PART ONE: REPORT OF FINDINGS OF

PART ONE: REPORT OF FINDINGS OF PART ONE: REPORT OF FINDINGS OF THE FEASIBILITY STUDY FOR A NEW DEGREE PROGRAM

I. PROGRAM DESCRIPTION

Computation has assumed a status equal in importance to theory and experiment in many science and engineering disciplines. Computation's role continues to grow in disciplines such as economics, fine arts, and film. Computational science is now recognized as a speciality that is well served by neither a traditional degree in computer science, nor a degree in a specific application areas, such as pure science or engineering. For example, scientists wishing to contribute through large-scale computation to leading edge research must henceforth have a background that combines a significant share of the scientific degree, non-traditional courses in high performance or large-scale computing and courses which integrate computing with a scientific discipline. Many of the most important problems of our time involve considerable complexity and are best approached through a combination of modes of investigation that includes skillful computational simulations.

The new degree program in computational science is intended to be offered for both a Masters and Doctoral degree in Computational Science. It's goal is to train graduates who have expertise in computer science, information technology, applied mathematics, science and engineering beyond the purview of their specialization. The program will also develop a small number of courses (4) for professional development of educators and three undergraduate courses. Students in this program are likely to come from a wide range of undergraduate backgrounds including science, mathematics, engineering, and social sciences.

II. INSTITUTIONAL MISSION

The Board of Regents has designated Florida State University as a Research I University and thus has been established as one of three major research universities within the State of Florida. In keeping with this designation, the mission statement of Florida State University begins as follows: "Florida State University is a comprehensive, graduate-research university with a liberal arts base. It offers undergraduate, advanced graduate, and professional programs of study; conducts extensive research, and provides service to the public in accord with its statewide mission. The University's primary role is to serve as a center for advanced graduate and professional studies while emphasizing research and providing excellence in undergraduate programs."

The proposed Masters and Doctoral degree programs in computational science address the above mission directly. They will provide advanced graduate programs of study that enhance and rely upon the extensive research activities at Florida State University. In addition the program's courses, seminars and research activities can be used to supplement graduate programs throughout the University.

III. PLANNING PROCESS AND TIMETABLE

Extensive Planning

Begin Faculty hiring       Fall 1996
Began Offering CSE Courses       Fall 1997
Computational Science on SUS
Master Plan (MS & Ph.D.)       Fall 1998
Completed Internal Review
of the Program of Studies Spring 2000
Report on Feasibility
Study & Authorization to
Plan a New Degree Program Spring 2000
Begin Teaching Courses Fall 2000
in Program of Study Fall 2000
Request for Authorization
to Implement Spring 2000
Upgrade Classrooms to
Computational Science Labs Spring 2001
Accept Students Fall 2001

IV. ASSESSMENT OF NEED AND DEMAND

A. What national, state or local data support the need for more people to be prepared in this program at this level? (This may include national, state or local plans or reports that support the need for this program; demand for the proposed program which has enated from a perceived need by agencies or industries in your service area; and summaries of prospective student inquiries.) Indicate potential employment options for graduates for the program. If similar programs exist in the state, provide data that support the need for an additional program.

IV-A. In considering the feasibility of this program, FSU has been able to make use of a host of state and national studies on the changing nature of the work-force and the need for new graduate training opportunities. In November of 1999, FSU held a workshop that examined the general role of computational science and information technology across a wide range of scientific enterprises and in graduate education. Additionally, FSU faculty working on the feasibility study have sought the advice and guidance of a number of faculty at other institutions and with government and industry leaders who are potential employers for the graduates of this program.

Enterprise Florida, Inc. in their Sector Strategy Discussion Paper on Information Technology Products and Services in Florida provided an estimate on the impact of Information Technology on the Florida Economy. They point out several common misconceptions about information technology and its development that are relevant to this effort. These include:

The sweep of digital technologies and the transformation to a knowledge-based economy have created a robust demand for workers highly skilled in the use of information technology. In the past ten years alone, employment in the U.S. computer and software industries has almost tripled. The demand for workers who can create, apply and use information technology goes beyond these industries, cutting across manufacturing and services, transportation, health care, education and government.

This same dynamic is occurring in the application of high performance computing to science and engineering. In these endeavors modern computers and detection equipment are producing simulation and/or raw data at tremendous rates. This is forcing scientists and engineers to push the envelop by developing and applying new information technology techniques to their problems.

Consequently, part of the role of the CSIT program is to train students who are able to assimilate the results of advanced information technology research from computer science and mathematics and apply them to the problems in their disciplines. Consequently, the goal is to train leaders in the application of information technology to science and engineering problems.

A recent study published by Efstratios Gallopoulos and Ahmed Sameh entitled "Computational Science and Engineering: Content and Product" in CSE Magazine. (need reference). Their views of the educatiional offerings helped motivate the design of the CSIT program. A few of their points are worth noting:

Students in science and engineering receive at least introductory courses in computer technology (introductions to computer system organization, a programming language, data structures and basic numerical analysis). Some of these courses are taught in computer science and engineering departments, computational methods courses tend to be taught by the student's home department. The resulting education and training have frequently proven insufficient for the kinds of problems that are routinely encountered today in industry or in meaningful research activities in academia.
Computational science and information technology is about the design, implementation and effective integration of computing tools to target specific scientific processes and less about their everyday use.
Successful CSIT curricula will cover its basic components with courses that bring the cross-disciplinary components to the forefront. Programs that merely collect a number of previously existing courses from different departments will not be effective and need not exist.
The US Federal Government has been active in motivating CSIT-type cross-disciplinary research efforts, first through the HPCC Grand Challenges, in response to the recommendations of workshops, and most recently through the Accelerated Strategic Computing Initiative (ASCI). (Note: More recent examples not cited include the NSF's Knowledge and Distributed Intelligence Initiative and the Information Technology Research Initiative currently in progress.)

At least two graduate Ph.D. programs of this type are in a similar stage of development as this one. One program is at San Diego State University and the other is at George Mason University. The outlines of those programs are available online and along with informal discussions with the principles involved, this information has been used to help evaluate these programs.

Studies on Indirectly Related Issues

A 1995 study by Russ Miller (miller@cs.buffalo.edu) conducted for the National Science Foundation entitled "The Status of Parallel Processing Education" was published in IEEE Computer 27(8): 40-43 (1994). This report solicited information from over 4000 members of the IEEE Computer Society, and all chairs for computer science and engineering departments involved with the IEEE Computer Society. Approximately 70 sites were identified at that time. University based graduate-level education programs provided an array of courses, including parallel algorithms, parallel programming, and parallel architectures. The students in these program typically had access to large computing facilities either at the university of at one of the NSF sponsored sites.

There have also been numerous studies on graduate education of scientists and engineers that relate to the proposed degree program. In 1995 the National Academy of Sciences, the National Academy of Engineering and the Institute of Medicine published "Reshaping the Graduate Education of Scientists and Engineers." Among the findings and recommendations are the following:

More that half of new graduates with Ph.D.s now find work in nonacademic settings.
To provide more versitile scientists and engineers, graduate programs should provide options that allow students to gain a wider variety of skills.
Over the long-term, demand for graduate scientists and engineers in business and industry is increasing; more employment options are available to graduate scientists and engineers who have multiple disciplines, minor degrees, personal communication skills, and entrepreneurial initiative.

The U.S. Council on Competitiveness in their 1999 report "Winning the Skills Race" have singled out "worker skills as the greatest competitive challenge the nation faces" and have noted that ïnformation technology has become a defining feature of the American workplace, turning computer literacy into a basic skill requirement and creating a demand for knowledge workers that is not being met." One of the main goals of CSIT is to train students who possess computer fluency and can become leaders in developing new applications of computational science and information technology within their chosen endeavors.

