How to increase women’s participation in data science and STEM fields

SARAO has released a case study on DARA Big Data Programme highlighting how to increase women's participation in data science and STEM fields.

women in data science and stem

The fourth industrial revolution (4IR) has begun. And Africa is not only lagging; the continent also lacks skilled human resources, especially women, that would enable it to take advantage of this technological advancement.

The World Economic Forum (WEF), in its 2020 Global Gender Gap report, projects that it will take sub-Saharan Africa 95.1 years and North Africa 139.9 years to close their respective gender gaps. According to the report, only 26% of professionals employed in data and artificial intelligence roles were women.

Klaus Schwab, WEF’s founder, described the 4IR as the fusion of technologies blurring the lines between physical, digital, and biological spheres. It involves using and adopting technologies such as artificial intelligence, cloud computing, big data, machine learning, robotics, 3D printing, the Internet of Things, and advanced wireless technology.

It’s vital to spotlight the persistent gender gaps, especially in these jobs of the future. The awareness would engender new pathways to economic opportunities for women in the fourth industrial revolution. It would also foster the creation of gender parity initiatives.

African countries need skilled human resources to thrive in the 4IR global economy. Their ability to provide good health and fight diseases, protect their environment and natural resources and develop new industries and technologies depends on their population’s scientific knowledge and skills.

The fourth industrial revolution requires human resources skilled in science, technology, engineering and mathematics (STEM) fields. Women must participate in the 4IR, so there would be diverse technological innovations addressing societal challenges.

The Human Capacity Development division of the South African Radio Astronomy Observatory (SARAO) has released a report titled: “A Case Study of the UK – South Africa Newton Fund Development in Africa with Radio Astronomy (DARA) Big Data Programme”.

The report examined the existing gender gap in the DARA Big Data programme and the factors contributing to the gender gap in developing human capacity in data science and STEM fields in Africa.

The authors are Dr Bonita de Swardt, SARAO’s Programme Manager for Strategic Partnerships; Monushia Zimri, Research and Development Intern at the South African Agency for Science and Technology Advancement (SAASTA); and Linda Camara, Communications Manager at the African Institute for Mathematical Sciences (AIMS).

Between 2017 and 2020, the DARA Big Data programme provided data science training and development initiatives to science and engineering students from South Africa and the Square Kilometre Array (SKA) Africa partner-countries. The eight SKA Africa partner-countries are Botswana, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Namibia, and Zambia. The SKA is an intergovernmental undertaking to build the world’s largest radio telescope–a scientific driver for research relevant to the 4IR.–in Australia and South Africa.

DARA Big Data training and development initiatives include the Big Data Africa School (2017-2019), which introduced students to data science and machine learning fundamentals through exposure to various tools and techniques that they can use to work efficiently on large data sets. A total of 89 students participated in the three editions, and only 38% were female.

Another initiative is the DARA Big Data Scholarships (2018-2019). It provided Masters and Doctoral degree scholarship opportunities to students from the SKA Africa partner countries to undertake a research project that focuses on data science applications in one of the DARA Big Data thematic areas of astronomy, health or agriculture. Over three editions—DARA put out two separate calls for applications in 201817 people, 41% of whom were female, received scholarships.

DARA Big Data Programme also organised or provided financial support for students to participate in hackathons. The hackathons are short, introductory-level data science training that takes place over two or three days. Between 2018 and 2020, DARA Big Data hosted four hackathons in Botswana, Madagascar, Namibia and Zambia. And out of the total 85 students who participated, only 31% were female.

The last DARA Big Data initiative is the Africa Data Science Intensive (DSI) programme. It’s an intermediate- to advanced-level data science training course with a focus on exposing participants to the latest algorithms and techniques in data science, industry trends and network building, as well as building the necessary real-world skills in transitioning to a data science role in industry, academia or through entrepreneurship.

DARA Big Data programme funds its initiatives through the UK–South Africa Newton Fund. DARA Big Data programme also has partner universities, research and educational institutions in the UK and South Africa. The students awarded scholarships, for instance, undertake their degree at a partnering university in the UK. These academic partners are:

  • University of Manchester (UK)
  • South African Radio Astronomy Observatory (SARAO)
  • Inter-University Institute for Data-Intensive Astrophysics (IDIA, South Africa)
  • International Astronomical Union’s Office of Astronomy for Development (IAU OAD)
  • Centre for High-Performance Computing (CHPC, South Africa)
  • Leeds University (UK)
  • University of Sussex (UK)
  • University of Hertfordshire (UK)
  • York University (UK)

Why women don’t pursue a career in data science and STEM fields

According to the 2021 Women in Data Science report, these are the challenges hindering women from excelling in STEM fields:

  1. Insufficient institutional capacity, infrastructure and resources to support STEM courses
  2. Fewer opportunities for women compared to men for advancement in STEM.
  3. Lack of scholarship opportunities and financial limitations to pay for basic needs
  4. Women are perceived as less competent.
  5. Workplace environments and unsupportive work environments favour men.
  6. Language barrier
  7. Lack of self-confidence
  8. Patriarchal perception of certain professions by society
  9. Cultural challenges with the career choice – unsupportive family
  10. Absence of role models and mentors
  11. Lack of policies against sexual harassment

Recommendations:

The report found that belief in personal capabilities to undertake STEM-related subjects and encouragement from role models such as teachers, family members, or friends are two main factors influencing most females to pursue a STEM career.

Based on its findings, the Women in Data Science report recommends the following interventions to increase women participation in data science and STEM. To increase women’s participation in data science:

  1. Increase the application numbers from females towards data science training and development programmes, which will lead to increased participation and inclusion of women in initiatives.
  2. Provide female mentorship or role models throughout training initiatives to ensure women’s exposure in data science professions during the training event.
  3. Establish women in data science networks with alumni who have participated in past training and development initiatives.
  4. Establishment and promotion of women in data science and artificial intelligence events in Africa.
  5. Targeted opportunities for training and development for African women in data science and AI
  6. Embedding basic computer programming skills in girls at a primary and secondary school level.

To increase women’s participation in STEM:

  1. Mentorship and workshop initiatives that reach out to young girls and women to provide avenues for entry
  2. Female awareness campaigns/events to empower women.
  3. Early childhood interventions
  4. Support work-life balance and create welcoming work environments
  5. Flexible working hours
  6. Focus on changing the mindsets of both boys and girls at a young age
  7. Empower teachers so that they can, in turn, empower young girls to be more confident in science and mathematics
  8. Incorporate basic computer skills at the primary and secondary level
  9. Support women in data science and artificial intelligence by providing scholarships and internships
  10. Professional societies at universities to provide structured professional development opportunities for women

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