After a year of lockdowns, online family gatherings, digital education, and distance work, there is no doubt that the world has become immensely digitalized, creating a huge demand for tech professionals. Why is it then that women are still practically invisible in the field? As a matter of fact, only around 16.5% of the IT sector are women in the EU28 zone, according to Eurostat. The low representation of women in tech is clearly a social problem, part of the bigger framework of gender inequality. But the truth is, women’s scarcity in IT has economic and technological repercussions as well, so fixing the issue is both timely and relevant. But how can we do that? Well, there are a number of approaches we can take. To increase women’s involvement in IT, we can focus on “fixing the numbers” or “fixing the institutions” for example. Studies (including one on the present website), however, underline that the low number of women in IT cannot be efficiently addressed by either of those approaches. Instead, focusing on education and “fixing the knowledge” seems the most effective on the long run. Why is that? And how can we go about it? In this blog post, that is what I would like to share with you.
Why education?
Cross-national studies revealed that the stereotypes that link science to men, and thus, to boys, are the main causes behind women’s – and girls’ – exclusion from STEM-fields (Nosek et al., 2009). In my native country, Hungary, women’s involvement is even lower than the EU’s average. In order to find out why this is, researchers thought we need to look at education. A series of interviews were made with high school girls about their reluctance to choose STEM majors (Nagy, 2014; Papp & Keszi, 2014). Girls confessed that they refuse to apply for STEM majors because they consider those fields to be “masculine” in which they could not fulfill their “feminine roles.” Others explained their reluctance with having bad experiences in high school STEM classes as teachers treated them differently than boys. Unfortunately, the situation in higher education is not much better either. In Hungary, only around 20% of all students majoring in STEM are women (while the world average is a little higher, according to Ramirez & Kwak, 2013). So, women that do end up choosing IT majors at university find themselves tokenized, with infrastructures that do not necessarily support them. Consequently, the drop-out rates are extremely high, which makes it no wonder why the percentage of women at IT jobs remains so low.
It is clear then that the role and responsibility of teachers is immense in directing girls towards the tech sector as much as keeping them in the field. If we want to have a more diverse workforce in the IT sector, educators need to create a more hospitable environment for girls and women in IT education. I am a university educator myself, endowed with a strong sense of commitment for (and a doctoral degree in) gender. Teaching at a (state) tech university which is located in and administered by a country where the concept of gender has been stigmatized and gender studies banned, I recognized I had an important job to do. In order to put the theory into practice, I have set myself the goal to design my classes with an eye for diversity and inclusion, sensitizing tech-students about their social responsibilities such as gender equality, tolerance, and cooperation. Now I would like to you share my experiences with you.
A course to teach gender to tech students
In 2018 a new, four-semester-long Computer Science (CS) program was launched at the Faculty of Informatics at Eötvös Loránd University, Budapest. As part of the program, students are expected to learn and practice professional English language use, not just programming, given that most of the CS literature is in English. This two-semester-long language course, scheduled for the first two terms of the program, is the only soft-skills course students need to take as part of their education. The purpose, as described in the curriculum, is to acquaint students with CS topics and materials in English from around the world, that is, rather vague. This is why I saw an opportunity to engage students in diversity / gender studies, while doing “CS language practice.”
How was the course designed?
To design the course, I used the insights of various researchers focusing on diversity education for tech students (Frehill & McGrath Cohoon, 2015, Mansour & Wegerif, 2013; Margolis & Fisher, 2002). In order for IT classes to be efficient, the authors underline the importance of using teamwork and cooperation when solving tasks; humanizing and contextualizing programming; and presenting role models as part of the study material. The specific circumstances of the course also had to be taken into consideration. There were two factors that emphatically called for the application of Margolis and Fisher’s tools: on the one hand, the large number of students with different language competence levels within each group made it impossible to plan a lot of – undifferentiated – classwork. Instead, group and pair work seemed to be more suitable as that way students could and were forced to help and complement each other while solving tasks together. On the other hand, as the student body is overwhelmingly homogeneous regarding gender and ethnicity (the majority is white, male, and Hungarian), it was also obvious that diversity, difference, and inclusion had to be brought into the class through the study materials. Altogether, both with the methods (of differentiated education and teamwork) and the contents (of diverse materials and contextualized tasks), the course was aimed to improve students’ cooperational and social skills, in order to make them better language users, but also better programmers.