An excellent online resource for surveying computational science programs is maintained the Society for Industrial and Applied Mathematics; it is available at: http://www.siam.org/world/compsci/cplsci.htm

IV-B. Table One - headcount and FTE for the Ph.D. Program in CSIT.

Year 1 Year 2 Year 3 Year 4 Year 5
Source HC FTE HC FTE HC FTE HC FTE HC FTE
Agencies/Industries
Other Grad Programs 16 16 16 16 16
Second Degrees(FSU)
Second Degrees(SUS)
New In-State 5 5 6 6 8 8 8 8 8 8
New Out-of-State 7 7 12 12 15 15 15 15 15 15
New Foreign 4 4 6 6 7 7 7 7 7 7
Other 11 11 32 32 47 47 81 79
Total 32 51 78 93 127

Rationale for projections.

Rationale for headcount to FTE ratio. Estimate that the number of Ph.D. students which can be educated effectively is about 100 - 120. Estimate that the number of master's students who can be educated effectively is about 100. Include approximately 30 students per year who are taking 1 computational science graduate course. National demographics indicate that approximately half of the students in science and engineering programs are foreign nationals. With a lot of effort in recruiting, we believe this can be kept under one-third.

IV-B. Table One - headcount and FTE for the Masters Program in CSIT.

Year 1 Year 2 Year 3 Year 4 Year 5
Source HC FTE HC FTE HC FTE HC FTE HC FTE
Agencies/Industries
Other Grad Programs 144 188 188 188 188
Second Degrees(FSU)
Second Degrees(SUS)
New In-State 18 36 54 54 54
New Out-of-State 6 12 18 18 18
New Foreign 6 12 18 18 18
Other 27 54 80 80
Total 42 79 92 117 142

Rationale for projections.

Are students expected to change majors: How big an impact is this? What disciplines will be affected?

Students will not be encouraged to change majors from a program at FSU to enter the CSIT program. CSIT will work with departments to provide CSIT training to students currently in their programs without changing departments. CSIT will also work with departments to develop joint programs that enable both CSIT and the departments to attract additional students. Such program might include five year bachelor's/masters degree program that involve undergraduate majors with the department and a master's degree in CSIT or within the department but with some CSIT courses. Another option being explored is offering a masters degree in CSIT and a PhD in an application area or vice versa. In all case the goal is to allow CSIT and departments throughout the University to recruit students they would not otherwise be able to attract.

Students are not expected to change from other graduate degree programs into Computational Science. We will encourage students students to receive dual degrees, such as a Ph.D in an affiliated subject and a Master's Degree in Computational Science or a Ph.D in Computational Science and a Master's Degree in an affiliated subject.

IV.C. Steps taken to assure a diverse student body.

One of the avowed goals of this program is to strongly encourage students to attend graduate school at Florida State University. Our efforts will be aimed towards students who have the innate capability to successfully complete the CSIT degree programs in a timely manner. Thus, we are interested in recruiting students into CSIT degree programs who, with proper assistance, guidance and direction, have an excellent opportunity of succeeding in these novel graduate programs. In order to find and retain such students from a diverse pool of candidates, a concerted and active recruitment and retention program in needed.

The education and research programs will serve as the foundation for the recruitment and retention of students. Faculty members in CSIT have strong contacts with many of the traditional feeder colleges and universities for FSU. In addition, in order to further enhance our recruitment efforts, CSIT will rely on the resources of Florida State University (.....NEEDS MORE HERE ON FSU's ACTIONS). FSU has extensive experience in recruiting students for graduate degree programs. In particular, the departments affiliated with CSIT have many contacts with colleges and universities throughout the country. These combination of resources will greatly facilitate the accomplishment of CSIT recruitment goals.

CSIT is committed to using its research efforts as an important mechanism for recruiting under represented students. For example its research efforts include development of advanced tools and environments to support online teaching and learning. A proposal is being submitted by FSU faculty in CSIT, Computer Science and Physics and senior personnel in FSU's Office of Distributed and Distance Learning to the National Science Foundation to work with Florida A&M University, Jackson State University, North Carolina A & T on course modules for computer science. A proposal involving faculty from CSIT, the College of Arts and Sciences and the College of Education at and from the College of Arts and Sciences and the College of Education at Florida International University has been submitted to the National Science Foundation. This proposal seeks funds to develop distance learning courses in biology, chemistry, earth science, physics, applied mathematics, computational science and education technology for the professional development of K-8 educators. Both of the these proposal create additional contacts with faculty and students in minority institutions.

Retention of students is a key component of any recruiting effort. There several things we will do to help insure the retention of as many students as possible. We will ensure that every student has a program of study that is customized to their particular strengths and weaknesses, we will ensure that every student becomes a part of the CSIT community as soon as possible and we will ensure that impediments to satisfactory progress towards a degree are identified early and that steps are taken to enable every student to successfully complete the program.

Every student accepted into the program will be assigned an advisory committee consisting of at least three faculty members. These faculty will be responsible for evaluating the students background, consulting with the student and producing a program of study that meets the needs of the student. Because success in CSIT relies on knowledge and understanding in a wide variety of areas, it is expected that many students who are capable of completing the program in a timely manner, will enter the program with gaps in training in some areas and strengths in others. This committee will seek to identify any deficiencies in the student's background and recommend workshops, short courses, tutorials, or directed individual study or other means of filling these gaps. In addition, the committee will make recommendations concerning advanced study options open to the student.

As a result of participation in summer and academic year activities, we feel that strong associates will develop between students and faculty. These CSIT activities will include seminars, workshops, summer institutes, interactions with external visitors and post-doctoral fellows. It is CSIT's philosophy that these activities and the resulting associations will play an important role in both the training and retention of students.

Each student's faculty advisory committee is responsible for meeting with the student and the student's instructors at least once each semester to evaluate progress. The results of these discussions will be communicated to the student and the rest of the CSIT faculty.

CSIT will use a variety of recruiting methods which include visits to institutions, advertisements, web pages, K-12 and undergraduate outreach programs,and direct mailings. Visits to institutions which can provide a diverse student body will play an important role in our recruitment plans. During these visits, faculty members from CSIT will deliver a lecture describing the various degree programs, including research activities that students could get involved in should they join the CSIT graduate program. These visiting faculty members will also engage in more informal discussions with students and faculty at these institutions. Once again, it is CSIT's philosophy that such personal contact is the best way to publicize its programs, and to subsequently recruit students.

During these visits, faculty will also make presentations on scientific subjects. These presentations will serve as part of the recruitment process, and, as an added bonus, will be of sufficient intrinsic value so that they will also be of interest and benefit to the research community at large as each particular institution.

Advertisements publicizing the various degree programs, in national trade magazines such as Newsletters for the Society for Industrial and Applied Mathematics and a well designed web site will help CSIT reach all students and educators with an interest in this program. Outreach programs, including programs such as the NSF sponsored Research Experience for Undergraduates, serve as ideal tools for recruiting future graduate students. In additional, we intend to develop web sites for K-12 and K-12 teacher education focus on CSIT activities that will help help foster interest in the program from students even before they enter undergraduate school. Faculty from the school are involved in distance learning programs for schools throughout the US, including several HBCU's. This program provides an excellent opportunity to recruit students outstanding students.

In addition, two types of mailings will be used. First, a professionally designed and printed flyer will be produced and mailed to a large number of institutions throughout the United States. These flyers will describe the various degree programs and solicit applications. The second mailing will be targeted to traditional feeder institutions for FSU. This mailing will be in the form of personal letters to faculty members, including the heads of departments and undergraduate advisors, giving descriptions of the degree programs and soliciting their help in publicizing CSIT programs to their students and in helping identify strong candidates. The letters will also contain offers for personal visits to their institutions (and vice-versa where appropriate).

