What are the factors associated with girls choosing to study computing at GCSE?

Girls continue to be heavily underrepresented in computer science. At GCSE, 20% of entries are female students (Kemp et al 2018). Frank Kelly on 23 August 2018, Chair of the Royal Society Advisory Committee stated that, "Girls making up 19.8% of Computing GCSE entries simply isn’t good enough”. He states that improving the gender balance should remain a priority as it will help increase the number of young people with skills in computing which, according to Sellen et al (2017) will help the individual and national economic progress.

Why is this important?

The gender imbalance experienced in schools seems to also reflect the world of work where 17% of Google’s, 15% of Facebook’s, and 10% of Twitter’s engineers are women (Zynczak 2016). More recently it has been estimated that technology will create approximately 97 million new jobs in 15 industries and 26 economies (Zopf,2020).

This paper considers the factors associated with girls choosing computing at GCSE and suggests what can be done in the classroom to encourage more girls to choose it as an option.

According to the Roehampton Report June 2018 - compared to 2014, when the computing curriculum reform was introduced, there are approximately 30,000 fewer females taking any computing qualification at GCSE. 

What does GCSE Computing entail?

The UK 2014 reformed computing curriculum is split into three key areas, Digital Literacy, Computer Science, and Information Technology (Kemp, 2014). Each of these strands are equally important. Programming forms a part of the computer science element however programming is disproportionately used to describe the curriculum and in doing so possibly creates a misconception of what is entailed in the subject (Kemp et al 2018). In a study of students who were not familiar with the computing curriculum when asked, what the subject computing is about a common response was, ‘it was something about programming and that was enough to stay away from it’ (Spieler et al 2018).

Reflecting on what is taught in computing at GCSE, it is important to understand that prior to the UK reform of 2014 ICT GCSE qualification and ECDL (European Computing Drivers Licence) were both taught separately and were popular choices for females with 38% and 45.3% representation, respectively. Elements of these courses were included into the reformed computing GCSE qualification however not explicitly communicated to prospective students. Therefore, the lack of effective communication and understanding of the GCSE computing elements could affect the number of girls taking it as an option. 

Learning theories

There are two prominent and relevant learning theories in education that may have impact on the presenting problem, these are:

1. Expectancy-Value Theory (Eccles 1983) which posits that a student’s achievement and related choices are mostly determined by two factors, expectancies for success in the task, and subjective task values (usefulness and importance). 
2. Social Cognitive Theory (SCT) advanced by Bandura (1986) which directly attributes learning from observing others within social interactions, experiences and the media. The theory states that when a model is observed performing a behaviour and its consequences the observer remembers the sequence of events and uses it to guide their subsequent behaviour. 

In additional to the learning theories mentioned above, extensive research by Eccles et al (1984) has identified developmental factors such as gender differences, interests, sense-of-belonging, self-efficacy (Bandura 1983) and engagement as being present at the life-stage of teenage girls aged 13 – 14 years, which forms part of the Stage-Environment Fit Theory (Eccles et al 1993). Along with other factors such as classroom experiences, family (Eccles 2007), stereotypes, and school practicalities. All these factors and theories could help the understanding of teenage girls’ motivation and attitude towards choosing computing at GCSE. 

Identified factors in research.

Researchers such as Spieler et al (2018) looked at the gender differences in motivations for choosing computing as a subject. Even though their research has limitations, it does help the understanding of generalised influencers and effects of social, practical, and cultural attributes on the motivation of young people in selecting computing as a subject in secondary school.  

This illustration indicates the SCT (bandura 1986) approach to learning that female students are more likely to choose computing when they already know somebody who is interested or has worked in the computing industry. It also shows that having a positive attitude towards computing in the home through activities such as ‘tinkering’, reading books about the topic and learning through friends or relatives will lead to a positive attitude towards choosing to study computing. In education ‘tinkering’ refers to trying things in technology (including coding) without the fear of failure, in a playful way, e.g., Resnick’s Scratch (Slany 2014; Harris et al 2016) and before that Papert’s Logo programming language. Often also referred to as low stakes with high challenge.

