An experimental course in elements of digital computer technology for the training of computer programmers
Jessica Dragonette Gordon · 1987
A course has been developed in the conviction that adult students will become better computer programmers if they have some understanding of the inner workings of the machine they program. Adequate preparation for a career programmer must include not only immediately marketable skills, but enough knowledge of basic principles to make it easy to adjust to new situations and make useful inferences about how things work. The course attempts to provide the students, at the beginning of the training, with a useful mental model of the machine. there are three major topics: first, the requirements for the encoding of information in a binary storage device; this includes the methods typically employed for the storage and manipulation of numeric data. Second, the logical foundations of computation, including an introduction to Boolean algebra and its application to the design of simple circuits. Third, the architecture of a hypothetical computer of the von Neumann type; the student is given the opportunity to write programs in pseudo-machine code and a simple assembler language. The course, called Elements of Digital Computer Technology was developed at Columbia University as a requirement in a three-semester certificate program intended to prepare students from other fields to enter business data processing as a new career. Four chapters of a projected seven-chapter textbook have been completed, focusing on the first and third of major topics. Course and text materials were subjected to a formative evaluation with four successive classes over two years. Demographic, academic, aptitude, and performance data were collected for 118 students. Performance in the course is significantly associated (level < .001) with performance in the program, with performance in two subsequent Cobol programming courses, and with job placement. Contingency table analysis reveals no significant relationships (level < .05) between performance in the program and the any of the following: age, sex, occupation, highest degree, undergraduate major, years of mathematics after high school. Significant association (<.05) is seen between overall performance and scores from only one component of the aptitude test.