V. CURRICULUM

The objective of the Computational Science and Information Technology program is to provide students with an environment in which they can develop skills necessary to seamlessly blend computational science, information technology and mathematical techniques with a specialized discipline. It is becoming increasingly clear that these tools will serve as the backbone leading to major advances in all fields of research. To achieve this objective, an alliance of several departments from the College of Arts and Sciences and the College of Engineering has been established to sponsor and staff an inter-departmental, interdisciplinary, graduate degree program in computational science and information technology.

The term "Computational Science and Information Technology" is used to represent an interdisciplinary field comprising a specific scientific or other discipline, applied mathematics (including numerical mathematics), and computing science. ???? The applied mathematicla aspect emphasizes mathematical modeling of the physical world and the discretized version thereof, whereas the computing science aspect emphasized the development of software and hardware systems and tools (including libraries, environments, protocols, and devices). Until recently, these disciplines evolved in isolation without consideration of each other's requirements and opportunities. In order to effectively harness the resources made available by the fast-paced evolution of computer software and hardware, a close-knit coupling of the disciplines is required. The CSIT Program seeks to produce researchers capable of such integration through a curriculum that includes the disciplines of computing science, applied mathematics, and an engineering or science speciality.

This objective is achieved through complementary requirements: students from computer science or mathematics will approximately one-third of their total course load in an engineering or scientific discipline outside their department, while engineering or science students will carry approximately one-third of their total course load in computer science or mathematics. In addition, certain core CSIT courses will be required of all CSIT degree candidates. These courses are designed to provide a common knowledge base for the wide variety of students expected in the program and to emphasize the interdisciplinary aspect of the program.

Alternative Version of the Above Paragraph

The objective of the CSIT curriculum is two-fold: one, to build upon the individual strengths of the students and two, to provide students with a cohesive, but broadly-based graduate education in high performance computing and information technology as applied to science and engineering. Students are expected to enter the CSIT Program with a variety of undergraduate backgrounds. Consequently, the program provides for two tracks: one for students from computer science or mathematics, the other for students from an engineering or scientific discipline. These tracks are have considerable overlap, but provide the flexibility to build upon the student's strengths.

To achieve this objective the CSIT curriculum will provide provide students with the opportunity to explore some topics in detail, while at the same time achieve breadth. This is accomplished through courses and activities that establish a core foundation in CSIT, establish graduate level competency in an application area, provide in depth exploration of several tracks and integrate contemporary research results and techniques. Consequently students will take courses from CSIT core courses, their application area, from several CSIT tracks and from additional advanced graduate courses.

End of Alternative Version

A. Sequence of Courses and Credit Hours for Every Degree Option

The Ph.D. degree is intended to be completed in approximately five years of full time effort. The recommended course work for the Ph.D. is 45 graduate hours.

The M.S. degree is intended to be completed in two years of full time effort. The required course work, including six (6) hours of thesis, is 30 graduate hours.

Recommended Programs of Study

The CSIT program offers two (2) core courses which every CSIT student must master. These courses are Foundations of Computational Science I and Foundations of Information Technology I. The CSIT program also includes nine (9) different tracks of three (3) courses each, advanced CSIT courses and courses in affiliated departments. (NOTE: Many of these track and dvanced courses and the vast majority of the courses in the affiliated departments were being taught prior to the proposal for the CSIT degree program and do not need additional development). These tracks and courses will be described in detail below.

Students entering CSIT are expected to have a wide range of interests. These students may elect to pursue a degree with a strong application area emphasis or with a strong computing sciences and mathematics emphasis. The recommended programs of study differ slightly in these two cases. Each recommended program includes at least 15 courses, though students may have engaged in prior graduate work that will enable them to master the material without taking the courses. Whether all of the courses have been taken or not, students will be expected to demonstrate mastery of the material in the core courses and in their selected tracks on the preliminary exam.

In addition to the two CSIT core courses, students wishing to pursue a degree with strong application area emphasis will be advised to master at least six (6) courses from the graduate courses offered in an affiliated department, and four (4) courses from two different CSIT tracks. In addition, they will be advised to take at least three (3) courses from the approved list of Advanced CSIT courses (at least one (1) of these courses must be the third course in one of the student's selected CSIT tracks). Though there are no other specific course requirements, students will be encouraged to take other specialized courses in CSIT and in application areas.

In addition to the two CSIT core courses, students wishing to pursue a Ph.D. degree with strong computing sciences and applied mathematics emphasis will be advised to take six (6) courses from three different CSIT tracks, three (3) courses from the approved list of Advanced CSIT courses (at least one (1) of these courses must be the third course in one of the student's selected CSIT tracks), and four courses (4) from the list of approved CSIT Affiliated Courses. Though there are no other specific course requirements, students will be encouraged to take other specialized courses in CSIT and in application areas.

A MS degree in CSIT will not be required for the Ph.D. degree. Before a student can be admitted to candidacy for the Ph.D. degree, the student must: 1) pass the written portion of the preliminary exam on the material in the CSIT core courses and on the material in their CSIT tracks (two (2) for an application area emphasis and three (3) for a computing sciences and mathematics emphasis), 2) write a tentative prospectus of a research topic suitable for a Ph.D. dissertation and 3) students pursing an application area emphasis must also pass the written portion of the preliminary exam in an application area at the Master's level, or have a master's degree in an application area. No less than one week after the prospectus has been submitted the student must, and 4) pass the oral portion of the preliminary exam to be given by the student's graduate advisory committee. Students pursing an application area emphasis must also pass the written portion of the preliminary exam in an application area at the Master's level, or have a master's degree in an application area from an accredited institution.

The nine CSIT tracks are:

Advanced Computer Graphics, Scientific Visualization, Virtual Reality Environments
Numerical Linear Algebra, Advanced Numerical Algorithms, Computational Optimization
Foundations of Computational Science II, Parallel Software Systems, Distributed Software Systems
Foundations of Information Technology II, Distributed Collaboration Environments, Advanced Methods in Information Technology
Computational Geometry, Combinatorics, Pattern and Structure
Computational Statistics I, Stochastic Systems, Statistics in Applications I.
Advanced Data Management, Distributed Databases, Mathematical Foundations of Databases and Information Retrieval
Uniprocessor Architectures, Parallel Processor Architectures, Embedded and Distributed Processors
Information Security, Cryptography, Advanced Security Systems

In each track, the first course listed is a prerequisite for the other two.

B. 120 hour Maximum for Undergraduates

This is a graduate program and not subject to the 120 hour maximum for undergraduates.

D. Prerequisites

This is multidisciplinary graduate program and consequently does not require a particular degree as a prerequisite. The ideal background of potential students would include an undergraduate major in mathematics, computer science, science or engineering combined with some training in the areas not a part of their major. Few students are likely to meet this standard. Consequently, the program intends to develop courses and activities which normally would occur in the summer before the student begins the CSIT core courses for assisting highly qualified students who lack some of this breadth in their undergraduate program of study. This plan is critical to the success of this program.

Departments affiliated with the CSIT program grant Ph.D.'s in their own disciplines. With this proposals students will be accepted into either the M.S. or the Ph.D. program in CSIT who meet the admission requirements of CSIT and an affiliated department.

E. Limited Access Status

This program in not applying for Limited Access status.

C. Description of Required Courses - Currently identical to Other version

V.C.1. CSIT core courses

Students in the CSIT Ph.D. program would be required to master at least three of the following courses.

