Equity and High School Computer Science Enrollment

I recently wrote to the Ontario Ministry of Education to obtain female and male enrollment information for Ontario’s high school Computer Studies courses1.

Considering the number of Computer Science (CS) initiatives in K-12 education and the desire to ensure equity within these initiatives, educators, policy makers and researchers should be considering these numbers in an effort to uncover the causes and impact of the profound under-representation of females in high school CS.

An image of a chairs raised on desks in a classroom.

I have shared the enrollment numbers below, but before scrolling down, I would encourage readers to first explore some research and perspectives surrounding gender and computer science enrollment. It is a complex issue that includes a number of influences spanning economical, historical, political, psychological, and social domains.

BARRIERS:
Are there barriers in place that hinder the participation of girls in computing classes?
In 2002, Jane Margolis and Alan Fisher published their influential book Unlocking the clubhouse: Women in computing2. Their research uncovered a number of influences contributing to a gender gap in CS education. They called these influences the doors, walls and windows of the computing clubhouse.

CS HISTORY:
Does the history of CS education and work impact enrollment?
A full understanding of current issues may require an appreciation of the historical forces at play in CS education and the field of work. Patitsas, Craig and Easterbrook3  present a number of barriers that prevented women from participating in CS work and categorize them as either intentional/unintentional and institutional/individual. Janet Abbate’s book Recoding Gender: Women’s changing participation in computing4 provides a rich historical analysis of women in computing in North America and Great Britain.

THE DEFICIT APPROACH:
When considering equity and education issues, what is a deficit approach and why is it dangerous?
A number of authors caution against the tendency to employ a “deficit approach” when discussing the CS education gap. Victores and Gil-Juarez5 explain that too often girls are portrayed as deficient and lacking a normal relationship with technology. Focusing on a need to “fix this deficiency” fails to appropriately consider the social structures that may cause these inequalities in the first place.

STEREOTYPES:
What is the influence of stereotypes on gender and CS education?
Cheryan, Master and Maltzoff6 caution against the impact that often unrecognized stereotypes can have on signalling to girls that CS is not an appropriate field for them. Sometimes parents and teachers unwittingly steer females away from the subject and field, and they fail to recognize the abilities of females.

SCALE:
How can initiatives be scaled in order to have a greater impact?
In terms of solutions and how to scale these solutions, Patitsas, Craig and Easterbrooks7 borrow a tool used in public health called the Universal/Selective/Indicated (USI) model. The USI model categorizes initiatives based on their target audience. Universal initiatives target all students, selective initiatives target those that are underrepresented and indicative initiatives target those who are underrepresented and who may require extra supports. Their article lists and classifies a number of effective strategies used at the post-secondary level.

THE PIPELINE METAPHOR:
Is the pipeline metaphor a good one when considering equity issues in greater CS initiatives?
The pipeline metaphor paints a picture of students enrolling in introductory CS courses in high school, then continuing on to post-secondary studies in CS and ending in a career in the CS field. Vitores and Gil-Juarez5 indicate that there are concerns with the pipeline metaphor, and with the approach to “women in computing” in general. They warn about the paradox of reproducing dangerous assumptions about computing and gender through research that hopes to identify and solve the problem in the field. Instead, they highlight the need for “different researchers’ eyes” that would allow for varied landscapes in the field of women in computing research including acknowledging the limitations of gender binaries and the black-boxing of gender.

NEW EYES AND SENSITIVITIES:
What are some theoretical and research frameworks being used to shed light on these issues?
Research from a technofeminist8 approach is shedding light on the idea that people and objects (such as the hardware and software in CS education) co-evolve, resulting in a need for new perspectives in terms of the way we consider women in computing. Material feminism9 is an approach that reminds us that “matter matters” and that the way that software and hardware are made can have an impact on those who use them.

CURRENT INITIATIVES:
How should these numbers, as well as the research, inform current initiatives in CS education?
The integration of coding to curriculum has become an international phenonmenon10. Canada’s federal government recently announced an additional $60 million to support the CanCode initiative which aims to support young people from kindergarten to Grade 12 in coding and digital skills development11. Across Canada, Alberta12, British Columbia13, New Brunswick14, and Nova Scotia15 all include coding or computational thinking in their current or draft K-8 curriculum and Ontario recently announced plans to update their high school CS curriculum16. How should these initiatives be implemented in order to ensure equity of access to all groups?

