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LONDON — When you think of a typical computer science student, what image comes to mind? For many, it might be the stereotypical “tech geek” — highly intelligent, socially awkward, and most likely male. However, a new study suggests that this narrow and unhelpful view may be outdated and potentially harmful to the future of computer science education.
Researchers from the University of Reading and King’s College London have uncovered a surprisingly diverse range of characteristics that young people associate with the “ideal” computer science student. Their findings challenge long-held stereotypes and offer hope for creating a more inclusive environment in computer science classrooms.
The study, which surveyed over 3,000 students between the ages of 11 and 16 in the United Kingdom, revealed that while being “smart and clever” is still the most commonly cited trait, it’s far from the only quality young people value in computer science. In fact, the researchers identified eight distinct clusters of characteristics that students used to describe the ideal computer science student.
Beyond pure intelligence, students emphasized the importance of being knowledgeable and interested in the subject, determined and hardworking, kind and helpful, creative, independent, confident, and collaborative. This multifaceted view suggests that young people’s perceptions of who can excel in computer science are broader and more nuanced than previously thought.
Perhaps most interestingly, the study found significant differences in how various groups of students described the ideal computer science student. For instance, girls were more likely than boys to emphasize traits like determination, hard work, and independence. Students from lower socioeconomic backgrounds were less likely to mention creativity or collaboration. Additionally, those who aspired to become computer scientists themselves had distinct views compared to their peers.
These findings may go a long way toward addressing the persistent gender gap in computer science education and careers. In the United Kingdom, for example, only about 20% of students taking computer science qualifications at age 16 are girls. By understanding how different groups of students perceive the field, educators and policymakers can develop more targeted strategies to attract and retain a diverse range of students in computer science.
“This is good news for widening participation in computer science education. Stereotypes exist for a reason but can be a powerful deterrent to participation by some underrepresented groups,” says lead author Professor Billy Wong, of the University of Reading, in a statement. “Our findings show that young people recognize the importance of being knowledgeable and hardworking in computer science, and they also value softer traits such as creativity and collaboration. This challenges the popular stereotype of computer scientists as simply being ‘clever’ but socially challenged.”
This research comes at a critical time, as the demand for workers with digital skills continues to outpace supply in many countries. By broadening our understanding of what makes a successful computer science student, we may be able to tap into a larger and more diverse talent pool to meet this growing need.
The study’s findings also highlight the potential power of role models and representation in shaping students’ perceptions. As more diverse voices and stories are highlighted in computer science education and the tech industry at large, it may further expand young people’s ideas of who belongs in the field.
Paper Summary
Methodology
The researchers conducted a large-scale survey of 3,235 students aged 11-16 in 15 secondary schools across England. As part of a longer questionnaire, students were asked to list three characteristics of an “ideal computing student.” The researchers collected 9,442 keyword responses, which were then analyzed and grouped into clusters of similar traits. The team used statistical analysis to examine how these characteristics varied based on students’ demographic information and other survey responses, such as their aspirations to become computer scientists.
Key Results
The study identified eight main clusters of characteristics that students used to describe the ideal computer science student:
- Smart & Clever (28.5% of responses)
- Knowledgeable & Interested (15.4%)
- Determined & Hardworking (15.0%)
- Kind & Helpful (10.1%)
- Creative (4.3%)
- Independent (4.3%)
- Confident (2.7%)
- Collaborative (2.2%)
The researchers found significant differences in how various groups described the ideal student. For example, girls were more likely to mention traits like determination and independence, while students from lower socioeconomic backgrounds were less likely to mention creativity or collaboration. Students who aspired to become computer scientists were more likely to emphasize traits like creativity and collaboration.
Study Limitations
The study focused on a specific group of schools in the U.K. that had higher-than-average participation in computer science, particularly among girls. This means the results may not be representative of all schools or students. The research also relied on open-ended survey responses, which can be subject to interpretation and may not capture the full complexity of students’ views.
Additionally, the study provides a snapshot of perceptions at one point in time and doesn’t track how these views might change over time or in response to interventions.
Discussion & Takeaways
The study’s findings suggest that young people have a more diverse and nuanced view of who can excel in computer science than previously thought. This broader perspective could be leveraged to create more inclusive educational environments and challenge persistent stereotypes in the field.
The research highlights the importance of considering how different groups of students perceive computer science and tailoring approaches to encourage wider participation. By promoting a range of desirable traits beyond just intelligence, educators may be able to attract and retain a more diverse group of students in computer science education.
Funding & Disclosures
The research was funded by the Nuffield Foundation. The authors declared no conflicts of interest.