Computational Science I: This is the first course in a two-semester sequence on the role of computational methods, models of computation, computer architectures, and digital computations in scientific applications. Cross-cutting scientific applications selected from topics in materials science, quantum mechanics, data analysis, global warming, earth-quake propagation, will be used to underscore the importance of numerical methods in linear algebra, ordinary and partial differential equations, Monte Carlo methods and tools for software development, performance monitoring, visualization and model evaluation.
Computational Science II: This is the second course in a two-semester sequence on the role of computational methods, models of computation, computer architectures, and digital computations in scientific applications. Cross-cutting scientific applications selected from topics in fluid flow, phase transistions, biological structure and climate prediction will be used to underscore the importance of parallel computing, numerical methods in linear algebra, ordinary and partial differential equations, Monte Carlo methods, and optimization techniques.
Applied Information Technology I: This is the first course in a two-semester sequence covering the application of information technologies of current interest within integrated online environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications currently in the course include collaborative research environments, genomics database application, electronic logbooks, weather prediction, and teaching and learning systems, but specific applications will evolve rapidly to insure inclusion of leading-edge scientific applications of information technology.
Applied Information Technology II: This is the second semester of a two-semester sequence covering the application of information technologies of current interest within integrated online environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications will be selected from distributed physics simulations, remote instrument operation and control and advanced teaching and learning systems, but specific applications will evolve rapidly to insure inclusion of leading-edge scientific applications of information technology.

V.C.2. CSIT Intermediate Courses

These courses are designed to build upon knowledge and skills acquired in the core courses. Note that students may be advised to any of the core courses they have not already taken.

Computational Science II: This is the second course in a two-semester sequence covering computational methods. Topics include sequential and parallel computer applications of linear algebra, numerical methods for ordinary and partial differential equations, Monte Carlo methods, optimization techniques, tools for performance monitoring, visualization and model evaluation.
Parallel Computing Applications: This course will focus on strategies for the development and maintenance of large parallel applications required by a rapidly growing class of scientific and engineering applications. Students will develop a variety of parallel applications to solve science and engineering problems requiring extensive computations.
Parallel Algorithms and Architectures
Applied Information Technology II: This is the second semester of a two-semester sequence covering the application of information technologies of current interest within integrated online environments including environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications currently in the course include distributed simulations for high energy and nuclear physics, weather prediction, electronic logbooks and teaching and learning systems, but they will evolve rapidly to include leading edge scientific applications of information technology.
Distributed Computing Applications: This course will focus on the strategies for the development and maintenance of large distributed computing applications, such as fortunately parallel computations, remote instrument monitoring and control, grid computing and large-scale, real-time data acquisition. Students will develop distributed computing applications to solve science and engineering problems, such as those listed above.
Distributed Collaboration Environments: This course provides students with an in depth look at the unique problems, tools and requirements of online collaboration environments. It focuses on the requirements, technology and use of online collaboration environments for scientific research, commerce and education.
Photorealistic Computer Graphics: Computer architectures for graphics applications, algorithms for rendering, scattering, realism and lighting techniques.
Scientific Visualization: Serial and parallel visualization algorithms, visualization of complex data sets, techniques for extracting information from complex data sets.

V.C.3. CSIT Affiliated Courses

The courses listed below are offered by departments as part of their standard course offerings and are included as part of the CSIT curriculum. A student's graduate advisory committee may recommend that students within CSIT include selected courses within their program of study for a variety of purposes. Particular courses may be used to help meet a student's needs in CSIT intermediate or advanced instruction. Additionally, some of these courses may be used to help build a student's application area expertise, provided they are normally used within the department's own degree programs for that purpose.

Biological Sciences

Advanced Evolutionary Biology (PCB 5675): - Needs description
Current Problems in Neuroscience (PSB 6070r): - Needs description
Gene Expression and Development (PCB 5595): - Needs description
Computational Biology ( ): - Needs description

Chemical Engineering

Advanced Biochemical Engineering (ECH 6748)
Advanced Process Control (ECH 5325)
Advanced Chemical Engineering Computation (ECH 5844)
Computational Molecular Dynamics

Chemistry

Principles of Inorganic Chemistry (CHM 5620)
Physical Organic Chemistry (CHM 5245)
Thermodynamics and Statistical Mechanics (CHM 5460)

Computer Science

Artificial Intelligence (CAP 5600)
Artificial Neural Networks (CAP 5615)
Complexity of Algorithms (COT 5410)
Computer Architecture (CDA 5155)
Database Systems (COP 5710)
Object-oriented Programming
Software Engineering (COP 5632)

Economics

Applied Microeconmics (ECO 5114)
Computational Economics I, II (ECO 5408)
Limited Dependent Variable Models (ECO 5427)
Mathematical Demography (ECP 5117)
Simultaneous Equation Models (ECO 5424)
Time Series Analysis (ECO 5425)

Geology

Advanced Topics in Hydrology (GLY 5829r)
Hydrodynamics (GLY 5556)
Numerical Modeling of Groundwater Flow (GLY 5826)

Industrial Engineering

Advanced Simulation Applications (ESI 5524)
Applications of Knowledge Engineering (ESI 5625)
Computational Topics in Industrial Engineering (EIN 5118)
Computer-Aided Manufacturing (EIN 5396)
Optimization on Networks (ESI 5492)
System Modeling and Simulation (ESI 5523)

Mathematics

Advanced Topics in Differential Equations (MAP 6316r)
Advanced Topics in Numerical Analysis (MAD 6408r)
Finite-Element Methods (MAP 5395)
High-Order Finite-Difference Methods (MAD 5757)
Hydrodynamic Stability (MAP 5512)
Numerical Solutions of Partial Differential Equations I (MAD 5738)
Numerical Solutions of Partial Differential Equations II (MAD 5739)
Optimization (MAP 5207)
Perturbation Theory (MAP 5441)
Spectral Methods for Partial Differential Equations (MAD 5745)
Wave Propagation Theory (MAP 5513)

Mechanical Engineering

Advanced Computational Fluid Dynamics (EML 6726)
Computational Materials Science (EML 5930)
Introduction to Computational Mechanics (EGH 5456)
Numerical Methods in Engineering (EGN 5455)

Meteorology

Dynamical Weather Prediction (MET 5541r)
Advanced Time Series Analsysis (MET 6308): - check on number
Objective Analysis (MET 6561): - check on number
Statistical Weather Prediction (MET 5550)

Oceanography

Physics of the Air-Sea Boundary Layer (OCP 5551)
Stability of Geophysical Fluid Flows (OCP 5255)
Turbulence (OCP 5271)

Physics

Condensed Matter Physics I (PHZ 5491): - check on number
Condensed Matter Physics II (PHZ 5492): - check on number
Electrodynamics A (PHY 5645) and B (PHY 5437)
High-Energy Physics I (PHZ 5354) and II (PHZ 5355)
Nuclear Physics I (PHZ 5305) and II (PHZ 5307)
Computational Physics Laboratory (PHZ 5151C)
Management of Scientific Computations (PHZ 5146C)
Statistical Mechanics (PHY 5524)
Stochastic Processes and their Statistical Analysis

Statistics

Computational Methods in Statistics I (STA 5106)
Computational Methods in Statistics II (STA 5107)
Image Analysis (STA 6468r)
Operations Research: Linear and Dynamic Programming (STA 5619)
Statistics in Applications I (STA 5166)
Statistics in Applications II (STA 5167)
Statistics in Applications III (STA 5168)

