available online at http://www.ed.umuc.edu/general_info/publications/catalogs/index.html or from your local Education Center, for information on the following:
Academic Integrity
Course Load
Exception to Policy
Grade Appeal Process
Make-up Examinations
Nondiscrimination
Students with Disabilities.
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Faculty Bio:
Cristina Ethington
...Collegiate Associate Professor
...BSEE Federal University of Rio de Janeiro
...MS Polytechnic University of Madrid
Ms. Ethington completed her undergraduate studies in VLSI Architecture, Computer Organization and Programming Languages in Rio de Janeiro.
Her graduate studies were completed at the Polytechnic University of Madrid focusing on Computer Networking and Artificial Intelligence.
She is a member of ACM (Association for Computing Machinery).
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