What is the content of the course?
As for the content of the course, it was designed primarily to demonstrate the human side, the social context, and the diversity of IT to students who are interested but may not yet be deeply experienced in IT. The course was divided into two parts (semesters) in a way that the materials did not only connect to but they also derived from each other. While the first part was supposed to lay the foundations of the coursework, the second was meant to elaborate on and deepen the concepts and the skills. All the communication, skills development, or analytic activities of the course were based on eight, high-quality, English-language TED-talks covering a specific IT topic. They are the following:
Agüera y Arcas, Blaise: How PhotoSynth can connect the world’s images
Arar, Raphael: How we can teach computers to make sense of our emotions
Bracy, Catherine: Why good hackers make good citizens
Buolamwini, Joy: How I’m fighting bias in algorithms
Feinberg, Danielle: The magic ingredient that brings Pixar movies to life
el Kaliouby, Rana: This app knows how you feel – from the look on your face
Lupi, Giorgia: How we can find ourselves in data
Redmon, Joseph: How computers learn to recognize objects instantly
The course material was compiled in order to reflect and emphasize the diversity, the rich variety of contexts, and the human aspects of IT, so students can more easily find themselves in and connect with CS. As one of the guiding concepts of the course, diversity appeared in the material on several levels. First of all, the speakers were selected so they can represent and present different subtopics within IT in order to showcase the wide options within the field. Next to expertise, the identity of the speakers was also meant to be a testament of difference (and inclusion). Regarding their ethnicity and origins, the speakers are not at all homogenous: there are white and black tech experts; European, American, and African IT professionals. Religion and sexual orientation appear as a matter of choice as well. Finally, as far as gender is concerned, it was a very conscious decision to include a fair number of women among the presenters. Five of the eight speakers are women (C. Bracy, J. Buolamwini, D. Feinberg, R. el Kaliouby, and G. Lupi), as fig. 1 shows. With this, the course aimed to clearly demonstrate, both to the few female students and to the masses of male students, that women also have a place in IT. By watching such role models speak, students could realize that women can be authentic, inspirational leaders and experts of IT as well. Altogether, the course material was designed to make students conscious of the fact that IT is, and has to be, a diverse field, in the gender aspect and many others.
As Margolis and Fisher emphasize, it is also essential to contextualize IT. As it was mentioned before, all the talks present a specific and different area within technology, such as computer vision, object recognition, animation, data visualization, and so on. Each of them place their respective technology within a specific context, offering insight into what can be done with coding. To give an example, one of the speakers demonstrated in her talk that machine learning can be used for the development of emotion-enabled apps which can facilitate emotion recognition.
Besides giving context to IT, it was also an important goal to humanize it. Even in this aspect all the selected talks fare well: each of the speakers stress the importance of social responsibility when putting their specific technology to practice. To demonstrate this, it is best to continue elaborating on the previously mentioned video. When talking about her company that works with emotion recognition, el Kaliouby was quick to emphasize the social relevance of such technology. She explained that an emotion enabling app can not only help people who are visually impaired or are on the autism spectrum decode emotions, it can also assist all of us to communicate and connect better with our tools and each other. The fact that every speaker approached their topic in a similar matter, not failing to mention the social importance of their projects, students could become aware that social responsibility is key in IT, even if this aspect is rarely addressed during their CS studies.
How did the students feel about it?
In order to check the effectiveness of the methodology, students were asked to reflect on various concepts, core to the course, multiple times. Both at the end of the first term and at the end of the second term, in practice and in test situations they had to contemplate on (1) what they think about cooperation and teamwork, (2) what they consider to be the main social values in IT, and (3) who they were inspired by. This way, the course not only offers them situations to practice the values Margolis and Fisher define to be effective learning tools, such as group work, the humanization and contextualization of IT, and role models, but it also makes them become conscious of them.
