Persistence in computer science by first-year students at the University of Victoria
| dc.contributor.author | Connors, Joan Marion | en_US |
| dc.date.accessioned | 2024-08-13T18:11:43Z | |
| dc.date.available | 2024-08-13T18:11:43Z | |
| dc.date.copyright | 1987 | en_US |
| dc.date.issued | 1987 | |
| dc.degree.department | Department of Psychological Foundations in Education | |
| dc.degree.department | Department of Educational Psychology and Leadership Studies | |
| dc.degree.level | Master of Arts M.A. | en |
| dc.description.abstract | The primary purpose of this study was to examine possible gender differences in persistence in introductory university-level computer science courses. This investigation was done using path analytical methods to test models for persistence based on earlier studies on gender differences in technical subjects: computer science, mathematics, and the physical sciences. The secondary purpose of the study was to suggest possible intervention strategies based on the path analysis which could possibly increase the persistence rate of all students, but especially female students in computer science. The subjects for this study were all students enrolled in Computer Science 110, the introductory computer science course at the University of Victoria in September, 1986. Of the 308 students who responded to the survey questionnaire, only 269, 189 males and 80 females, who indicated their intention to persist in computer science were retained for testing the path models. The path analytical models being tested involved nine variables: attitude to mathematics; previous computer courses; previous computer experience; age; tendency to stereotype computing and computer users; comfort level, prediction of success, and achievement in Computer Science 110; and persistence measured by whether or not the student enrolled in the subsequent computer science course. The models predicted that the persistence of female students would be affected more strongly by the affective variables--attitude to mathematics, tendency to stereotype, and comfort level--while the persistence of males would be more dependent on the "concrete" variables--previous computer courses, previous computer experience, and achievement in Computer Science 110. The data analysis revealed that the overall model for females accounted for 73% of the joint variance in the included variables for the female sample while the male model accounted for 63% of the joint variance on the included variables for the males sampled. The results of the path analysis revealed that there is a gender difference in the factors which affect the persistence of students in computer science. Of the variables included i n the models, achievement level in Computer Science 110 and previous computer experience related to persistence most positively for both male and female students although the relationship was more positive for males than females. The persistence of females was more positively related to the affective variables than was that of the males. Age and previous computer courses were negatively related to persistence for all students with the relationship being more negative for females. The study seems to indicate that interventions at two levels, prior to university entrance and at the university level, should occur to improve the persistence rate of first-year computer science students. Interventions prior to university entrance could include increasing access to computers for all students in a variety of subject areas; reviewing the high school computer science curriculum; affecting a positive change in the attitude to mathematics of female students; and increasing the awareness of students, teachers and concerned others of factors related to persistence in computer science. At the university level interventions should focus on making the learning environment as supportive and comfortable as possible for students and as such more conducive to persistence in computer science. The models tested in this study are by no means definitive models for persistence in computer science. The results of the study and literature review indicate the need for further study of models for persistence which include these factors as well as academic factors such as high school mathematics, science, and English grades; computer languages previously studied; and the type of computer--mainframe or micro--used in the introductory computer science course at the university. | |
| dc.format.extent | 190 pages | |
| dc.identifier.uri | https://hdl.handle.net/1828/17507 | |
| dc.rights | Available to the World Wide Web | en_US |
| dc.title | Persistence in computer science by first-year students at the University of Victoria | en_US |
| dc.type | Thesis | en_US |
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