Graduate Courses

Computer Science Courses

CSCI 5613. Computers in Education. An introduction to basic functioning of a computer and basic problem solving using the computer with special attention given to the educational setting. Programming concepts are introduced but programming is not the major focus. May not be counted as degree credit in Department. Three lecture hours a week. Credit: Three hours. Cannot be counted as satisfying mathematics requirements.

CSCI 5643. Internet/Intranet Services: Design and Implementation. Design and implementation of Internet/Intranet network information services including FTP, World Wide Web, and conferencing. Preparation and integration of digital graphics, animation, video, audio, and script-based (Java/Java Script) content. Students will design and build an intranet, install and maintain servers, and prepare multimedia rich content. Prerequisites: CSCI 1403, CSCI 3002, CSCI 5613 or equivalents. Three lecture hours a week. Credit: Three hours.

CSCI 5653. Technology Issues, Achievements and Challenges in Education. Current developments and open research issues for technology in education. Includes current and future trends in multimedia, simulation, communication, networks, AI, intelligent tutoring systems, learning communities, learning technologies, security concerns, communication strategies, ethical and leadership issues. Prerequisites: CSCI 5613, CSCI 5843 or equivalents; completion of other Master Technology Teacher Courses or permission of the instructor. Three lecture hours a week. Credit: Three hours.

CSCI 5663. Statistical Programming. Design of statistical programs to manipulate raw data, generate reports and analyze data. Numerous case studies demonstrate appropriate analysis based on the experimental design. Advanced statistical research methods such as ANOVA, MANOVA, repeated measures ANOVA, Multiple Linear and Logistic regression, factor analysis and survival analysis SAS. Prerequisite: six hours undergraduate statistics or three hours graduate level statistics or equivalent. Three lecture hours a week. Credit: Three hours.

CSCI 5703. Computer Science I. Introductory course in basic computer structure and programming with applications to numerical and non-numerical computation. An interdisciplinary approach is stressed. May not be counted as degree credit in Department. Three lecture hours a week. Credit: Three hours.

CSCI 5713. Computer Science II. Topics in data structures, information storage and retrieval, text analysis and other more advanced concepts in computer structure and programming. Prerequisite: CSCI 5703 or permission of instructor. Three lecture hours a week. Credit: Three hours.

CSCI 5753. Computer Graphics. The study of computer generated graphic images. Evaluation of current graphic hardware, software and applications. Investigation and implementation of algorithms used to perform such graphics functions as windowing, clipping, two- and three-dimensional transformations, projections, and hidden line/surface removal. Prerequisite: CSCI 5713. Three lecture hours a week. Credit: Three hours.

CSCI 5783. Computer-Assisted Instructional Systems. Introduction of models used in computer-aided instruction. Introduction of linked-lists and network methods for presenting information as related to CAI systems. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

CSCI 5793. Statistical Computer Packages. Survey of major statistical computation program systems with special emphasis on SPSSX and BMDP. Basic concepts of control language and data set preparation, program execution and interpretation of statistical program output. Prerequisite: Intermediate statistics or permission of the instructor. Three lecture hours a week. Credit: Three hours.

CSCI 5813. Concepts of Data Warehousing and Data Mining. Review of the basic concepts of file systems, databases, data warehousing, data mining and related statistics. Summary of database management, modeling, design, and life cycle is provided as related to data warehousing. Methods of extracting information from a large database by use of data mining techniques are studied. Techniques include: machine learning, decision algorithms, statistical modeling and clustering. Three lecture hours a week. Credit: Three hours.

CSCI 5823. Modeling Machine Learning. Introduction to Widrow's LMS Algorithm, K-Map Clustering, and various topics from genetic programming and adaptive algorithms. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

CSCI 5843. Microcomputer Applications. Analysis of current application software including disk operating systems, word processing, spreadsheets, data bases, graphics, communications and integrated systems. Applications to problem solving in many disciplines will be studied. Efficiency and effectiveness of peripherals will be critiqued. Prerequisite: CSCI 5613 or equivalent or permission of instructor. May not be counted as degree credit in Department. Three lecture hours a week. Credit: Three hours.

CSCI 5893. Statistical Packages II. A further survey of major statistical computation program systems. Concepts of control language and data set preparation, program execution and interpretation of statistical program output will be studied. Prerequisite: CSCI 5793: Three lecture hours a week. Credit: Three hours.

CSCI 5913. Individual Study. Selected topics in advanced computer science. Credit: Three hours. May be repeated for additional credit.

CSCI 5921. Statistical Analysis with Computers. Exposure to available University resources in research design and data analysis, including fully computerized statistical analysis techniques. Appropriate for graduate students who are at least in the proposal/prospectus phase. Prerequisite: Permission of the instructor. May be repeated for additional credit. Credit: One hour.

CSCI 5953. Cooperative Education. Cooperative work-study arrangement between business, industry, or selected institutions with the University. Nine laboratory hours per week. Credit: Three hours.