In an alternative proprietary article by Accenture (2016) they too identify factors, which correlates with the Stage-Environment Fit theory (Eccles et al 1993), looking what effects girls’ interest in computing through the education timeline.

What are the factors that influence girl’s choices in studying computing at GCSE?

Below are nine key factors that seems to be the predominate influencers.

1: Gender Stereotypes

Gender stereotypes could come from many different aspects of a girl’s developmental life stage and the work of Eccles (2015) identifies that parents’ beliefs and practices has an influence on the bias girls exhibit against computing. Teachers were also identified as having an unconscious male bias while teaching computing in classrooms, exhibited through language and masculine examples (Kemp et al 2018). The role of stereotypes in producing and sustaining segregation amongst the genders has perpetuated beliefs that females are inferior to their male counterpart in fields such as technology (Eccles 2015) despite that girls outperform boys at GCSE computing (Kemp et al 2018). Stereotyping plays a significant role in creating negative attitudes, dampens self-efficacy and creates a sense of not belonging (Eccles 2015). Spieler et al (2018), uses the image of a helpless, uninterested, and unhappy ‘girl in computing’ which is rooted in the notion that women are technologically inept and ill-suited for computing. This stereotypical perception helps to perpetuate the reality as a self-fulfilling prophecy (Bandura 1986).

2: Exposure to Technology

Research has found that contact with technology at an early age could perhaps improve the interest levels and attitude of women towards technology before stereotyping takes hold (Carter 2006; Sadler et al 2012). However, a more recent study has identified that female students do not feel motivated to learn about technology outside of school nor are they compelled to engage with friends or family to pursue computing interests (Unfried et al 2015; Master et al 2016). These studies could be contradictory however what is not clear in either study is what types of ‘contact with technology’ is being referenced. Spieler et al (2018) says exposure to technology should be done from an early stage of development as shown in the Accenture illustration where girls’ interest in computing peaks between the ages of 11 and 13 then falls at the next teenage girls’ life-stage of 13 – 14 years (Eccles et al 1993). 

3: Interests

Interest is an important motivational variable because it can affect learning and performance outcomes and, by extension, self-confidence (Denner 2011). Weibert et al (2012) identified that a combination of computing with another field of interest, for example business or medicine, was the number one positive influencer for girls selecting computing as a subject. It would also seem that teenage girls will engage with technology if it makes the world a better place through creating programs or products (Goode 2006). Girls take a utility approach to interest in computing through their Expectancy-Value model (Eccles 1983) of fulfilling other goals. 

4: Teaching Pedagogy

If girls do not find interest to pursue technology outside of school beyond its utility value (Weibert et al 2012), then their only exposure to computing (for exploration) is in structured classes. It is in this setting that as a teacher I have the most influence to motivate girls to choose computing at GCSE. It is in the classroom that role-models and positive computing experiences can be fostered. Webb et al (2012) in their study of Scalable Game Design (SGD) concluded that the girls were less likely to be motivated by direct instruction and preferred guided discovery scaffolding when involved in programming. I have identified a further four specific areas which could further influence the pedagogy process, these are ‘praise’, ‘fun’, ‘practical’ and ‘interaction’ which are expanded upon below:

Praise: A study by Schwartz (2013) identifies the importance to appreciate sufficiently students’ achievements, but more importantly, to formulate the feedback in such a way that it does not harbour harmful tensions that would create fear of failure. It is not helpful to praise girls for achievements that are not addressed also in boys. Praise for ‘normal’ performance can damage self-confidence. While boys are often praised for their talents, girls are more often praised for being hard-working. Overall, it is important to praise the work of female students at least in the same way as that of the male students and to provide recognition of their work done. 

