5. DEGREE REQUIREMENTS

5.1. Credit Requirements -- Overview

Students are required to attend the Ph.D. orientation session the first time it is offered following their matriculation. The Ph.D. program in information science requires a minimum of 60 credits beyond the master's degree. Most students will need to take more than 60 credits, particularly if they come to the program from a background other than an IS masters program. The 60 credit minimum must meet the following distribution requirements:

1. Nine (9) credits of course work in preparation for the preliminary exam
2. Nine (9) credits of course work dedicated to developing a methodological framework for their research
3. Six (6) credits of course work dedicated to developing a conceptual framework for their research
4. Eighteen (18) credits of course work in doctoral seminars or 3000-level courses
5. Eighteen (18) credits of dissertation research.

All course work, with the exception of the dissertation research must be taken for a letter grade. Dissertation research credits will be graded "I" incomplete or "S" complete. The doctoral degree requires a cumulative QPA on required courses of at least 3.3. Grades of C- or lower are unacceptable for graduation credit. "I" and "S" grades are not included in calculating the QPA.

In addition to the specific requirements specified above and below in this section, all students who are candidates for doctoral degrees are governed by the Regulations of the University Council on Graduate Study, which establishes minimum standards for graduate work throughout the University as well as by those regulations established by the SIS faculty.

5.2. Preliminary Examination Preparation

Doctoral students should take at least 9 credits in preparation for the preliminary exam. Those who do not have a background in information science may need to take more than 9 credits. Course work taken beyond the 9 recommended credits may be taken on a pass/fail or audit basis at the discretion of the graduate student and advisor. The scope and content of the Master of Science in Information Science (MSIS) degree are considered adequate preparation for the preliminary exam.

5.3. Statistics and Research Design Requirement

A solid grounding in statistics is critical to understanding much of the literature in information science and to the conduct of most research. In addition, a Ph.D. student needs to be exposed to various approaches to research design. The student is expected to develop competence in statistics and to have some course exposure to various approaches to research design. Students will demonstrate competency in this area by taking at least one basic and one advanced statistics course and one course in research design. These courses are included in the 42-credit courses and seminar requirement. The lists below provide examples of courses at each level. Equivalent courses may be substituted with the permission of the advisor. A student with a graduate course in statistics need not retake a basic statistics course and will be required to take only six credits in this area -- one course in advanced statistics and one course in research design.

Basic Statistics (one course)

• INFSCI 2060 Statistical Methods
• PSYED 2014 Statistical Methods 1
• PSYED 2015 Statistical Methods 2
• PSY 2010 Statistical Analysis 2

Advanced Statistics (one course)

• STAT 1201 Applied Nonparametric Statistics
• INFSCI 2070 Scaling Theory
• PSYED 2016 Statistical Methods 3
• PSY 2015 Statistical Analysis 3

Research Design (one course)

• INFSCI 2100 Research Design
• SY 2020 Advanced Experimental Design
• ANTH 2763 Field Methods (4 credits)
• IE 2001 Operations Research
• EE 2165 Algorithms for Design Automation
• NROSCI 2090 Applied Statistics in Neuroscience

5.4. Conceptual Framework Requirement

Information science can be cast in several different frameworks. A consistent framework provides a focus to a student’s research efforts. The student is thus required to take two courses outside the department that form a consistent conceptual framework. Each of the following clusters of courses constitutes a group from which the student may select these courses. Additional clusters suggested by students or faculty may be approved from time to time by the Ph.D. Committee. These courses are included in the 42-credit course and seminar requirement.

Linguistics Cluster (Recommended)

• LING 1950 Introduction to Linguistics
• LING 2682 Introduction to Semantic Theory
• LING 2777 Syntactic Theory

Systems Cluster

• BQOM 2401 Statistical Analysis: Uncertainty
• BORG 2304 Organizational Analysis
• BMIS 3012 Fundamentals of Information Systems Research (2 credits)

Graphics Cluster

• I&L 3325 Interactive Multimedia
• SA 1470 Graphic Design

Neuroscience Cluster

• NROSCI 1003 Introduction to Neuroscience
• NROSCI 1040 Biological Bases of Learning & Memory
• NROSCI 2090 Applied Statistics in Neuroscience

Electrical Engineering Cluster

• EE 1391/2391 Projects in Computer Vision
• EE 1552 Signals and Systems Analysis
• EE 2372 Pattern Recognition
• EE 3395 Advanced Topics: Image Processing/Computer Science Vision

Computer Cluster

• CS 2151 Design & Analysis of Algorithms
• CS 2610 Interface Design & Evaluation
• CS 2790 Pattern Recognition

5.5. Seminar Requirement

The goal of doctoral seminars is for students to gain in depth knowledge of several areas from a number of faculty. These seminars are divided between traditional discussion seminars which take a variety of formats and research seminars which are coupled with the research program of a faculty sponsor or advisor. Students are required to complete 18 credits of doctoral seminars or 3000-level courses, no more than six credits being taken before the preliminary exam. At least four faculty members should be involved in the teaching of the seminars taken by any one student. Of the 18 credits, no more than six should be research seminar credits.

5.6. Research Preparation

As the Ph.D. is largely a research degree, each student is encouraged to begin preparing for research upon entry to the program. The initial preparation is done in consultation with the program advisor and consists largely of a careful review of the current literature within information science. This review will increasingly focus on an area of research interest to the student. The student is also encouraged to keep a notebook in which to record any observations from the literature and any interesting research problems or procedures that are developed. By the second year in the program, the student should be actively exploring research ideas and beginning to determine an individual research program for his or her dissertation work.