Kathie A. Yerion

Gaussian Elimination and Dynamical Systems

Kathie Yerion (yerion@gonzaga.edu) studied mathematics at the University of Montana (Ph.D. 1978) under the direc? tion of William R. Derrick. She began teaching mathematics in 1977 at Gonzaga University in Spokane, and since retraining at IFRICS she also teaches core courses and analytic upper-division courses in computer science. Her main teaching and research interests are in the applied analysis fields of partial differential equations and numerical analysis.

The Development of a B.A. in Computer Science and Computational Thinking

In 2006 the computer science program at Gonzaga University was moved from the College of Arts and Sciences (CAS) to the School of Engineering and Applied Science (SEAS). Before the move, a significant proportion of students majoring in computer science (CS) also majored/minored in another discipline within the CAS. After the move, the proportion dramatically decreased in part because of: institutional hurdles for students double majoring across schools; a lack of CS courses within the CAS (where a greater number of students pursue double majors and minors); and additional CS, Math, and Science credits added to the B.S. degree to meet ABET Accreditation requirements. In 2009, we developed a Minor in Information Technology for CAS students that included courses in “computational thinking”, information technology, and computational courses in other CAS disciplines. In 2013, because of a perceived need for a CS degree with a stronger liberal arts background, we designed a new B.A. in Computer Science and Computational Thinking (BA CSCT). Inspired by our earlier CS degree requiring 18 credits in another discipline, the 2007 Model Curriculum for a liberal arts degree in CS, and a desire by administration to emphasize interdisciplinary coursework, the new interdisciplinary B.A. requires a concentration in a “Discipline for Computational Thinking (DCT)” in which the discipline is selected from CAS programs (including Art, Music, Sociology, etc.). The degree requires that an additional three elective CS courses be chosen to best integrate with the particular DCT chosen. What makes the BA CSCT degree unique is the integration of the computer science courses with the chosen DCT.

Dual degree tracks for computer science majors (abstract only)

Many institutions offer either a Bachelor of Science or a Bachelor of Arts degree program to computer science majors, often depending on what type of college or department houses the major. However, an increasing number of institutions have created dual degree tracks wherein students may choose to pursue either a BS or a BA, with a different set of requirements for each and possibly different credentialing as well. This BOF provides a forum for educators and administrators who currently offer dual degree options to share their experiences with those who are considering adding a second track. Issues of interest such as requirements within and outside the major, enrollment, accreditation, student outcomes, and possibly different career options may be discussed.

Computer Experiments with Diffusion: Finite Differences, round-off Error and Animal Stripes?

This paper describes a module for the teaching of diffusion to mechanical engineering students that can be part of a course on numerical methods or advanced engineering mathematics and as a precursor to a heat transfer course. The purpose of the module is to pull together many of the mathematical concepts in the early education of mechanical engineering students while at the same time introducing them to other important topics – an application of finite differences to the numerical approximation of partial differential equations, the importance of controlling round-off error in computational algorithms, and the time complexity of some numerical models. Students learn these topics through the execution of computer experiments. The first set of experiments cover the numerical approximation of heat conduction in a ring, and a second set cover the numerical approximation of the reaction and diffusion of chemicals that will produce the markings on an animals tail. The learning outcomes of the module are evaluated with data from pre- and post-module surveys given to mechanical engineering students in several sections of a required course in numerical methods.