Fun: It is commonplace in a computing classroom to have a traditional set-up where the teacher mainly relies on Microsoft PowerPoint slides and sections of code to follow, rarely with social context (Spieler et al 2018). This setting is not only less challenging for all students, but also boring, and it can even prevent students from truly understanding a programming language and the concept of coding itself. This approach does not show the multiple ways that students can be involved in problem-solving, nor does it encourage tinkering, nor any form of group work, which is a known motivator for girls (Frieze and Quesberry 2015), nor class discussions (Spieler et al 2018). Which ultimately leads to negative experiences for all genders in the classroom and are a key detractor for girls choosing to study computing. 

Practical: Weilbert et al (2017) implemented a practical and integrative computing curriculum which helped to point out how the subject directly links with professional computing jobs which in turn positively influenced girls’ interest in computing as an area of study. This change of curriculum was the result of a study by Weilbert et al (2012) which showed that low classroom engagement by girls was experienced when basic input and output processes were explained without real-world context (Carter 2006). Improved engagement was experienced during problem-solving or creative skills (Carter 2006) classes.

Interaction: Alvarado et al (2017) research using a large-scale survey of university students experiences in computing classes revealed that female students refused to ask questions in class nor publicly interacted with the instructor (and if done felt less comfortable doing so), and as a result, they were left with lower confidence in their abilities and with doubts about the learning content. Girls seem to want more one-to-one time with teachers and tutors to confirm their understanding (Goode 2006).

5: School Practicalities

According to an article by Peter Henshaw, 20 June 2018 in www.sec-ed.co.uk based on the Roehampton Report (2018) it identified that a cause for girls not taking computing is that some schools are not offering it at GCSE in the first place, 47.5% of mixed gender schools do not offer computing at GCSE and 55% of girls-only school who do not offer GCSE computing.

6: Role-models, mentors, and family

Role-models: In a recent ISAC global survey report (Wisniewski 2017) the absence of relatable female role-models is one of the top five reasons why women are underrepresented in technology. While their male counterparts are drawn to role-models in the form of celebrity status given to many noted male technology entrepreneurs, such as Bill Gates and Mark Zucherberg etc. young women are more likely to look for role-models closer to home and more relatable. In this instance often the role-model becomes the mentor (Mendick et al 2016).

Mentors: A study conducted by The Association for Women in Science/AWIS (2017) showed that female students who had mentoring relationships, e.g., with different kinds of people, including friends, parents, siblings, cousins, teachers, and neighbours, were influenced positively. For example, they were more interested in computing (e.g., incorporating computing into their identities), had more positive beliefs about people working in computer science (e.g., the associated attributes were ‘creative’, ‘patient’, ‘intelligent’, or ‘hard-working’), and finally, felt more engaged in coding opportunities (e.g., encountering more programming languages). 

Family: According to Denner (2011) family members, especially fathers have great influence over a teenage girl’s decision to study computing. These family expectations have long-term effects and form part of the Expectancy-Value Motivation Learning model expressed by Eccles (2006). Parents who hold less traditional attitudes about gender roles and careers when their daughters are 12 – 14 years have adult daughters that are more likely to pursue non-traditional careers like computing (Chhin et al 2008).

7: Sense-of-Belonging and identity

As outlined in the paper by Wong (2016) the relationship between doing computing and being a computing person is complex amongst young people. In the study, many stereotypes were described by female participants which were not congruent with their own self-image. The overwhelming image portrayed as being a computing person was someone liken to a white, middle-class, glasses-wearing, physically weak and socially awkward individual (Mercier et al 2006). The image was also associated with the term geek (Ward 2014) who reminds us that geeks are also typified as being “shy, or unattractive social outcasts”. All of which would not necessarily be appealing to girls considering their subject choices at 14 years (Wong 2016). Research by Archer et al 2012 explains the tensions between geekiness and normative femininities. For example, writing about science (however equally relevant to computing), Louise Archer et al (2012, p.181) argue that the subject’s associations with geekiness mean that it “appears by default as an imagined space that is incompatible with girls’ performances of popular/desirable hetero-femininity”. 

