Boston University’s bold experiment to reverse the longstanding gender gap in computer and data science is defying national trends, according to a recent feature by the university (Boston University). While women comprise about half the workforce in the United States, they remain woefully underrepresented in the booming fields of technology and data: barely 15-20% of professionals in data science are women, and women-led start-ups and founding teams are even scarcer.
This gender disparity is not new. Women’s share of computer science degrees in the US peaked at around 35% in the 1980s, only to tumble to about 20% by 2020. Despite high-profile calls to bolster diversity in science, technology, engineering, and mathematics (STEM), the actual progress has been alarmingly slow. Compounding this inequality, talented women miss out on intellectually stimulating, flexible, and high-paying careers, and society as a whole suffers from the absence of diverse perspectives—both in innovations and in critical decision-making.
For Thai readers, the situation will sound familiar. Despite advances in education and the growing presence of women in universities, female representation in Thailand’s computer science and technology sectors remains similarly lopsided. The digital economy is powering national strategies like Thailand 4.0, yet women are still in the minority across most IT and data-driven industries (UNESCO Regional Office Bangkok). Boston University’s approach could offer timely lessons for educators, policymakers, and aspiring students in Thailand and across Asia.
At BU’s Faculty of Computing & Data Sciences (CDS), which launched in 2021, women made up 46% of the first cohort of students—a figure that has even increased in subsequent classes, reaching 47% for the incoming class of 2028. This gender-balanced cohort stands in sharp contrast to both national and international averages, where women are typically relegated to the margins of computing classrooms and workplaces.
Institutional leaders at BU attribute this breakthrough to more than mere recruitment or quotas. One senior academic administrator at CDS frames the issue as one of untapped societal potential: “Women are half of the population, and half of our brain power… As a society, we will do far better if we get the best brains to work on the most pressing problems,” he explained. Rather than simply opening the door, CDS rebuilt the entire doorway. The faculty, designed from the ground up rather than retrofitted from traditional STEM programs, was able to prioritize broad impact and application from the very start. According to another CDS assistant professor, focusing on how data science enables work in diverse fields such as biology, business, and media, helps draw in students—especially those who may not see themselves reflected in the standard STEM narrative.
This innovative framing is supported by evidence from BU students themselves. One senior in the program described her high school experience as isolating—she often found herself the only girl in advanced programming classes, hesitant to ask questions in a male-dominated setting. Now, at BU, she finds the learning environment “refreshing and really exciting,” noting the support from a diverse student body and approachable coursework. Another student cited a persistent feeling she had to work “ten times harder” to prove her worth in male-heavy classes—an experience echoed by many Thai women who have ventured into science and tech pathways.
The core of BU’s approach is the so-called “spiral approach” to learning. Instead of weeding out students with difficult theoretical courses at the start, CDS welcomes students of all backgrounds with introductory classes that emphasize real-world datasets and collaborative problem-solving. Rather than requiring extensive math or coding experience as a prerequisite, the program equips students with these skills as needed—always in the context of intriguing, relevant questions. For instance, first-year students might analyze datasets on smoking and lung cancer to uncover correlations, then learn the statistical and programming skills needed to validate their findings. This method fosters not only competence but also curiosity, offering an accessible ramp for those who haven’t previously seen themselves represented.
The results are telling. Students from across diverse disciplines join CDS’s foundational classes just to “try it out,” creating classrooms where gender, race, and academic interests mix, resulting in richer and more nuanced discussions. The educational models upend the artificial barriers that have long filtered out women and minorities from tech. “The intro classes act as a way for anybody—regardless of experience or whether they have seen themselves represented in the field—to learn about data science and see if it is something you would like,” said one senior student and teaching assistant.
The need to address gender bias isn’t just a question of fairness—it’s fundamental to the quality and reliability of emerging technologies. Recent missteps by technology companies illustrate the dangers of lacking diversity. In 2018, Amazon abandoned a computer program developed to screen job applicants after discovering it had learned to favor résumés from men over women, essentially encoding and amplifying pre-existing workplace biases (Reuters, 2018). Just this year, a UNESCO study sounded the alarm on generative AI models, such as those underpinning platforms like ChatGPT and OpenAI: these systems often perpetuate regressive gender stereotypes, associating women with domestic roles and men with business and executive functions (UNESCO, 2024). Experts warn that as these technologies proliferate in daily life, the embedded biases will only become more entrenched and more harmful.
