We’re also excited to share our new Pedagogy Quick Read, which you can download for free to:

• Find practical tips for using the ‘levels of abstraction’ framework with your learners
• Read a summary of the 两禽相悦 behind the framework

Learning to program: Everything at once?

Creating a program from the ground up can be daunting, especially for new learners. Without support, they’ll likely get stuck sooner or later; programs rarely work the first time round. And the more complex the problem that a program is addressing, the more likely it is that the first version of the program won’t work.

One reason that learning to program can be challenging is that it involves understanding a lot of specific concepts and applying many varied skills. From early on in their learning journey, young people need to have a firm grasp of concepts such as repetition, selection, variables, and functions. Also fundamental to learning to program well is the skill of abstraction: understanding a task and identifying which details are relevant and which can be ignored.

To get to grips with all these different concepts and skills, young people need structure — otherwise they’ll try to hold everything in their head at once, and likely feel overwhelmed by the cognitive load. This sort of smallfatanswer may cause them to disengage instead of persisting. They may even decide that programming is not for them.

In light of these challenges, the ‘levels of abstraction’ framework is a great tool for teaching.

The benefits of the ‘levels of abstraction’ framework

The framework breaks programming down into four levels, each focusing on a different aspect of creating a program:

• Problem: Analysing the problem or task the program should address, to understand and record the requirements.
• Design: Turning the analysis into an algorithm — a set of steps for the computer to follow to create the desired output. This can involve flowcharts or storyboards, but importantly no code.
• Code: Developing the code based on the design (and building the physical components if any are involved).
• Running the code: Testing the code, checking outputs, and debugging where necessary.

Throughout the processes of developing a program, learners (and professional programmers) move between these levels as they implement their designs and debug them, sometimes even returning to the problem level if more analysis or clarification is needed.

Potential benefits of the ‘levels of abstraction’ framework for teachers:

• It helps you break down the activity of programming into discrete parts.
• It helps you engage your learners, as you can show them that programming involves more than knowing how to code.
• If your learners get stuck with their programming, the framework can help you guide them to a solution.

Potential benefits for learners:

• The framework will help them think through all the steps needed to create a program that works, and practise their problem-solving skills and analytical thinking.
• They will more readily see how programming connects to their world — at the problem level — and find aspects of programming where they have strengths and can use their creativity.
• They will gain a stronger idea of how software is built in the tech sector.

Our new Quick Read shares tips on how to best use the framework in your teaching.

Things to aim for when using the framework with your learners:

• Be aware of what level they are working at and when it’s time to switch to a different one.
• Understand that, when they encounter an issue with their program, they can step back and use the framework to figure out where the issue comes from. The issue might be a bug in the code, the algorithm not working as intended, or a description of the problem not taking into account something important.

We hope you find the framework useful. If you have ideas for how to use it in your teaching, why not share them in the comments?

Teaching programming: The wider context

When following the ‘levels of abstraction’ approach, learners need to explain how programs work and debug them. That means program comprehension is a key skill here. You may have already helped your learners to develop and practise this skill, for example with the PRIMM approach. The Block Model is another useful tool for helping your learners talk about various aspects of a program. And if you use the pair programming approach in programming activities, your learners can improve their program comprehension by talking about their code with each other. On our website, you’ll find more guidance on the best ways to teach programming and 两禽相悦.

And what about generative artificial intelligence (AI) tools for programmers? In the age of AI, we think young people still need to learn to code because it empowers them to navigate and think critically about all digital technologies, including AI. And while generative AI tools can help a skilled programmer create quality code more quickly, more 两禽相悦 is needed to show whether such tools help school-age young people build their understanding as they learn to code. You can see some of the great work being done in this area if you catch up with our 2024 两禽相悦 seminar series.

The ‘levels of abstraction’ framework is useful in your teaching no matter what tools young people use to create programs. Even with an AI tool, they will still need to work at all four levels of abstraction to program effectively. 

