Views on Teaching and Learning Preferences for Women and Men in Undergraduate Computer Science

This article explores differences between women’s and men’s views on teaching and learning in undergraduate computer science studies at a Canadian university. The research focuses on perceptions and experiences about learning activities and teaching computer science and how students and teachers view these aspects as valuable for these activities. To better understand research problems and complex phenomena, a mixed-methods concurrent approach was developed for this research, with the qualitative part being the major component (QUAL + quant). The data collected was based on interviews with students and academic staff, surveys, and class observations. Quantitative data from surveys were converted into narratives that were analyzed qualitatively (meaning we qualitized the data). The results show that students who identify as women relied more on formal teaching, while students who identify as men found informal teaching and smaller class sizes more important in their learning approaches. The interaction with the teaching assistants (TAs) was found to be more important for the students who identify as women than for the students who identify as men. As for learning preferences, women preferred more direct instruction, while male students were interested in more complex settings flexibly commuting between competitive, cooperative, and individual learning approaches. Neither women nor men preferred single-gender classes. It was noticed that a small class size is not automatically a solution, as in our case, male students benefited from small classes, while some women felt without adequate support.

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Publication Details

Journal
ACM Transactions on Computing Education
Published
2025-05-30
DOI
https://doi.org/10.1145/3742441
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
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article

Views on Teaching and Learning Preferences for Women and Men in Undergraduate Computer Science

Andreea Molnar, Dorian Stoilescu
ACM Transactions on Computing Education
Teaching and Learning Programming
article

Views on Teaching and Learning Preferences for Women and Men in Undergraduate Computer Science

Andreea Molnar, Dorian Stoilescu
article en

Abstract

This article explores differences between women’s and men’s views on teaching and learning in undergraduate computer science studies at a Canadian university. The research focuses on perceptions and experiences about learning activities and teaching computer science and how students and teachers view these aspects as valuable for these activities. To better understand research problems and complex phenomena, a mixed-methods concurrent approach was developed for this research, with the qualitative part being the major component (QUAL + quant). The data collected was based on interviews with students and academic staff, surveys, and class observations. Quantitative data from surveys were converted into narratives that were analyzed qualitatively (meaning we qualitized the data). The results show that students who identify as women relied more on formal teaching, while students who identify as men found informal teaching and smaller class sizes more important in their learning approaches. The interaction with the teaching assistants (TAs) was found to be more important for the students who identify as women than for the students who identify as men. As for learning preferences, women preferred more direct instruction, while male students were interested in more complex settings flexibly commuting between competitive, cooperative, and individual learning approaches. Neither women nor men preferred single-gender classes. It was noticed that a small class size is not automatically a solution, as in our case, male students benefited from small classes, while some women felt without adequate support.

ACM Transactions on Computing EducationVol. 25(3)
Swinburne University of Technology (AU), Western Sydney University (AU)
Openalex Percentile: Top 89%
Teaching and Learning Programming
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