V.C.4. CSIT Advanced Courses

Advanced Applications in Computational Science: This course examines emerging computational science technologies and their potential applications in science, engineering and other fields. Students will be engaged in developing applications which explore the use of these technologies in selected application areas.
Advanced Applications of Information Technology: This course examines emerging information technologies and their potential applications in science, engineering and other fields. Students will be engaged in developing applications which expand the use of information technology in selected application areas.
Advanced Data Management or Data Intensive Computing: This course provides students with an in depth look at the unique problems, tools and requirements of data intensive computing applications. It includes applications utilizing databases and data management, computer networking technologies, grid computing, management of scientific computations, and the principles, design and optimization of data intensive computing systems.
Online Teaching and Learning Systems: This course provides students with an in depth look at the unique problems, tools and requirements of online teaching and learning environments. It focuses on the requirements, technology and use of online environments for education.
Special Topics in Computational Science and Information Technology: Each semester a number of courses labeled Special Topics in Computational Science and Information Technology may be scheduled. The exact content of each of these courses will depend on the interests and needs of the students and faculty. Three months prior to the scheduling of these courses, individual faculty members submit proposals for special topics courses to the Graduate Affairs Committee. Student or faculty groups are encouraged to approach an appropriate faculty member and persuade him or her to submit a proposal for a course they feel is needed.
Graduate Tutorial in Computational Science and Information Technology: Selected topics in computational science. Reading and analysis of primary literature. Maximum of eight (8) students in each tutorial. May be repeated up to a maximum of fifteen (15) semester hours.
Applied Fuzzy Logic and Neural Networks: Place Holder.
Computational Geometry, Grid/Mesh Generation: Place Holder.
Computational Optimization: Place Holder.
Control Theory: Place Holder.
Distributed Databases: Place Holder.
Domain Decomposition and Parallel Algorithms: Place Holder.
Evolutionary Algorithms: Place Holder.
Image and Time Series Analysis: Place Holder.
Intelligent Systems: Place Holder.
Linear and Nonlinear Programming: Place Holder.
Parallel Computer Architectures: Place Holder.
Parallel Linear Algebra: Place Holder.
Stochastic Systems: Place Holder.
Symbolic Computing: Place Holder.
User Interface Design: Place Holder.
Virtual Reality Environments: Place Holder.
Wavelets in Computation and Analysis: Place Holder.

V.C.5. Additional CSIT Courses

Preliminary Doctoral Examination: Students are required to pass this examination before they can be admitted to the candidacy for the Ph.D. This exam covers core knowledge in computational science and information technology and the student's chosen application area.
Dissertation: The student must write a dissertation on original CSIT research constituting a significant contribution to knowledge and representing a substantial scholarly effort on the part of the student. The minimum number of dissertation hours for completion of a doctoral degree shall be twenty-four (24) semester hours.
Dissertation Defense: The student must successfully defend their dissertation before the student's graduate committee in an open meeting.
Directed Individual Study: May be repeated for a maximum of forty-eight (48) semester hours.
Supervised Research: May be repeated for a maximum of forty-eight (48) semester hours.
Colloquium: A series of lectures given by faculty and visiting scientists. May be repeated for a maximum of ten (10) hours.
Introductory Seminar on Research: A series of lectures given by faculty on the research being conducted by the School of Computational Science and Information Technology. May be repeated for a maximum of two (2) semester hours.
Supervised Teaching: Teaching under the direction of a senior faculty member. May be repeated for a maximum of forty-eight (48) semester hours.
Graduate Seminar in Computational Science and Information Technology: May be repeated for a maximum of ten (10) semester hours.

V.C.6. Additional Activities within CSIT

The educational elements of the CSIT program extend beyond course work, to include workshops, short courses, summer research internships and an annual retreat. Workshops will bring scientists and engineers in the forefront of CSIT-related research from around the world to campus to interact with students and faculty. Short courses provide concentrated instruction on a cutting-edge research topic to students and faculty at FSU, and from around the world. Summer research internships in industry or a national laboratory provide students with valuable experience in applications of computational techniques to real-world problems. The annual retreat will provide an informal setting for CSIT students and faculty to exchange ideas and perspectives, both on their individual research topics and on more general CSIT issues.

V.C.7. Other Courses

Computational Models of Physical Systems: (Undergraduate courses) Principles of the design, development and evaluation of computational models, common computational science and information technology techniques, impact of numerical methods, computer hardware and software on model performance, testing and validation of numerical models, and techniques for improving computational models. The course uses real-world applications to illustrate the principles involved.
Principles of Educational Technology
Principles of Computational Science
Principles of Information Technology
Simulation Science

V. CURRICULUM

The term "Computational Science and Information Technology" is used to represent an interdisciplinary field comprising a specific scientific or other discipline, applied mathematics (including numerical mathematics), and computing science. ???? Definition of Information Technology The applied mathematical aspect emphasizes mathematical modeling of the physical world and the discretized version thereof, whereas the computing science aspect emphasized the development of software and hardware systems and tools (including libraries, environments, protocols, and devices). Until recently, these disciplines evolved in isolation without consideration of each other's requirements and opportunities. In order to effectively harness the resources made available by the fast-paced evolution of computer software and hardware, a close-knit coupling of the disciplines is required. The CSIT Program seeks to produce researchers capable of such integration through a curriculum that includes the disciplines of computing science, applied mathematics, and an engineering or science speciality.

Alternative Version of the Above Paragraph

End of Alternative Version

A. Sequence of Courses and Credit Hours for Every Degree Option

The Ph.D. degree is intended to be completed in approximately five years of full time effort. The recommended course work for the Ph.D. is 45 graduate hours.

The M.S. degree is intended to be completed in two years of full time effort. The required course work, including six (6) hours of thesis, is 30 graduate hours.

Recommended Programs of Study

The CSIT program offers four core courses which are designed to emphasize the multidisciplinary nature of CSIT and provide students with the foundations for further study. Every CSIT student is required to master at least three (3) of these courses. These courses are Foundations of Computational Science I and II, and Foundations of Applied Information Technology I and II. The CSIT program also includes a number of intermediate and advanced CSIT courses which are designed to provide CSIT students with sufficient depth and breadth to build a common body of knowledge in CSIT and the courses in affiliated departments which are designed to provide the depth and breadth required in application areas.

Students entering CSIT are expected to have a wide range of interests. The recommended program of study includes at least 15 courses. Approximately one-half of these courses will come from CSIT core and advanced courses and the others will come from courses in application areas. In some cases students may have engaged in prior graduate work that will enable them to master the material without taking the courses. Whether all of the courses have been taken or not, students will be expected to demonstrate mastery of the material in the core CSIT and advanced courses and in their application area(s) on the preliminary exam.

In addition to the three (3) CSIT core courses, students will be advised to master at least six (6) courses from the graduate courses offered in an affiliated department, and three (4) CSIT intermediate courses. In addition, they will be advised to take at least two (2) courses from the approved list of CSIT advanced courses. Students are also expected to attend graduate introductory research seminars and colloquia in CSIT and their application areas when available. Though there are no other specific course requirements, students will be encouraged to take other courses in CSIT and in application areas. The specific program of study for students in this program will be determined by the student's Advisory Committee in consultation with the student. This committee is charged with ensuring that the student achieves sufficient depth and breadth in their program of study and that the specific mix of CSIT and application area courses reinforce each other and the student's research area. The initial list of CSIT advanced and affiliated courses are provided in section V.C. of this document.

B. 120 hour Maximum for Undergraduates

This is a graduate program and not subject to the 120 hour maximum for undergraduates.

D. Prerequisites

E. Limited Access Status

This program in not applying for Limited Access status.

C. Description of Required Courses

V.C.1. CSIT core courses

Students in the CSIT Ph.D. program would be required to master at least three of the following courses.

Computational Science I: This is the first course in a two-semester sequence on the role of computational methods, models of computation, computer architectures, and digital computations in scientific applications. Cross-cutting scientific applications selected from topics in materials science, quantum mechanics, data analysis, global warming, earth-quake propagation, will be used to underscore the importance of numerical methods in linear algebra, ordinary and partial differential equations, Monte Carlo methods and tools for software development, performance monitoring, visualization and model evaluation.
Computational Science II: This is the second course in a two-semester sequence on the role of computational methods, models of computation, computer architectures, and digital computations in scientific applications. Cross-cutting scientific applications selected from topics in fluid flow, phase transistions, biological structure and climate prediction will be used to underscore the importance of parallel computing, numerical methods in linear algebra, ordinary and partial differential equations, Monte Carlo methods, and optimization techniques.
Applied Information Technology I: This is the first course in a two-semester sequence covering the application of information technologies of current interest within integrated online environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications currently in the course include collaborative research environments, genomics database application, electronic logbooks, weather prediction, and teaching and learning systems, but specific applications will evolve rapidly to insure inclusion of leading-edge scientific applications of information technology.
Applied Information Technology II: This is the second semester of a two-semester sequence covering the application of information technologies of current interest within integrated online environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications will be selected from distributed physics simulations, remote instrument operation and control and advanced teaching and learning systems, but specific applications will evolve rapidly to insure inclusion of leading-edge scientific applications of information technology.

