As part of continuing research in to the state of women in tech, WITI@UC, would like to enlist students to visualize data from CalAnswers and UCOP to show percentages and changes over time in the participation of women in tech fields, and specifically the participation and persistence of women on the Berkeley campus in various STEM majors. Research will look at intersectionality and potential opportunities for effective interventions to retain diverse talent in STEM majors. Participants will help define the research questions and will be FERPA trained to leverage more detailed data sets.
The Project
The objective of the Visualizing Women in Tech research team was to examine the effectiveness of the computer science grade cap and identify opportunities to make the major more equitable. Our project fits within the broader conversation of gender, race, and income barriers in STEM and overall inequities surrounding computer science at Berkeley. We are trying to accomplish progress towards making the computer science major and classes more equitable. Ultimately, we are hoping to improve diversity and inclusion within computer science through potential modifications to the grade cap, class structure, and institutional support.
Our data is primarily campus data composed of students' applications to Berkeley and their grades, so it is confidential. Bias could come from the data stored from applications, as students may have inaccurately reported their data. Additionally, since there was missing data, some of our data could have been misreported or not recorded in full. Since our research was confidential, we cannot include any of our specific findings (e.g., images and links), but we find that the publicly available graphs from Berkeley’s campus data below are useful for illustrating the problem we were trying to solve. The left graph shows the number of female computer science majors (457) versus the right, which shows the number of male computer science majors (1236.5). These numbers demonstrate the lack of diversity and gender equity in the CS major.
Some of the specific questions we researched were if the GPA cap affects men and women differently, if CS performance is affected by generational status, how participation in pre-introductory CS classes affects performance in CS61A/B, and the impact of prior experience on students intending and declaring computer science. Additionally, our team developed a logistic regression predictive model on the probability of females, males, and URM to declare.
[[{"fid":"2340","view_mode":"width_400","fields":{"format":"width_400","field_file_image_alt_text[und][0][value]":false,"field_file_image_title_text[und][0][value]":false},"type":"media","field_deltas":{"1":{"format":"width_400","field_file_image_alt_text[und][0][value]":false,"field_file_image_title_text[und][0][value]":false}},"attributes":{"class":"media-element file-width-400","data-delta":"1"}}]][[{"fid":"2341","view_mode":"width_400","fields":{"format":"width_400","field_file_image_alt_text[und][0][value]":false,"field_file_image_title_text[und][0][value]":false},"type":"media","field_deltas":{"2":{"format":"width_400","field_file_image_alt_text[und][0][value]":false,"field_file_image_title_text[und][0][value]":false}},"attributes":{"style":"float: left;","class":"media-element file-width-400","data-delta":"2"}}]]
Source: https://opa.berkeley.edu/campus-data/our-berkeley
As for work left to be done, our team only predicted and analyzed the current data stored in the datasets, but we didn’t include personal stories/opinions from students. We feel that it would’ve been interesting to use interviews to develop a more thorough story. This work also definitely requires long-term analysis, as Berkeley’s student population is constantly growing and evolving, and there will likely be more diverse student backgrounds in the future.
Unfortunately, we cannot include any of our specific data in this blog post because of student confidentiality. However, through our analysis, we found that the grade cap in general has shown to decrease the diversity within the CS Major and there are crucial changes needed in the CS major. We presented our research to different faculty members with the hope that our findings will help contribute to more intervention through enrichment programs such as academic help and community support aimed at URM, women, and those without prior experience. We highly encourage more universities to take part in examining their computer science department and how might they eliminate structural inequities in computer science education.
Researchers: Klara Chisholm, Isaac Sloan, Cheryl Liu, Anissa Rashid, Mary Petrovich, Shreya Ayyagari
Project Mentors: Vivian Tsang, Rebekah Tang
Supervised by: Jill Finlayson