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Graduate Course Proposal Form Submission Detail - LIS6702
Tracking Number - 4834
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Current Status:
Approved by SCNS - 2014-11-01
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: Recd after 3/1. To Chair; Appd 5/19/14. to USF 5/20/14; to SCNS 5/28/14. Apprd eff 11/1/14
Detail Information
- Date & Time Submitted: 2013-10-15
- Department: Library and Information Science
- College: AS
- Budget Account Number: 124800
- Contact Person: Randy Borum
- Phone: 43520
- Email: borum@usf.edu
- Prefix: LIS
- Number: 6702
- Full Title: Advanced Intelligence Analytic Methods
- Credit Hours: 3
- Section Type: C -
Class Lecture (Primarily)
- Is the course title variable?: N
- Is a permit required for registration?: N
- Are the credit hours variable?: N
- Is this course repeatable?: N
- If repeatable, how many times?: 0
- Abbreviated Title (30 characters maximum): Adv Intelligence Analytic Mthd
- Course Online?: O -
Online (100% online)
- Percentage Online: 0
- Grading Option:
R - Regular
- Prerequisites: No course pre-reqs
- Corequisites: No course co-reqs
- Course Description: This course is designed to help the student select and apply complex, structured techniques and methods used to support intelligence analysis.
- Please briefly explain why it is necessary and/or desirable to add this course: Needed for new program/concentration/certificate
- What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? Necessary "methods" course for the intelligence studies concentration in the M.S. in Information Studies with a focus on Strategy & Information Analytics and the M.S. in Cybersecurity Concentration in Cyber Intelligence
- Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? No
- What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) Expertise in analytic methodology as applied to intelligence problems.
- Objectives: This course is designed to help the student select and apply complex, structured techniques and methods used to support intelligence analysis.
- Learning Outcomes: o Understand the applications and limitations of contemporary data analysis software
o Understand the relationship between demographics, technology and the impacts on critical infrastructures within the assigned areas of research.
o Compare the merits of existing technologies and their relationship to future needs.
o Develop a rational and philosophy for data-driven intelligence.
o Explain the scope and applications of open source intelligence gathering by business and government entities and its impact on information security
- Major Topics: Key Concepts of Analysis
Processing Intelligence
Populating the Model
Integrating the Centric Model Format into Student Projects
Analysis
Predictive Techniques
Shaping Forces
Organizational & Technology Analysis
Techniques for Decomposition and Visualization
Techniques for Idea Generation
Scenarios and Indicators
Techniques for Hypothesis Generation and Testing
Techniques for
Assessment of Cause and Effect
Techniques for Challenge Analysis
- Textbooks: Beebe, S., & Pherson, R. H. (2011). Cases in Intelligence Analysis: Structured Analytic Techniques in Action. Washington, DC: CQ Press.
Heuer, R. J., & Pherson, R. H. (2010). Structured analytic techniques for intelligence analysis. Washington, DC: CQ Press.
- Course Readings, Online Resources, and Other Purchases: Supplemental course readings will be provided on the online learning systems. The student is not required to purchase any additional supplies or materials for the course.
Readings include selections from the following:
Altman, I. (1997). The Concept of Intelligence: A Philosophical Analysis. Lanham, MD: University Press of America
Beebe, S. M., & Beebe, G. S. (2012). Understanding the Non-Linear Event: A Framework for Complex Systems Analysis. International Journal of Intelligence and CounterIntelligence, 25(3), 508-528.
Clark, R. M. (2004). Intelligence analysis: A target-centric approach. Washington, DC: CQ Press.
Clauser, J. (2008). An Introduction to Intelligence Research and Analysis. Lanham, MD: Scarecrow Press.
Derbentseva, N., & Mandel, D. R. (2011). Using concept maps to improve the practice and organization of intelligence in Canada. B. Moon, R. Hoffman, JD Novak, & AJ Cañas (Eds.), Applied concept mapping: Capturing, analyzing, and organizing knowledge, 109-130.
Friedman, J. A., & Zeckhauser, R. (2012). Assessing Uncertainty in Intelligence. Intelligence and National Security, 27(6), 824-847.
