Doug Baldwin

Striving for mathematical thinking

Computer science and software engineering are young, maturing disciplines. As with other mathematically based disciplines, such as the natural sciences, economics, and engineering, it takes time for the mathematical roots to grow and flourish. For computer science and software engineering, others have planted these seeds over many years, and it is our duty to nurture them. This working group is dedicated to promoting mathematics as an important tool for problem-solving and conceptual understanding in computing.

Using scientific experiments in early computer science laboratories

Computer science is an experimental science, in the same sense that biology or physics are experimental sciences. Nonetheless, lab exercises for CS1 and CS2 courses are almost never formal “experiments” as the term would be understood in any other science. This paper describes our experiences using formal experiments in CS1 and 2 laboratories. Such exercises are extremely valuable, in part because they help students relate abstract concepts to concrete programs, but more importantly because they lead students into new areas of computing, and even new forms of learning.

A compiler for teaching about compilers

Projects in which students write a small compiler are common in compiler design courses, but even a small compiler can be daunting to students with no prior compiler-writing experience. When I recently taught compiler design, I developed a very small language with a highly modular compiler, focusing the project on implementing the core parts of a compiler without requiring students to build all the infrastructure from scratch. This paper describes the language and its compiler, and their successes (and occasional limitations) for teaching compiler design.

Computer science needs an insight-based curriculum

Computer science is a fundamentally creative endeavour. The creativity necessary for science is not produced through a knowledge of many facts, but through deep insight into the relationships between facts and the methods of inquiry through which they are discovered. The goal of computer science education should be the development of insight into the methods and nature of the discipline, not simply exposure to its current factual content. Unfortunately, few aspects of insight are explicitly addressed in any standard curricula. We call for, and present an outline for, a curricula based on insight rather than topics.

Three years' experience with gateway labs

A gateway lab is an interactive, computer-delivered, tutorial, which helps students make the transition from passively acquired knowledge of abstract concepts to active and concrete use of that knowledge. Colleagues and I have developed a suite of gateway labs for an introductory computer science sequence. These gateway labs are as effective as lectures and textbooks at introducing students to concrete material, students like them better than textbooks, and students seem to do assigned gateway labs more often than they do assigned readings.

A three-fold introduction to computer science

We have developed a new introduction to the computer science major, consisting of two courses, called Science of Computing 1 and Science of Computing 2. This sequence emphasizes balanced development of basic abilities in all three of computer sciences fundamental methods of inquiry (design, theory, and empirical analysis), as opposed to the more traditional emphasis on programming and data structures. Science of Computing 1 introduces students to all three methods of inquiry, in the context of recursive algorithms and their mathematical and experimental analysis. Science of Computing 2 extends, and provides extensive practice in, all three methods. Both courses use a strongly hands-on approach to demonstrate the importance of, and interactions between, the three methods of inquiry. Preliminary results indicate that these courses successfully teach basic design, theory, and empirical analysis, and encourage students to continue studying computer science at a rate as high as or higher than that of traditional introductory courses.

Consul: a parallel constraint language

The author describes a constraint-based language, Consul, that can exploit implicit parallelism. The results are reported of the first stage of the Consul project, which was designed to produce empirical evidence for or against Consul as a parallel language. To produce the evidence, a parallel-execution model is developed that is based on local propagation and uses some important generalizations of earlier work on local propagation. A set of tools was developed to measure the execution of several Consul programs. The results suggest that considerable parallelism is available in Consul programs and that local propagation is a viable mechanism for solving most real-world constraints. The Consul programs demonstrate that programmers can control performance through the proper choice of algorithms, despite Consuls declarative nature.<<ETX>>

Teaching mathematical reasoning across the curriculum

It is all too often the case that CS students learn concepts of mathematical reasoning in a required discrete math course, but fail to apply what they have learned to their CS courses. This may occur because the courses are taught in different departments with little communication between faculty members, so that different terminology may be used in the math course from what is used in the CS curriculum, making it seem as though these two areas are not connected. Even when discrete math faculty collaborate with CS course instructors, students may not carry over what they learned into their CS curriculum.

Integrating empirical methods into computer science

Empirical skills are playing an increasingly important role in the computing profession and our society. In addition to being problem-solvers and designers/engineers, computer scientists must also be capable experimenters in order to develop, test, and evaluate complex hardware and software systems. The widespread use of computers as tools for interdisciplinary research also demands a strong grounding in the scientific method.This panel is designed to promote discussion about innovative methods for integrating empirical skills within the traditional computer science curriculum. Each panelist will define a set of core empirical concepts and skills that they see as essential to computer scientists, with a brief rationale for each. In conjunction, they will describe classroom practices that serve to demonstrate the key concepts and/or develop skills they have identified. Sufficient time will be allocated for discussion and contributions from the audience.

Mechanics of undergraduate research at liberal arts colleges: lessons learned

The benefits of engaging undergraduate students in research are numerous and well-known. Therefore, many schools are encouraging undergraduate research. However, carrying out undergraduate research in a liberal arts school can be challenging – liberal arts schools usually lack the resources typically available in larger research universities; the research programs of faculty at such schools are often insular; undergraduates may not always be adequately prepared or motivated for research; and research is only one of the many activities competing for the time and energy of undergraduate students. The objective of this panel is to discuss how undergraduate research can be successfully carried out in liberal arts schools in spite of all these constraints. We want to examine the mechanics of undergraduate research in such an environment which practices work and which do not.