Computing Perceptions of Street-Connected Youth in Nigeria

In the modern world, knowing how to use a computer, navigate the internet, write code, or understand artificial intelligence is becoming as essential as reading or writing. These skills are no longer just for specialists; they are the tools people use to find jobs, manage their money, and connect with others. For many young people, learning these skills happens in schools, where teachers explain how the technology works from the inside out. But for a specific group of young people living on the streets of cities like Lagos, Nigeria, the path to learning is different. They often miss out on formal schooling due to poverty and instability. This raises a critical question for educators and researchers: if these young people are not in a classroom, how do they understand the digital tools they use every day? Do they see a computer as a machine they can control, or just a box that gives them money? Do they see the internet as a network of information, or simply a way to survive? Understanding their perspective is vital because if we want to help them learn, we must first understand what they already believe.

A team of researchers set out to answer these questions by listening to ten young men living on the streets of Lagos. These young people, aged between thirteen and twenty, had been living outside their homes for periods ranging from less than a year to over a decade. Most had finished secondary school, but their lives had been disrupted by poverty and family issues. The researchers did not ask them to take a test or fill out a survey. Instead, they invited the young men to draw pictures of four specific things: a computer, the internet, artificial intelligence, and programming. Afterward, the researchers sat down with each young man to ask them to explain their drawings and talk about what those things meant to them in their daily lives. This approach allowed the researchers to see not just what the young people knew, but how they thought about these concepts based on their own experiences.

The study revealed that these young people had a very specific, yet fragmented, way of understanding technology. When asked to draw a computer, most of them sketched a desktop setup with a monitor, keyboard, and a large tower. However, when they explained their drawings, their understanding of what the parts actually did was often incorrect. They knew the keyboard was for typing and the screen showed the words, but they did not understand the internal logic of the machine. One young man described the central processing unit, the brain of the computer, as a printing device. Another saw the mouse as having the same function as the keyboard. Crucially, almost none of them recognized their own smartphones as computers, even though they used them every day to make money or talk to friends. To them, a "computer" was a specific object they had seen in a shop, not the device in their pocket. This showed that they could recognize the tools but did not grasp the principles behind them.

The confusion extended to the internet. When drawing this concept, the young men grouped together a wide variety of devices that they saw connecting things. They drew satellite dishes, cash machines, and even megaphones, all under the label of "internet." Their logic was consistent but broad: anything that seemed to connect one thing to another was part of the internet. One young man explained that he used a specific internet service to photograph his construction work and share it with clients, a sophisticated use of the technology for business. Yet, in his drawing, he still grouped unrelated devices together. This highlighted a gap between their ability to use technology effectively and their understanding of what the technology actually was. They knew how to make the internet work for them, but they did not know what it was.

Artificial intelligence, or the idea of machines that can think or act like humans, was the concept they understood best, though with some caveats. Their drawings were filled with specific examples they had seen, such as automated traffic lights, voice assistants, and tools that generate images. They understood that these systems could do tasks faster than people. However, their definition was also quite broad. Some described power tools that replaced manual labor or machines that printed cloth as examples of artificial intelligence. They were applying the same logic—that machines doing human work equals intelligence—to things that were simply automated. One young man, however, showed a deeper understanding. He correctly identified that artificial intelligence involved computers performing tasks humans used to do, but he also realized that his own lack of knowledge meant he might lose out on future jobs. This was the only instance where a participant combined a clear concept with a realistic self-assessment.

Perhaps the most surprising finding was how the young men viewed programming. For most, the word meant nothing to do with writing code or software. When asked to draw it, they drew machines that worked on their own, like automatic doors or cash machines. They saw programming as the magic that made a machine run without a human pushing buttons. They did not see it as a human activity of writing instructions. In fact, several participants defined the word "programming" as a social event, like a wedding or a church service, because that was the only time they had heard the word used. One young man who came closest to understanding programming as a logical process still felt it was something only for "intellectuals," not for someone like him. This revealed a deep barrier: they could imagine the result of programming, but they could not imagine themselves doing it.

The study also uncovered a powerful and sometimes troubling motivation behind their interest in technology. For these young men, computing was not about learning or creativity; it was about survival. They valued digital technologies primarily for their income-generating potential, which included fraudulent practices, without any ethical framing or moral concern. In their drawings and conversations, they focused on betting shops, printing presses, and online sales. But this economic focus came with a lack of ethical boundaries. When asked about their future plans, several young men spoke about using computers for spamming, hacking, or creating fake documents with the same casual tone they used for legitimate design work. They did not see fraud as wrong; they saw it as just another skill, like graphic design, that could help them survive. The researchers found that this was not because the young men lacked morals in general, but because their environment had not taught them to apply ethics to the digital world. They had learned from watching others, and in their streets, the line between making a living and breaking the law was often blurred.

The driving force behind all these perceptions was exposure. None of the young men had received formal training in computing. Instead, exposure was the primary mechanism through which their computing understanding and aspirations were formed. They had learned by watching others. They saw a neighbor use a computer to design flyers, or a friend use a phone to get clients, and they imagined that they could do the same. This observation sparked a strong desire to learn. They wanted to build websites, create software, and design graphics. However, this desire was built on a shaky foundation. They had the dream but not the map. They could imagine the destination, but they had no idea how to get there. The researchers noted that while their ambition was real and powerful, it was disconnected from any understanding of the steps required to achieve it. They were ready to learn, but they needed a guide to bridge the gap between what they wanted to do and what they actually knew how to do.

The study concludes that these young people are not empty vessels waiting to be filled with knowledge. They are active, engaged users of technology who have developed their own ways of making sense of the digital world. They are not excluded because they lack interest; they are excluded because the standard way of teaching computing does not connect with their reality. To help them, educators cannot simply start from scratch. They must start with what the young men already know: that technology can make money, that it can be used to connect with people, and that it can be a tool for survival. The challenge is to take these existing interests and guide them toward a deeper understanding of how the technology works, while also teaching them the ethical responsibilities that come with using it. If the field of computing education wants to include everyone, it must recognize that for some, the journey begins not in a classroom, but on the street, with a dream and a smartphone.