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The Data Gap: A Potential Barrier to Gender Equity in Computer Science Education

The substantial decline in female enrollment in computer science programs has been a cause of concern, especially as the application of computer technology to an ever-wider range of human endeavor expands. While many studies have examined the attitudes and perceptions of female computer science students, little attention has been paid to studying empirically how classroom interventions-such as curricular choices and pedagogical approaches-may result in disparate impacts in the learning outcomes of male and female students. This study examines recent research articles in leading journals and conference proceedings of computer science education to analyze the gender composition of the subject pool, the extent to which cognitive learning results are disaggregated by gender, and whether there are gender differences in outcomes. This study found that about one-third of studies indicated the gender composition of the subjects, and about one-third of those research subjects were female. About ten percent of papers disaggregated research findings by gender; of those, 30% found differences between male and female subjects. No studies recommended gender disaggregation of data in future work. The lack of data for learning outcomes by gender may be one of the contributors to the paucity of female computer science students; it is possible that interventions found to be more (or less) effective would show different outcomes if the data were considered in light of the gender of the participants. Thus, further research into potential gender differences in the effectiveness of computer science instructional tools is recommended.