This opens an urgent conversation for Thai society, which is rapidly adopting AI for everything from healthcare management to financial services. Without the inclusion of women and other underrepresented groups in the design and deployment of these technologies, existing social stereotypes risk becoming algorithmically “baked in”—compounding discrimination in subtle but pervasive ways. For example, if popular generative AI applications in Thailand are not trained or audited with gender balance in mind, there is a risk that digital content and job matching tools could reproduce outdated stereotypes that still shape Thai society.
Current research also cites the “pipeline problem”: girls are less likely than boys to be enrolled in foundational science and technology courses during their school years, and the gap only widens with each academic step (National Girls Collaborative Project). Without adequate exposure and encouragement, few women venture into college-level computer science, and even fewer progress to industry leadership. BU’s solution—contextual, open-access introductory courses—offers a replicable template. Senior faculty at BU noted the traditional “weed-out” curriculum in STEM programs discourages those who might not see themselves as the stereotypical coder or engineer, but still have strong potential.
For Thailand, where top universities and innovation hubs aim to produce world-class software engineers, data analysts, and tech entrepreneurs, integrating more inclusive pathways could transform the landscape. Programs modeled after BU’s spiral approach could enable a more diverse generation of digital leaders, closing the gender gap and enhancing the overall quality of innovation.
Thai culture offers unique perspectives in this debate. While there is a rich tradition of women excelling in various professions—medicine, academia, and business—stereotypes around gendered skills still influence career choices. Many young Thai women are encouraged to pursue “appropriate” jobs perceived as less technical or competitive, often from a desire to maintain social harmony or meet family expectations. These cultural dynamics can be self-reinforcing, echoed in curricula, media representations, and workplace cultures. As in the US, this has led to a gendered division of roles, not just at work but in the design of digital futures.
By contrast, countries that have prioritized gender equity in STEM fields—such as Finland, Sweden, and certain East Asian economies—now reap benefits in innovation and employment rates. The results from BU’s experiment back up these broader trends, showing that targeted outreach, flexible teaching models, and a focus on real-world impact can make computer and data science genuinely attractive and accessible for a wide spectrum of students.
Looking to the future, CDS is not resting on early successes. University leaders acknowledge ongoing challenges, especially in supporting first-generation college students and scaling these models for wider impact. But their progress demonstrates an important principle: with determined intervention, the gender gap in computer and data science is not fixed, but can be radically narrowed.
For Thai educators, the lesson is clear: cultivate environments where students of all genders feel welcome to explore and experiment. Schools and universities should rethink prerequisite-heavy curriculums that tend to favor those with existing confidence or networks—often young men—and instead offer supportive, curiosity-driven entry points. Industry partners can help by promoting women’s visible participation in high-profile tech projects and innovation competitions. Government agencies should ensure gender balance is a central part of digital literacy campaigns and policies under Thailand 4.0 and related national strategies.
Thai families, too, play a decisive role. Parents and community leaders should encourage girls’ interests in problem-solving, numbers, and technology from an early age and challenge internalized expectations around “male” and “female” professions. Anecdotal evidence from local coding camps, robotics competitions, and university tech festivals suggests that with the right encouragement, Thai girls can and do excel—often surpassing boys in design thinking, software development, and analytics.
Practical actions for Thai readers interested in promoting gender balance in tech and data science could include joining local mentorship schemes, supporting AI literacy clubs, or participating in international programs such as Girls Who Code (girlswhocode.com). Schools can partner with universities to offer age-appropriate, hands-on data science workshops. Meanwhile, parents and teachers can help dispel common myths—for example, the idea that “men are naturally better at math”—by highlighting success stories and providing consistent encouragement.
As BU’s experience affirms, broadening participation is not only possible—it’s essential. When more women, and more diverse groups in general, shape the technologies underpinning our modern economies, societies grow stronger, more innovative, and better equipped to tackle pressing challenges, from economic transformation to ensuring ethical AI. The journey from the margins of the classroom to the center of the data revolution is not one that any nation—Thailand included—can afford to leave unfinished.
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