EFFECTIVENESS OF COMPUTER ASSISTED INSTRUCTION IN COLLEGE ALGEBRA

This study was designed to determine the extent to which micro-computer instruction affects the learning of mathematics in College Algebra when used as a substitute for traditional methods of instruction. The computer programs involved in the study were designed to teach the student how to find and graph the solution set of linear inequalities with two variables. The lessons were programmed on an Apple II microcomputer and were designed using relatively simple linear branching techniques. The subjects involved in the study were enrolled in two sections of College Algebra in an upper division university. The students were randomly assigned to four groups and each group was taught using varying methods of instruction. One group received traditional classroom lecture followed by textbook homework. A second group was exposed to a computer tutorial program followed by textbook homework. A third group received classroom lecture followed by a computer drill and practice program. A fourth group completed both the computer tutorial and the computer drill and practice programs. Prior to exposure to different teaching methods, each group was administered a pre-test to determine the extent of their knowledge of the subject matter, establish the randomness assertion, and to determine whether or not the groups were equivalent at the outset. After each group received instruction, a post-test was administered to determine relative levels of achievement. One way between subjects analysis of variance was used with the pre-test scores to determine initial differences between the groups. The same statistical procedure was used with the post-test scores. The results of analysis of variance, at the .05 level, indicated that no significant differences in learning took place between the four groups in the study. However, observation of the data seemed to suggest differences which favored the more conventional lecture, homework group. Recommendations for future study included replication of the experiment using the same or modified populations. Additional variables could also be identified such as student attitude, academic background, sex, and age.