Students’ feedback reflected that they believe cooperation is crucial not only for efficiency and swiftness, but also because team members can complement each other and produce more diverse and socially more inclusive solutions. As for values in IT, students listed equality, inclusiveness, diversity, and lack of discrimination. Some of them even addressed that it is their responsibility as future programmers to respect and enforce these values. Finally, when students were asked which speaker inspired them throughout the course, they responded in a lengthy and passionate way. It is also worth noting that several speakers were named, not just one, which shows that the diverse people can be inspired by diverse role models included in the course material. It is worth noting that multiple students underlined that they could relate to the personal stories (often about initial struggles) of the speakers and that seeing them succeed gave them hope that they would too. Especially female students seemed to verbalize such impressions.
Closing words
So what did I try to show you in this blogpost? My goal was to explain why it is important to approach IT education from a gender perspective. Due to social stereotypes infiltrating classrooms (as well), girls and women are gravely underrepresented in the IT sector, which has serious social, economic, and technological ramifications. IT educators have a central role in this process. By questioning entrenched gender stereotypes related to IT (and STEM in general), along with enabling diversity and cooperation within the classroom, teachers can have a beneficial impact on the gender balance in the IT world. With the introduction of my course, I aimed to give some practical guidance about how this can be done. The case study of a recent, and as a matter of fact ongoing, IT(-related) course was meant to show how the notions of cooperation in classwork, the contextualization and humanization of the IT topics, and the presentation of role models can be implemented to overcome gender stereotypes and celebrate diversity. Besides embracing the general idea of diversity, the course specifically strived to provide support and inspiration for female students, through the presentation of female role models and the discussion of equity and equality in IT, so that they persist and thrive in the IT field.
References
Adam, C. (2018). Gender studies programs to be banned in Hungary. Hungarian Free Press. Retrieved from http://hungarianfreepress.com/2018/08/10/gender-studies-programs-to-be-banned-in-hungary/ (accessed: 01/07/2021)
Dankwa, N. K. (2019). Four reasons why gender dimension matters in tech design and development. Engines of Difference, Aug 14, 2019. https://enginesofdifference.org/2019/08/14/four-reasons-why-gender-dimension-matters-in-tech-design-development/ (accessed: 01/07/2021)
Eurostat. (2019). ICT specialists in employment. https://ec.europa.eu/eurostat/statistics-explained/index.php/ICT_specialists_in_employment#ICT_specialists_by_sex (accessed: 01/05/2021)
Frehill, L. M. & McGrath Cohoon, J. (2015). Gender and Computing. In Pearson, Jr. W., Frehill, L. M. & McNeely, C. L. (Eds.) Advancing Women in Science. An International Perspective (pp. 237-264). Springer.
Hungary – Global Gender Gap Report. (2017) http://reports.weforum.org/global-gender-gap-report-2017/dataexplorer/#economy=HUN (accessed: 12/20/2020)
Huszár, Á. (2018). Problémák a (társadalmi) nem körül. Élet & Irodalom 62(34).
Mansour, N. & Wegerif, R. (2013). Science Education for Diversity: Theory and Practice. Springer.
Margolis, J. & Fisher, A. (2002). Unlocking the Clubhouse. Women in Computing. Cambridge Mass, MIT Press.
Nagy, B. (2014). Háttérben: Kísérlet egy szervezeti nemi rend feltárására. L’Harmattan.
Nosek, B.A., Smyth F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., Bar-Anan, Y., Bergh, R., Cai, H., Gonsalkorale, K., Kesebir, S., Maliszewski, N., Neto, F., Olli, E., Park, J., Schnabel, K., Shiomura, K., Tulbure, B. T., Wiers, R. W., . . . Greenwald, A. G. (2009). National differences in gender-science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 106 (26) 10593-10597; https://doi.org/10.1073/pnas.0809921106
Papp, G. & Keszi, R. (2013). A műszaki felsőoktatás a nemek tükrében – különbségek a pályaválasztás és az egyetemi tapasztalatok területén. Zárótanulmány. In Szekeres V. & Krolify Intézet (Eds.) „Ti ezt tényleg komolyan gondoltátok?” Nők és a műszaki felsőoktatás. Óbudai Egyetem, pp.214–314.
Ramirez, F. O. & Kwak, N. (2015). Women’s Enrollments in STEM in Higher Education: Cross-National Trends, 1970–2010. In Pearson, Jr. W., Frehill, L. M. & McNeely, C. L. (Eds.) Advancing Women in Science. An International Perspective (pp. 9-26). Springer.
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