As you review the enrollment numbers in Ontario, consider the ideas above as well as next steps as programs and initiatives seek to expand CS education in provincial jurisdictions in Canada and the rest of the world.

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More information about the Computer Studies courses: The current computer studies curriculum includes a total of five courses distributed over grades 10, 11 and 12. These courses include

  • ICS 2O: Grade 10 Introduction to Computer Studies – Open;
  • ICS 3C: Grade 11 Introduction to Computer Programming – College;
  • ICS 3U: Grade 11 Introduction to Computer Science – University;
  • ICS 4C: Grade 12 Computer Programming – College; and
  • ICS 4U: Grade 12 Computer Science – University.

The courses are classified as either open, college preparation or university preparation. The open courses are designed to broaden students’ knowledge and skills in computer studies while the college preparation courses are designed to equip students with the knowledge and skills to meet program requirements for college, apprenticeships, or other training programs. The university preparation courses are designed to equip students with the knowledge and skills required to meet university program requirements. Of the five courses, only two require prerequisites: students must have obtained the ICS 3C credit in order to enroll in ICS 4C and they must obtain the ICS 3U credit in order to enroll in ICS 4U. ICS 2O is not a prerequisite for either the ICS 3C or ICS 3U course.

More information about the data: As reported by schools through the Ontario School Information System. Data includes public and Roman Catholic schools and authorities. Data excludes private schools and publicly funded hospital and provincial schools, care, treatment and correctional facilities, summer, night and adult education day school. Data obtained from the Ontario Ministry of Education through a Freedom of Information and Protection of Privacy Act request.

A big thank you to Ontario teacher Ian McTavish who stepped me through the process of obtaining the data.

Footnotes

1. Ontario Ministry of Education. (2008). The Ontario curriculum grade 10 to 12: Computer Studies.
2. Margolis, J., & Fisher, A. (2002). Unlocking the clubhouse: Women in computing. Cambridge, MA: MIT press.
3. Patitsas, E., Craig, M., & Easterbrook, S. (2014). A historical examination of the social factors affecting female participation in computing. In Proceedings of the 2014 conference on innovation & technology in computer science education (pp. 111-116). New York, NY: ACM.
4. Abbate, J. (2012). Recoding gender: Women’s changing participation in computing. Cambridge, MA: MIT press.
5. Vitores, A., & Gil-Juárez, A. (2016). The trouble with ‘women in computing’: A critical examination of the deployment of research on the gender gap in computer science. Journal of Gender Studies, 25(6), 666-680.
6. Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in psychology, 6(49), 1-8.
7. Patitsas, E., Craig, M., & Easterbrook, S. (2015). Scaling up Women in Computing Initiatives: What Can We Learn from a Public Policy Perspective? In Proceedings of the eleventh annual International Conference on International Computing Education Research (pp. 61-69). New York, NY: ACM.
8. Wajcman, J. (2007). From women and technology to gendered technoscience. Information, Community and Society, 10(3), 287-298.
9. Hekman, S. (2008). Constructing the ballast: An ontology for feminism. In S. Alaimo & S. Hekman (Eds.) Material feminisms (pp. 85-119). Bloomington, IN: Indiana University Press.
10. Gadanidis, G., Brodie, I., Minniti, L., & Silver, B. (2017). Computer coding in the K-8 mathematics curriculum. What works? Research into Practice [Monograph].
11. Canada Department of Finance. (2019). Investing in young Canadians: Budget 2019.
12. Alberta Education. (2018). Mathematics DRAFT Kindergarten to Grade 4 Curriculum.
13. British Columbia Ministry of Education. (2016). British Columbia’s new curriculum: Applied design, skills and technologies.
14. New Brunswick Department of Education and Early Childhood Development. (2016). Middle School Technology Education 2016 Pilot.
15. Nova Scotia Department of Education and Early Childhood Development (2016). Information and Communication Technology/Coding 4–6 Integration.
16. Ontario Ministry of Education. (2019). Education that works for you – Modernizing Learning. Ontario Newsroom, March 15th, 2019.

One Comment Add yours

  1. Dforster says:

    The numbers are staggering. I had no idea. At least they are going up. But still…

    Like

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