V.C.2. CSIT Intermediate Courses

These courses are designed to build upon knowledge and skills acquired in the core courses. Note that students may be advised to any of the core courses they have not already taken.

Computational Science II: This is the second course in a two-semester sequence covering computational methods. Topics include sequential and parallel computer applications of linear algebra, numerical methods for ordinary and partial differential equations, Monte Carlo methods, optimization techniques, tools for performance monitoring, visualization and model evaluation.
Parallel Computing Applications: This course will focus on strategies for the development and maintenance of large parallel applications required by a rapidly growing class of scientific and engineering applications. Students will develop a variety of parallel applications to solve science and engineering problems requiring extensive computations.
Parallel Algorithms and Architectures
Applied Information Technology II: This is the second semester of a two-semester sequence covering the application of information technologies of current interest within integrated online environments including environments for distributed scientific computing, online research collaborations, education and electronic commerce. Information technology applications currently in the course include distributed simulations for high energy and nuclear physics, weather prediction, electronic logbooks and teaching and learning systems, but they will evolve rapidly to include leading edge scientific applications of information technology.
Distributed Computing Applications: This course will focus on the strategies for the development and maintenance of large distributed computing applications, such as fortunately parallel computations, remote instrument monitoring and control, grid computing and large-scale, real-time data acquisition. Students will develop distributed computing applications to solve science and engineering problems, such as those listed above.
Distributed Collaboration Environments: This course provides students with an in depth look at the unique problems, tools and requirements of online collaboration environments. It focuses on the requirements, technology and use of online collaboration environments for scientific research, commerce and education.
Photorealistic Computer Graphics: Computer architectures for graphics applications, algorithms for rendering, scattering, realism and lighting techniques.
Scientific Visualization: Serial and parallel visualization algorithms, visualization of complex data sets, techniques for extracting information from complex data sets.

V.C.3. CSIT Affiliated Courses

Biological Sciences

Advanced Evolutionary Biology (PCB 5675): - Needs description
Current Problems in Neuroscience (PSB 6070r): - Needs description
Gene Expression and Development (PCB 5595): - Needs description
Computational Biology ( ): - Needs description

Chemical Engineering

Advanced Biochemical Engineering (ECH 6748)
Advanced Process Control (ECH 5325)
Advanced Chemical Engineering Computation (ECH 5844)
Computational Molecular Dynamics

Chemistry

Principles of Inorganic Chemistry (CHM 5620)
Physical Organic Chemistry (CHM 5245)
Thermodynamics and Statistical Mechanics (CHM 5460)

Computer Science

Artificial Intelligence (CAP 5600)
Artificial Neural Networks (CAP 5615)
Complexity of Algorithms (COT 5410)
Computer Architecture (CDA 5155)
Database Systems (COP 5710)
Object-oriented Programming
Software Engineering (COP 5632)

Economics

Applied Microeconmics (ECO 5114)
Computational Economics I, II (ECO 5408)
Limited Dependent Variable Models (ECO 5427)
Mathematical Demography (ECP 5117)
Simultaneous Equation Models (ECO 5424)
Time Series Analysis (ECO 5425)

Geology

Advanced Topics in Hydrology (GLY 5829r)
Hydrodynamics (GLY 5556)
Numerical Modeling of Groundwater Flow (GLY 5826)

Industrial Engineering

Advanced Simulation Applications (ESI 5524)
Applications of Knowledge Engineering (ESI 5625)
Computational Topics in Industrial Engineering (EIN 5118)
Computer-Aided Manufacturing (EIN 5396)
Optimization on Networks (ESI 5492)
System Modeling and Simulation (ESI 5523)

Mathematics

Advanced Topics in Differential Equations (MAP 6316r)
Advanced Topics in Numerical Analysis (MAD 6408r)
Finite-Element Methods (MAP 5395)
High-Order Finite-Difference Methods (MAD 5757)
Hydrodynamic Stability (MAP 5512)
Numerical Solutions of Partial Differential Equations I (MAD 5738)
Numerical Solutions of Partial Differential Equations II (MAD 5739)
Optimization (MAP 5207)
Perturbation Theory (MAP 5441)
Spectral Methods for Partial Differential Equations (MAD 5745)
Wave Propagation Theory (MAP 5513)

Mechanical Engineering

Advanced Computational Fluid Dynamics (EML 6726)
Computational Materials Science (EML 5930)
Introduction to Computational Mechanics (EGH 5456)
Numerical Methods in Engineering (EGN 5455)

Meteorology

Dynamical Weather Prediction (MET 5541r)
Advanced Time Series Analsysis (MET 6308): - check on number
Objective Analysis (MET 6561): - check on number
Statistical Weather Prediction (MET 5550)

Oceanography

Physics of the Air-Sea Boundary Layer (OCP 5551)
Stability of Geophysical Fluid Flows (OCP 5255)
Turbulence (OCP 5271)

Physics

Condensed Matter Physics I (PHZ 5491): - check on number
Condensed Matter Physics II (PHZ 5492): - check on number
Electrodynamics A (PHY 5645) and B (PHY 5437)
High-Energy Physics I (PHZ 5354) and II (PHZ 5355)
Nuclear Physics I (PHZ 5305) and II (PHZ 5307)
Computational Physics Laboratory (PHZ 5151C)
Management of Scientific Computations (PHZ 5146C)
Statistical Mechanics (PHY 5524)
Stochastic Processes and their Statistical Analysis

Statistics

Computational Methods in Statistics I (STA 5106)
Computational Methods in Statistics II (STA 5107)
Image Analysis (STA 6468r)
Operations Research: Linear and Dynamic Programming (STA 5619)
Statistics in Applications I (STA 5166)
Statistics in Applications II (STA 5167)
Statistics in Applications III (STA 5168)

V.C.4. CSIT Advanced Courses

Advanced Applications in Computational Science: This course examines emerging computational science technologies and their potential applications in science, engineering and other fields. Students will be engaged in developing applications which explore the use of these technologies in selected application areas.
Advanced Applications of Information Technology: This course examines emerging information technologies and their potential applications in science, engineering and other fields. Students will be engaged in developing applications which expand the use of information technology in selected application areas.
Advanced Data Management or Data Intensive Computing: This course provides students with an in depth look at the unique problems, tools and requirements of data intensive computing applications. It includes applications utilizing databases and data management, computer networking technologies, grid computing, management of scientific computations, and the principles, design and optimization of data intensive computing systems.
Online Teaching and Learning Systems: This course provides students with an in depth look at the unique problems, tools and requirements of online teaching and learning environments. It focuses on the requirements, technology and use of online environments for education.
Special Topics in Computational Science and Information Technology: Each semester a number of courses labeled Special Topics in Computational Science and Information Technology may be scheduled. The exact content of each of these courses will depend on the interests and needs of the students and faculty. Three months prior to the scheduling of these courses, individual faculty members submit proposals for special topics courses to the Graduate Affairs Committee. Student or faculty groups are encouraged to approach an appropriate faculty member and persuade him or her to submit a proposal for a course they feel is needed.
Graduate Tutorial in Computational Science and Information Technology: Selected topics in computational science. Reading and analysis of primary literature. Maximum of eight (8) students in each tutorial. May be repeated up to a maximum of fifteen (15) semester hours.
Applied Fuzzy Logic and Neural Networks: Place Holder.
Computational Geometry, Grid/Mesh Generation: Place Holder.
Computational Optimization: Place Holder.
Control Theory: Place Holder.
Distributed Databases: Place Holder.
Domain Decomposition and Parallel Algorithms: Place Holder.
Evolutionary Algorithms: Place Holder.
Image and Time Series Analysis: Place Holder.
Intelligent Systems: Place Holder.
Linear and Nonlinear Programming: Place Holder.
Parallel Computer Architectures: Place Holder.
Parallel Linear Algebra: Place Holder.
Stochastic Systems: Place Holder.
Symbolic Computing: Place Holder.
User Interface Design: Place Holder.
Virtual Reality Environments: Place Holder.
Wavelets in Computation and Analysis: Place Holder.