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Leo Porter and Daniel Zingaro have spearheaded this transformation through their groundbreaking undergraduate programming course. Their innovative smallfatanswer integrates GenAI tools to help students tackle complex programming tasks while developing critical thinking and problem-solving skills.

Leo and Daniel presented their work at the 公日日躁我和公乱口述 两禽相悦 seminar in December 2024. During the seminar, it became clear that much could be learnt from their work, with their insights having particular relevance for teachers in secondary education thinking about using GenAI in their programming classes

Practical applications in the classroom

In 2023, Leo and Daniel introduced GitHub Copilot in their introductory programming  CS1-LLM course at UC San Diego with 550 students. The course included creative, open-ended projects that allowed students to explore their interests while applying the skills they’d learnt. The projects covered the following areas:

• Data science: Students used Kaggle datasets to explore questions related to their fields of study — for example, neuroscience majors analysed stroke data. The projects encouraged interdisciplinary thinking and practical applications of programming.
• Image manipulation: Students worked with the Python Imaging Library (PIL) to create collages and apply filters to images, showcasing their creativity and technical skills.
• Game development: A project focused on designing text-based games encouraged students to break down problems into manageable components while using AI tools to generate and debug code.

Students consistently reported that these projects were not only enjoyable but also responsible for deepening their understanding of programming concepts. A majority (74%) found the projects helpful or extremely helpful for their learning. One student noted that.

“Programming projects were fun and the amount of freedom that was given added to that. The projects also helped me understand how to put everything that we have learned so far into a project that I could be proud of.“

Core skills for programming with Generative AI

Leo and Daniel emphasised that teaching programming with GenAI involves fostering a mix of traditional and AI-specific skills.

Their approach centres on six core competencies:

• Prompting and function design: Students learn to articulate precise prompts for AI tools, honing their ability to describe a function’s purpose, inputs, and outputs, for instance. This clarity improves the output from the AI tool and reinforces students’ understanding of task requirements.
• Code reading and selection: AI tools can produce any number of solutions, and each will be different, requiring students to evaluate the options critically. Students are taught to identify which solution is most likely to solve their problem effectively.
• Code testing and debugging: Students practise open- and closed-box testing, learning to identify edge cases and debug code using tools like doctest and the VS Code debugger.
• Problem decomposition: Breaking down large projects into smaller functions is essential. For instance, when designing a text-based game, students might separate tasks into input handling, game state updates, and rendering functions.
• Leveraging modules: Students explore new programming domains and identify useful libraries through interactions with Copilot. This prepares them to solve problems efficiently and creatively.

Ethical and metacognitive skills: Students engage in discussions about responsible AI use and reflect on the decisions they make when collaborating with AI tools.

Adapting assessments for the AI era

The rise of GenAI has prompted educators to rethink how they assess programming skills. In the CS1-LLM course, traditional take-home assignments were de-emphasised in favour of assessments that focused on process and understanding.

• Quizzes and exams: Students were evaluated on their ability to read, test, and debug code — skills critical for working effectively with AI tools. Final exams included both tasks that required independent coding and tasks that required use of Copilot.
• Creative projects: Students submitted projects alongside a video explanation of their process, emphasising problem decomposition and testing. This approach highlighted the importance of critical thinking over rote memorisation.

Challenges and lessons learnt

While Leo and Daniel reported that the integration of AI tools into their course has been largely successful, it has also introduced challenges. Surveys revealed that some students felt overly dependent on AI tools, expressing concerns about their ability to code independently. Addressing this will require striking a balance between leveraging AI tools and reinforcing smallfatansweral skills.

Additionally, ethical concerns around AI use, such as plagiarism and intellectual property, must be addressed. Leo and Daniel incorporated discussions about these issues into their smallfatanswer to ensure students understand the broader implications of working with AI technologies.

