While this is a perfectly reasonable explanation, it is not the correct one. Instead, it highlights that our learners often have no idea how information technology (IT) actually works, what it does, or why something is happening. This makes it seem magical at best, and sentient at worst. This article will explore some common alternate conceptions that learners hold about computing systems, and how you can use the input–process–output (IPO) model to support learners in making sense of the IT around them.
The IPO model
All computers work with inputs, processes, and outputs (see Figure 1 above). All computers accept inputs, which are entered into or received by a computer. They can be generated in many ways, including by a user pressing a key on a keyboard, or a computer receiving a signal from another device. The process then determines what the computer does with that input. It can process the same input in different ways, depending on the program running. The output is how the computer finally presents the results of the process. It can return the results to the user in many ways, such as displaying text on a screen, creating printed materials, or playing a sound from a speaker.
In today’s connected world, it’s easy to overlook the processes taking place in devices that learners don’t immediately recognise as computer systems, such as pedestrian crossings or washing machines. This can lead to learners developing alternate conceptions about what is happening, making it harder for them to apply their understanding of programming or input and output devices as they gain more knowledge. We can’t build knowledge on insecure foundations, so the sooner we identify these misconceptions, the better.
Does a lamp have a computer inside it?
As we start to pay attention to the world around us, we begin to recognise different groups of objects that have similar properties, such as natural or manufactured, mechanical or electrical. However, as these objects become more complex, it can be hard to tell which groups they belong to. This ambiguity can make learners overgeneralise their understanding of how something works. Taking time to break this down with the IPO model allows learners to reflect on their assumptions.
Let’s imagine a desk lamp. Does it have an input? Yes — I press a button to trigger what I want to happen. Does it have an output? Yes — the light turns on. Now comes the important part: is there a process? No — there is no program receiving data that the button has been pressed. Instead, the switch on the lamp creates a circuit for the electricity to flow through, allowing the bulb to light. Therefore, most lights do not have computers inside of them.
Computers are really clever
The feeling we have that computers are magical, before we start to understand how they work, is often reinforced when the device can do something we do not know how to do ourselves. One of the most prevalent and early alternate conceptions that learners hold about computers is that they are ‘really clever’.
To address this, let’s consider looking for information on a website to answer a question. What is the input? Using the keyboard to type in keywords that tell the computer what I’d like to know. The search engine’s computer then processes this data by running a program to find relevant information. What is the output? A website showing a list of other websites on my screen. Do I have the answer to my question? Most often, no. I now have to go to each web page and decide if it has the answers that I need. Taking learners through each step in the model highlights how much of the process is reliant on human interaction to work, and how computers are only as powerful as the humans that use and program them.
IPO takes place on one device
Without understanding how a system works, it can be very easy to make assumptions. One afternoon, the internet went down at my (Josh’s) school. My class, however, didn’t believe me! Why? Because the interactive whiteboard was still working. These assumptions become more important when we begin considering personal data, what’s stored locally on the device you are using, and what’s uploaded to the internet. I’ve found that this is particularly challenging with certain apps on tablets that may also back up online.
To unpick this, it’s important to start considering larger and more complex systems, such as ATMs. The input (data from the keypad) and the output (the information displayed on the screen) are clear. However, much of the process is not happening on the computer within the ATM — it’s using the internet. The computer in the ATM sends the input data through the internet to the server at the cardholder’s bank, to check it’s correct. This is the process. Then the server sends back the output data to show the outcome on the screen. The first data processed will check whether the PIN number is accurate, but each instruction after that will begin the process again. Even if learners can’t accurately recognise what’s happening on a device and what’s happening online, having these IPO conversations can support them in thinking about what’s happening before they create content and potentially share it online.
From programming, to collecting data from sensors, to recognising technology around us, the IPO model applies to almost all aspects of computing. Starting activities with the question ‘How does this work?’ can evolve into learners recognising the many and varied IPO systems in the world around them. You can then get creative, letting learners invent imaginary systems to put the IPO model into practice (see helloworld.cc/tccsystems1). Initially, the processes will be assumptions, but as learners’ experiences grow, these approaches become a chance for them to imagine the computer systems that will change the world.
Further resources
The Raspberry Pi Foundation’s free online courses:
Free lessons and activities in the Teach Computing Curriculum:
IPO Model overview document:
Authors
Sway is a senior learning manager at the Raspberry Pi Foundation. She leads a team developing computing resources for primary teachers. Josh and Sway are both former primary teachers.
Josh is a programme coordinator at the Raspberry Pi Foundation, working across programmes such as the Teach Computing Curriculum and Hello World.