V.C.5. Additional CSIT Courses

Preliminary Doctoral Examination: Students are required to pass this examination before they can be admitted to the candidacy for the Ph.D. This exam covers core knowledge in computational science and information technology and the student's chosen application area.
Dissertation: The student must write a dissertation on original CSIT research constituting a significant contribution to knowledge and representing a substantial scholarly effort on the part of the student. The minimum number of dissertation hours for completion of a doctoral degree shall be twenty-four (24) semester hours.
Dissertation Defense: The student must successfully defend their dissertation before the student's graduate committee in an open meeting.
Directed Individual Study: May be repeated for a maximum of forty-eight (48) semester hours.
Supervised Research: May be repeated for a maximum of forty-eight (48) semester hours.
Colloquium: A series of lectures given by faculty and visiting scientists. May be repeated for a maximum of ten (10) hours.
Introductory Seminar on Research: A series of lectures given by faculty on the research being conducted by the School of Computational Science and Information Technology. May be repeated for a maximum of two (2) semester hours.
Supervised Teaching: Teaching under the direction of a senior faculty member. May be repeated for a maximum of forty-eight (48) semester hours.
Graduate Seminar in Computational Science and Information Technology: May be repeated for a maximum of ten (10) semester hours.

V.C.6. Additional Activities within CSIT

V.C.7. Other Courses

Computational Models of Physical Systems: (Undergraduate courses) Principles of the design, development and evaluation of computational models, common computational science and information technology techniques, impact of numerical methods, computer hardware and software on model performance, testing and validation of numerical models, and techniques for improving computational models. The course uses real-world applications to illustrate the principles involved.
Principles of Educational Technology
Principles of Computational Science
Principles of Information Technology
Simulation Science

VI. INSTITUTIONAL CAPABILITY

VI-A. Provide a list of affiliated departments, institutes and centers.

Magnet Lab

Structural Biology

GFDI

Currently, the following departments are affiliated with the Computational Science and Information Technology program:

Biological Sciences College of Arts and Sciences
Chemical Engineering College of Engineering
Chemistry College of Arts and Sciences
Computer Science College of Arts and Sciences
Economics College of Social Sciences
Geology College of Arts and Sciences
Industrial Engineering College of Engineering
Mathematics College of Arts and Sciences
Mechanical Engineering College of Engineering
Meteorology College of Arts and Sciences
Oceanography College of Arts and Sciences
Physics College of Arts and Sciences
Statistics College of Arts and Sciences

Activities not on the official books, but ongoing research efforts?

VI-B. Have there been program reviews - other than curriculum committee review?

VI-C. Courses will be delivered in a variety of formats, including traditional delivery on the main campus and non-traditional instruction via distance learning. Currently it does not appear possible for a student to earn either a Master's or Ph.D. degree without spending a significant amount of time on the main campus. However, one of the research goals of this effort is to improve the quality of course delivery and collaboration via the internet. Consequently, it may one day become possible to complete this degree (including the dissertation defense) via the internet.

VI-D. Assessment of Current and Anticipated Faculty for the Proposed Program

BOR Table 2 - current faculty resources.
BOR Table 2 - additional faculty needed.
BOR Table 2 - faculty member workload estimate.

VI-E. Assessment of Current and Anticipated Facilities and Resources

Currently Available Resources - we have all of them except library resources.

a.

Library resources.

b.

Serials.

c.

Classrooms, teaching labs, research labs, office, etc.

d.

Equipment - Computers, Network, Visualization Equipment, etc.

e.

Fellowships, scholarships and graduate assistantships. - Number and amount allocated to the academic unit in question for the past year.
Describe additional new facilities needed.

VII. ASSESSMENT OF IMPACT ON PROGRAMS CURRENTLY OFFERED

A. Budget:

1. Assuming no special appropriation or BOR allocation for initiation of the program, how would resources within the institution be shifted to support the new program?

2. Use BOR Table Three to display dollar estimates of both current and new resources for the proposed program for the first and fifth years of the program. In narrative form, identify the source of both current and any new resources to be devoted to the proposed program.

3. Describe what steps have been taken to obtain information regarding resources available outside the institution (businesses, industrial organizations, governmental entities, etc.). Delineate the external resources which appear to be available to support the proposed program.

NSF support (results of PITAC Report, HR Development)

Foundation Support (Computational Biology)

List the applications for research contracts which have been submitted.

Partnership with computer vendors

VII.B. Describe any other projected impacts on related programs, such as prerequisites, required courses in other departments, etc.

Currently there are no similar programs in any university in Florida nor are there any other programs on the SUS master list which would duplicate this program. This program will offer students within the State of Florida a unique opportunity to become involved in a rapidly growing field. Some of the courses within CSIT will be taught in science departments, computer science, mathematics and potentially other departments. CSIT faculty lines are being allocated to these departments to provide these courses where necessary.

In some instances (detailed in the table below) courses on similar topics are provided as part of science, computer science, computer engineering, electrical engineer or mathematics programs. When those courses are available at FSU, the CSIT program has included them in the CSIT curriculum. Any individual course within this group represents a small fraction of the course work in CSIT, so the number of CSIT students in any one of these courses is expected to be in the range of three to five students. These courses are a part of the standard offerings he programs for which they were first designed and generally have much higher enrollments. Consequently, the impact of CSIT students on these courses is not expected to be significant.

The CSIT curriculum committee will consider including within this program appropriate courses taught by other universities via distance learning. Individual graduate advisory committees will recommend such distance learning courses when deemed in a student's best interest. Currently, we are unable to find such courses within the SUS.

CSIT is committed to distance delivery of as many of its own courses as possible. Part of its research efforts include development of advanced tools and environments to support online teaching and learning. CSIT is currently exploring the possibility of creating a Center for e-Learning and e-Teaching. The goal of this project is to develop the advanced technology and online environment needed to enable effective online teaching and learning. Planned activities include developing a repository for course modules. A proposal is being submitted by FSU faculty in CSIT, Computer Science and Physics and FSU's Office of Distributed and Distance Learning to the National Science Foundation to work with Florida A&M University, Jackson State University, North Carolina A & T on course modules for computer science. A proposal involving faculty from CSIT, the College of Arts and Sciences and the College of Education at and from the College of Arts and Sciences and the College of Education at Florida International University has been submitted to the National Science Foundation. This proposal seeks funds to develop distance learning courses in biology, chemistry, earth science, physics, applied mathematics, computational science and education technology for the professional development of K-8 educators. The program would lead to a Master's degree in Education. This proposal also seeks to establish the technological environment needed to provide continued support of K-9 science, mathematics and technology educators.

VII-B. The graduate programs in CSIT are synergistic with graduate programs in science, engineering, computer science and applied mathematics (and often with other disciplines). Two scenarios are envisioned for students entering a degree program in CSIT. A student may receive a Ph.D. degree in CSIT and an M.S. degree in a traditional affiliated area, or the student may receive a Ph.D. in the affiliated area and a M.S. in CSIT. In the former case, the CSIT program would ensure that the student meet its requirements for the Ph.D. degree and so ensure that the student receive a truly broad education encompassing applied computer science, applied mathematics and one or more science and engineering discipline. In the latter case, the student's activities would be focused primarily on his or her traditional discipline, but the requirements imposed by CSIT for the M.S. degree would ensure the student's grasp of the fundamental principles of high-performance computing in that discipline. In both scenarios, the CSIT program would have high visibility both inside and outside the University to attract high-quality students and would have a stature that it would pass on to its graduates.

