In the spring of 2024, the Computing Research Association (CRA) asked a simple but powerful question: What do industry professionals think about the way we teach computer science today? as part of a “Practitioner to Professor (P2P)‘ survey that the CRA-Education / CRA-Industry working group is doing.
The response was overwhelming. More than 1,000 experienced computing practitioners—most with over two decades of experience—shared their honest thoughts on how well today’s CS graduates are being prepared for the real world.
These weren’t just any professionals. Over three-quarters work in software development. Many manage technical teams. Most hold degrees in computer science, with Bachelor’s and Master’s being the most common. Half work for large companies, and a majority are employed by organizations at the heart of computing innovation.
So, what did they say?
The Call for More—and Better—Coursework
One of the loudest messages was clear: students need more coursework in core computer science subjects. Respondents recommended about four additional CS courses beyond what’s typical today. Algorithms, computer architecture, and theoretical foundations topped the list.
But it wasn’t just CS classes that practitioners wanted more of. They also suggested expanding foundational courses—especially in math, writing, and systems thinking. It turns out that the ability to write clearly, think statistically, and understand how complex systems interact is as critical as knowing how to code.
It’s Not Just About Programming
When it came to programming languages, the responses painted a nuanced picture. Practitioners agreed: learning to code isn’t the end goal—learning to think like a problem-solver is.
They valued depth over breadth. Knowing one language well was seen as more important than dabbling in many. But they also stressed the importance of being adaptable—able to pick up new languages independently and comfortable working with different paradigms.
Familiarity with object-oriented programming? Definitely a plus. But what mattered most was a student’s ability to approach problems critically, apply logic, and build solutions—regardless of the language.
The Soft Skills Shortfall
One of the most striking critiques was aimed not at technical training, but at the lack of soft skills being taught in undergraduate programs.
Soft skills, they argued, can be taught—but many universities simply aren’t doing it well. Oral communication courses were highlighted as a critical need. And interestingly, several respondents felt that liberal arts programs were doing a better job than engineering-focused ones in nurturing communication, collaboration, and leadership.
Asked to identify the most important communication skills, respondents pointed to the ability to speak confidently in small technical groups, write solid technical documentation, and explain ideas clearly to leaders and clients—both technical and non-technical.
Math Is Still a Must
Despite the rise of high-level frameworks and automation, the industry’s love affair with math is far from over. In fact, 65% of respondents said they enjoyed or pursued more math than their degree required.
Why? Because math is the backbone of emerging fields like AI, machine learning, and data science. It sharpens analytical thinking, cultivates discipline, and builds a foundation for lifelong adaptability.
The most important math subjects? Statistics topped the list, followed by linear algebra, discrete math, calculus, and logic.
Foundations First
The survey didn’t just surface high-level trends—it got specific.
In algorithms, the emphasis was on conceptual thinking, not just implementation. Students should deeply understand how algorithms work, why they matter, and how to analyze them.
In computer architecture, digital logic and memory hierarchy were considered essential. These are the building blocks that enable students to understand modern computing systems, from the ground up.
And when it came to databases? Practitioners wanted a balance: students should learn both the theory (like relational algebra and normalization) and the practice (like SQL and indexing). Real-world readiness depends on both.
Toward a Better Future for CS Education
What makes this survey so impactful is its timing and intent. As technology continues to reshape every industry, there’s a growing urgency to close the gap between academia and the workforce. The P2P Survey is part of a broader movement to do just that.
Endorsed by leading organizations—ABET, ACM, CSAB, and IEEE-CS—this initiative creates a powerful feedback loop between universities and the industry they serve.
So, what’s next? A full report is expected later this year. But the message is already loud and clear: today’s students need a curriculum that not only teaches them how to code, but prepares them to lead, adapt, and thrive in a complex, evolving world.
