Gender Differences in Final Grades in Computer Science Courses at the University of Tartu
Name
Anne-Mari Kasemetsa
Abstract
Despite numerous initiatives and research efforts dedicated to increasing female representation in Computer Science, the overall percentage of women in this field continues to remain low. In order to help womens studies in Computer Science, it is important to analyse academic outcomes based on gender. That way the possible gender differences in learning aren’t overlooked. This Bachelor thesis compared the final grades in six compulsory courses of the Computer Science curriculum in the University of Tartu. Out of the analysed courses two are mathematical: Calculus I (MTMM.00.340) and Discrete Mathematics (LTMS.00.019), two involve programming: Object-Oriented Programming (LTAT.03.003) and Algoritms and Data Structures (LTAT.03.005), and two teach basic knowledge of the Computer Science field: Databases (LTAT.03.004) and Operating Systems (LTAT.06.001). The aim of the research was to see how are women and men performing in Computer Science studies and whether there are any major gender differences to be found. This was accomplished by constructing a data analysis of gender differences in the six courses over the period of 5 years (2018-2023). In total there were 3 different analysis: general, module based and subject based analysis. The results showed that the academic performance of women and men in computer science is very similar. Only very few statistically significant differences were found between the genders. Many of the found statistically significant differences favored women, except in one subject: Operating Systems (LTAT.06.001). Based on the results, it can be argued that women perform equally well or in some instances even better than men in Computer Science studies. The analysis confirms that supporting women's participation in computer science is warranted, as there are no significant gender differences in academic performance and outcomes.
Graduation Thesis language
Estonian
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Marina Lepp
Defence year
2024