This program improves the quality of the educational offerings of the SUS in several ways. It is the first CSIT degree program in the SUS and among the first in the country. The degree program is evolving from FSU's Certificate Program in Computational Science and Engineering should have very high visibility because it is breaking new ground in an area in which many are expected to follow. By taking advantage of this program through novel combinations of M.S./Ph.D. degree options or B.S./M.S. options, this program can be used to help departments attract students that they might not get under normal situations.

This program will provide courses, seminars, workshops and short courses that will benefit students in many graduate programs. The program will create several courses specifically for the CSIT degreee program which will be useful to these students in affiliated departments, this will help reduce the effort required in these departments to provide these offerings themselves. In addition, the program will make use of existing courses in affiliated departments and help increase their enrollment.

FSU has a large number of strong programs in the science and engineering, it has a strong research program in computational science and information technology and a long history in high performance computing and consequently represents an ideal site for this program. In developing this program FSU faculty and graduate research programs in meteorology, oceanography, geology, biology, computer science, materials science, mathematics, statistics and physics have identified computational intensive research activities of critical importance in their field.

In developing this program, one of the key goals is to avoid future duplication of effort. Faculty in the departments listed above have recognized the need for at least some of their students to have receive better training in modern techniques in computational science and information technology and are assisting in the creation of this program. The CSIT steering committee has at least one representative from each of the affiliated departments. The CSIT curriculum committee consists of members of the faculty from computer science, mathematics, physics, biology, oceanography, statistics and engineering. The activities of this committee are being presented on a regular basis to the Science Area Chairs Committee.

VIII. COMMUNITY COLLEGE ARTICULATION

This is a graduate program. We will provide guidelines for undergraduates wishing to prepare for this degree program. These guidelines will include specific instructions for community college students preparing for articulation and eventual enrollment in the Computational Science degree programs.

IX. ASSESSMENT OF APPLICABLE ACCREDITATION STANDARDS

This is a graduate degree program with no corresponding undergraduate program (There is only one undergraduate degree program within the United States in this field, at SUNY-Brockport). Since this field is growing rapidly, we fully expect that accreditation standards will emerge and we will seek accreditation at that time.

At least two professional groups have expressed interest in establishing guidelines for some aspects of computational science and information technology graduate and undergraduate education, the IEEE Technical Committee on Parallel Processing (a subcommittee of the IEEE Computer Society) and the Society for Industrial and Applied Mathematics. Neither group has published definitive standards.

X. PRODUCTIVITY

List all affiliated departments.

Get basic numbers for faculty in CSIT (grants, publications, students, courses taught, other).

Criteria for New Degree Authorization

The proposed program is listed in the current State University System Strategic Plan, and the goals of the proposed program relate to the institutional mission statement as contained in the Strategic Plan.
The proposed program does not duplicate other SUS offerings or, otherwise, provides a convincing rationale for doing so.
There is evidence that planning for the proposed program has been a collaborative process involving academic units and offices of planning and budgeting at the institutional level, as well as external consultants, representatives of the community, etc.
The proposal provides a reasonable timetable of events leading to the implementation of the proposed program.
The proposal provides evidence that there is a need for more people to be educated in this program at this level.
The proposal contains reasonable estimates of headcount and FTE students who will major in the proposed program.
The proposal provides an appropriate, sequenced, and described course of study.
For bachelor's programs, the total number of credit hours does not exceed 120; otherwise, the proposal provides a reasonable argument for an exception to the SUS policy of a 120 maximum. If the university intends to seek formal Limited Access status for the proposed program, the proposal provides an acceptable rationale and includes an analysis of diversity issues with respect to such a designation.
For bachelor's programs, the proposal lists all prerequisites and provides assurance that they are the same standardized prerequisites for similar degree programs within the SUS. If they are not, the proposal provides an acceptable rationale for a request for exception to the policy of standardized prerequisites.
The proposed program relates to specific institutional strengths such as programs of emphasis, other academic programs and/or institutes and centers.
If there have been program reviews or accreditation visits in the discipline pertinent to the proposed program, or in related disciplines, the proposal cites recommendations that were made and provides evidence that progress has been made in implementing those recommendations.
The proposal provides evidence that the institution has analyzed the feasibility of providing all or a portion of the proposed program through distance learning technologies via its own technological capabilities as well as through collaboration with other universities.
The proposal provides evidence that there is a critical mass of faculty available to initiate the program based on estimated enrollments.
For doctoral programs, the proposal provides evidence that the faculty in aggregate have the necessary experience and research activity to sustain the program.
The proposal provides evidence that, if appropriate, there is a commitment to hire additional faculty in later years, based on estimated enrollments.
The proposal provides evidence that library resources are sufficient to initiate the program.
The proposal provides evidence that classroom, teaching laboratory, research laboratory, office, and any other type of space which is necessary for the proposed program is sufficient to initiate the program.
The proposal provides evidence that necessary and sufficient equipment to initiate the program is available.
The proposal provides evidence that, if appropriate, fellowships, scholarships, and graduate assistantships are sufficient to initiate the program.
The proposal provides evidence that, if appropriate, clinical and internship sites have been arranged.
The proposal provides a complete and reasonable budget, reflecting the text of the proposal. Costs for the program should reflect costs associated with similar programs at other SUS institutions.
In the event that resources within the institution are redirected to support the new program, the proposal indicates the source from which funds will be redirected, and provides evidence that such a redirection will not have a negative impact on undergraduate education.
For an undergraduate program, the proposal provides evidence that community college articulation has been addressed and ensured.
For disciplines in which specialized accreditation is available, the proposal indicates whether the institution will seek such accreditation for the proposed program. If the institution indicates that specialized program accreditation will not be sought, adequate justification is provided.
The proposal provides evidence that the academic unit(s) associated with a new degree have been productive in teaching, research, and service.

File translated from T_EX by T_TH, version 2.33.
On 2 May 2000, 22:18.

Begin Faculty hiring		Fall 1996
Began Offering CSE Courses		Fall 1997
Computational Science on SUS
Master Plan (MS & Ph.D.)		Fall 1998
Completed Internal Review
of the Program of Studies		Spring 2000
Report on Feasibility
Study & Authorization to
Plan a New Degree Program		Spring 2000
Begin Teaching Courses		Fall 2000
in Program of Study		Fall 2000
Request for Authorization
to Implement		Spring 2000
Upgrade Classrooms to
Computational Science Labs		Spring 2001
Accept Students		Fall 2001

	Year 1		Year 2		Year 3		Year 4		Year 5
Source	HC	FTE	HC	FTE	HC	FTE	HC	FTE	HC	FTE
Agencies/Industries
Other Grad Programs	16		16		16		16		16
Second Degrees(FSU)
Second Degrees(SUS)
New In-State	5	5	6	6	8	8	8	8	8	8
New Out-of-State	7	7	12	12	15	15	15	15	15	15
New Foreign	4	4	6	6	7	7	7	7	7	7
Other			11	11	32	32	47	47	81	79
Total	32		51		78		93		127

Biological Sciences		College of Arts and Sciences
Chemical Engineering		College of Engineering
Chemistry		College of Arts and Sciences
Computer Science		College of Arts and Sciences
Economics		College of Social Sciences
Geology		College of Arts and Sciences
Industrial Engineering		College of Engineering
Mathematics		College of Arts and Sciences
Mechanical Engineering		College of Engineering
Meteorology		College of Arts and Sciences
Oceanography		College of Arts and Sciences
Physics		College of Arts and Sciences
Statistics		College of Arts and Sciences