Fung, K. (2010). Numbers Rule Your World: The Hidden Influence of Probabilities and Statistics on Everything You Do. MY: McGraw-Hill.
Heuer, R. (2006). Psychology of Intelligence Analysis. New York: Novinica Books.
McCue, C. (2007). Data Mining and Predictive Analysis: Intelligence Gathering and Crime Statistics. Elsevier, Inc.
Treverton, G., Thomson, J. & Leone, R. (2003). Reshaping National Intelligence: For an Age of Information RAND Studies in Policy Analysis. New York: Cambridge Press.
Walton, T. (2010). Challenges in Intelligence Analysis: Lessons from 1300 BCE to Present. Cambridge University Press.
Wirtz, J. J. (2013). Indications and Warning in an Age of Uncertainty. International Journal of Intelligence and CounterIntelligence, 26(3), 550-562.
- Student Expectations/Requirements and Grading Policy: Grading Scale: The following grading scale will be applied:
90% - 100% is an A
80% - 89% is a B
70% - 79% is a C
60% - 69% is a D
less than 60% is an F.
The grade will be judged and weighted on the following basis:
Presentation and Reading Quizzes: 65%
Final Exam: 25%
Final Project: 10%
- Assignments, Exams and Tests: Quizzes will be given every two weeks covering material from the readings, presentations and multimedia material during that two-week period.
A final project consists of an analytic memo and an electronic briefing.
The final exam is cumulative.
- Attendance Policy: Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,
http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)
Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)
In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.
- Policy on Make-up Work: Policy on Make-up Work
As a general policy, there are no make-ups for quizzes, projects or the final exam. If a student wishes to submit an assignment late, the instructor may accept it at his/her discretion and assess a suitable grade penalty.
System Emergencies
In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It is the responsibility of the student to monitor the Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.
Scheduled Absences
Students are expected to notify their instructors at the beginning of each academic term if they intend to be absent for a class or announced examination for religious reasons. They will be given reasonable opportunities to make up any work missed. For further information, please refer to: http://generalcounsel.usf.edu/policies-and-procedures/pdfs/policy-10-045.pdf
Academic Dishonesty
The University of South Florida has in place specific policies and procedures regarding academic dishonesty or disruption of academic process (also see below for more detail). Academic dishonesty includes, but is not limited to: copying or relying on another’s work and using it as your own; representing work you previously prepared for another class as work that was prepared for this class; and using any material during a quiz exam that has not been approved by the professor.
Academic dishonesty will result in a grade of “FF” and, possible dismissal from the program. An “FF” received as a result of academic dishonesty puts you on Academic Warning for the remainder of your time at USF. A class in which you receive an “FF” as a result of academic dishonesty is not repeatable. All papers, research, and examinations will be monitored carefully and students found cheating will be punished to the fullest extent allowed by the University and the Department.
In an effort to ensure compliance, plagiarism tracking software (SafeAssign) may be employed in this course. The University of South Florida has an account with an automated plagiarism detection service which allows instructors to submit student assignments to be checked for plagiarism. Your assignments may be submitted to this detection system, in which they are compared to a large database of journal articles, web articles, and previously submitted papers. Because all papers will be submitted to SafeAssign, you should know your rights:
You may be required to submit your paper to a plagiarism detection site that will be identified by your instructor. In order to comply with federal (FERPA) and state privacy laws, you (students) are not required to include personal identifying information such as your name, SSN, and/or U# in the body of the work (text) or use such information in the file naming convention prior to submitting. Please follow carefully your instructor’s instructions regarding what identifying information to include. Your submission will be placed in the course grade center in your account that can be accessed by the instructor and attributed to you.
If you have any questions, please refer to USF’s Procedures for Alleged Academic Dishonesty or Disruption – http://www.ugs.usf.edu/catalogs/0809/adap.htm and Student Academic Grievance Procedures – http://www.ugs.usf.edu/catalogs/0809/arcsagp.htm
- Program This Course Supports: M.S. in Information Studies with a focus on Strategy & Information Analytics
- Course Concurrence Information: M.S. in Cybersecurity Concentration in Cyber Intelligence
- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.