Mathematics Courses

MATH 5003. Mathematical Concepts in the Educational Setting. Problem solving, reasoning, sets, logic, geometry, algebra, trigonometry, matrices, statistics and probability, sequences and series, graph theory, integration, differentiation, vectors. Three lecture hours a week. Credit: Three hours.

MATH 5103. Problem Solving in the Elementary Grades. For students desiring professional development in strategies for teaching problem solving techniques in the elementary classroom. Number concepts, patterns and relations, functions, geometry, measurement, probability, statistics, operations and computation. Incorporate children's literature, manipulatives and relevant technology. Three lecture hours a week. Credit: Three hours.

MATH 5203. Problem Solving in the Secondary Grades. Study of problems with multiple solutions or alternative approaches; strategies for solving problems; assessment techniques; cooperative grouping methods; critical thinking skills. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5213. Math Manipulatives in the Classroom. Study of variety of manipulatives and their use in modeling math concepts in grades K-12; development of instructional sequences based on the constructivist approach to learning. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5303. Algebra in the Mathematics Classroom. Topics in algebra with an emphasis on problem solving, patterns, relationships, order pairs, prime and composite numbers, orders of operations, exponents number sentences, ratios, proportions, percents, modeling, formulas, equations, graphs, functions, systems of equations. Three lecture hours a week. Credit: Three hours.

MATH 5313. Geometry in the Mathematics Classroom. Topics in geometry with an emphasis in problem solving, shapes, angles, polygons, circles. Pythagorean Theorem, symmetry, transformations, measurement of area, volume with an emphasis on technology. Three lecture hours a week. Credit: Three hours.

MATH 5423. History of Mathematics. A survey of the historical development of various mathematical topics, including geometry, algebra and number theory. A study of the work of past mathematicians, including Archimedes, Euclid, Fermat, Newton and mathematicians of the 19th and 20th centuries. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5483. Theory of Probability and Statistics I. Basic principles of probability; combinations and permutations; conditional probability and independence; common discrete and continuous probability distributions, their properties and applications. Three lecture hours a week. Credit: Three hours.

MATH 5493. Theory of Probability and Statistics II. Sampling distribution theory and the Central Limit Theorem; point and interval estimation; hypothesis testing. Prerequisites: MATH 5483 or equivalent. Three lecture hours a week. Credit: Three hours.

MATH 5513. Matrix Algebra. Matrices; determinants; matrix inversion; rank and equivalence; linear equations; eigenvalues. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5523. Introduction to Number Theory. Divisibility properties of integers; prime numbers; congruences; multiplicative number-theoretic functions. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5543. Symbolic Logic. Symbolic analysis of English sentences. Formal proofs of validity via truth tables and deduction. Symbolic analysis and classification of relations. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5563. Logic, Sets and Real Numbers. Applications of logic and set theory to the development of the real number system. Equivalence relations will be used to define the natural numbers and create the reals from them. Prerequisite: MATH 5543. Three lecture hours a week. Credit: Three hours.

MATH 5573. Statistical Methods I. Probability distributions, graphical representations, curve fitting, hypothesis testing, regression and correlation, applications. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5583. Statistical Methods II. Statistical research tools including analysis of variance, chi-square tests, regression (simple and multiple), logistic regression, correlation, non parametric method, and survival analysis. Use of SPSS for the PC. Prerequisite: MATH 5573 or MATH 1713 or consent of instructor. Three lecture hours a week. Credit: Three hours.

 MATH 5593. Differential Equations. The existence and uniqueness for differential equations and systems of differential equations. General theory to specific types of differential equations of a single variable. The basic theory for linear and nonlinear systems. Linearization. Stability. Hamiltonian Systems. Applications with MAPLE. Three lecture hours a week. Credit: Three hours.

MATH 5763. Methods of Numerical Computation. Iterative approximation of polynomial roots, error analysis, linear systems, numerical differentiation and integration, numerical solution of differential equations, optimization, least squares, and orthogonal functions. Prerequisite: MATH 3123, CSCI 5703. Three lecture hours a week. Credit: Three hours.

MATH 5833. Computer-Aided Mathematical Modeling. Instruction in the use of computer-aided techniques in the mathematical modeling of biological and physical systems. Such models included in the course are feedback models, compartmental models, and simulation models. Also such computer software packages which are useful in the solution of similar problems are introduced. Prerequisite: Permission of the instructor. Three lecture hours a week. Credit: Three hours.

MATH 5903. Special Topics in Mathematics. Variable content. Three lecture hours a week. Credit: Three hours. May be repeated for additional credit.

MATH 5911. Individual Study. Selected topics in advanced mathematics. Credit: One hour. May be repeated for additional credit.

MATH 5913. Individual Study. Selected topics in advanced mathematics. Credit: Three hours. May be repeated for additional credit.

MATH 5953. Cooperative Education. Cooperative work-study arrangement between business, industry, or selected institutions with the University. Nine laboratory hours per week. Credit: Three hours.

MATH 5973. Professional Paper. Credit: Three hours.

MATH 5983. Thesis. Credit: Three hours.

MATH 5993. Thesis. Prerequisite: MATH 5983. Credit: Three hours.