8: Self-efficacy

The Kemp et al (2018) in the Roehampton Report identified that computing is hard at GCSE, students typically get half a grade lower than in their other subjects. If young women are used to failing or think they will fail in a specific course they will instead choose subjects that they know they are comparatively good reconfirming the Expectancy-Value Motivation learning theory by Eccles et al (2006). The notion that the subject is hard combined with the stereotype that girls are inept to cope with the difficulty of the content (Spieler et al 2018) may contribute to the presenting problem.

Based on my research self-efficacy is heavily intertwined with many of other influencing factors (stereotypes, sense-of-belong, identity, classroom environments and interest) of the presenting problem. The relationship can be briefly explained as following, since computing is stereotypically associated with the masculine role female teenagers are less likely to have a sense-of-belonging. Thus, they are less interested and engaged in these classes (Master et al 2016) and consequently, they feel less self-efficacy which then becomes a self-perpetuating cycle. 

Self-efficacy can be improved through mastery experience, social modelling, improved physical and emotional states and verbal persuasion (Bandura 1986). It is this approach which is most practical in the classroom.

9: Social and Cultural implications

According to Professor Rippon in Clarke (2015) the environment that we grow up in affects how our brain develops and our brain has an incredible ability to adapt, learn, accommodate, and rewire (known as neuroplasticity). To fit into our community we adopt the standards, beliefs, and prejudices of those we want to identify with – such as the role of our associated genders. Like self-efficacy, social and cultural expectations are intertwined with other factors such as gender and stereotypes. Culture seems to play a role as indicated in the Roehampton Report (2018), Asian students were more likely to choose computing than Caucasian and black students in GCSE, more research is required in the relationship between girls, ethnicity, and computing choices at GCSE.

From a social implication, peer acceptance is central to a girl’s development in their teenage years (Dasgupta and Stout 2014). To be socially connected and respected is a strong initial motivator; “it can create a sense-of-belonging that can reinforce a student’s self-efficacy and connections to community that support student perceptions of their ability within the field” (Veilleux et al 2013, p. 64). 

Suggested pedagogy approach in the classroom and the wider school environment.

Based on this research a seven-pronged pedagogy approach can be taken to encouraging more girls to take computing at GCSE:

1. Be careful with modelling language, this is important across all school staff, who should be aware of their language around computing, it is often heard by students in different subjects their teacher saying, “I cannot do IT,” or “Computers and I do not get along.” These perpetuate negative beliefs within girls, who within the Social Cognitive Theory Bandura (1986) are sensitive to their observations which then communicates that computing is hard. 
2. Do not over emphasise the gender differences in the learning environment such as classroom displays, examples, and language used thus not propagating gender binary stereotypes. 
3. Encourage extra curriculum involvement is encouraged within computing by way of clubs and competitions, do not make them “girls only” which can perpetuate stereotypes (Hercy et al 2009) instead clubs need to be inclusive and all genders need to see the value everyone can contribute. The key is that they are fun.
4. Engage in small group work which has a sense of purpose, achievement, and enjoyment; and use praise fairly and based on individual achievement. Utilising small group work as a form of assessment-for-learning rather than large group question and answer sessions. When teaching programming elements, ensure that guided discovery scaffolding is implemented. 
5. Sign posting the specific strands of the computing curriculum being taught during each lesson to ensure students understand how the learning fits into the wider computing curriculum and life in general. 
6. Take a more balanced approach regarding discussing curriculum with prospective students and their parents during GCSE options discussions, remembering that programming is only a small part of a bigger curriculum. Ensuring that the enabling elements of computing is communicated, and the positive impact computing can have on real-world problems.
7. Work with other facilities to demonstrate how computing is integral to all areas of study. An example is to collaborate with faculty heads and arrange for cross-faculty class visits to briefly share how technology has changed their areas of speciality.

Even though this research is specifically focused on girls choosing computing in GCSE, these seven pedagogy approaches will help all student access and engage wholeheartedly in computing regardless of their associated gender. 

Published: Cynthia Nolan

Based on original paper date: May 2019

Summary dated: February 2021

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