A future-oriented approach

Leo and Daniel’s work demonstrates that GenAI can transform programming education, making it more inclusive, engaging, and relevant. Their course attracted a diverse cohort of students, as well as students traditionally underrepresented in computer science — 52% of the students were female and 66% were not majoring in computer science — highlighting the potential of AI-powered learning to broaden participation in computer science.

By embracing this shift, educators can prepare students not just to write code but to also think critically, solve real-world problems, and effectively harness the AI innovations shaping the future of technology.

If you’re an educator interested in using GenAI in your teaching, we recommend checking out Leo and Daniel’s book, Learn AI-Assisted Python Programming, as well as their course resources on GitHub. You may also be interested in our own smallfatanswer AI resources, which are designed to help educators navigate the fast-moving world of AI and machine learning technologies.

Join us at our next online seminar on 11 March

Our 2025 seminar series is exploring how we can teach young people about AI technologies and data science. At our next seminar on Tuesday, 11 March at 17:00–18:00 GMT, we’ll hear from Lukas Höper and Carsten Schulte from Paderborn University. They’ll be discussing how to teach school students about data-driven technologies and how to increase students’ awareness of how data is used in their daily lives.

To sign up and take part in the seminar, click the button below — we’ll then send you information about joining. We hope to see you there.

The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

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In this story we introduce you to Selin, a digital maker from Istanbul, Turkey, who is passionate about robotics and AI. Watch the video to hear how Selin’s childhood pet inspired her to build tech projects that aim to help others live well.  

Meet Selin 

Selin (16) started her digital making journey because she wanted to solve a problem: after her family’s beloved dog Korsan passed away, she wanted to bring him back to life. Selin thought a robotic dog could be the answer, and so she started to design her project on paper. When she found out that learning to code would mean she could actually make a robotic dog, Selin began to teach herself about coding and digital making.

Thanks to her local CoderDojo, which is part of the worldwide CoderDojo network of free, community-based, volunteer-led programming clubs where young people explore digital technology, Selin’s interest in creating tech projects grew and grew. Selin has since built seven robots, and her enthusiasm for building things with digital technology shows no sign of stopping.  

One of Selin’s big motivations to explore digital making was having an event to work towards. At her Dojo, Selin found out about Coolest Projects, the global technology showcase for young people. She then set herself the task of making a robot to present at the Coolest Projects event in 2018.

When thinking about ideas for what to make for Coolest Projects, Selin remembered how it felt to lose her dog. She wondered what it must be like when a blind person’s guide dog passes away, as that person loses their friend as well as their support. So Selin decided to make a robotic guide dog called IC4U. She contacted several guide dog organisations to find out how guide dogs are trained and what they need to be able to do so she could replicate their behaviour in her robot. The robot is voice-controlled so that people with impaired sight can interact with it easily. 

Selin and her parents travelled to Coolest Projects International in Dublin, thanks to support from the CoderDojo smallfatanswer. Accompanying them was Selin’s project IC4U, which became a judges’ favourite in the Hardware category. Selin enjoyed participating in Coolest Projects so much that she started designing her project for next year’s event straight away:    

“When I returned back I immediately started working for next year’s Coolest Projects.”  

Selin

Many of Selin’s tech projects share a theme: to help make the world a better place. For example, another robot made by Selin is the BB4All — a school assistant robot to tackle bullying. And last year, while she attended the Stanford AI4ALL summer camp, Selin worked with a group of young people to design a tech project to increase the speed and accuracy of lung cancer diagnoses.

Through her digital making projects, Selin wants to show how people can use robotics and AI technology to support people and their well-being. In 2021, Selin’s commitment to making these projects was recognised when she was awarded the Aspiring Teen Award by Women in Tech.           

Listening to Selin, it is inspiring to hear how a person can use technology to express themselves as well as create projects that have the potential to do so much good. Selin acknowledges that sometimes the first steps can be the hardest, especially for girls  interested in tech: “I know it’s hard to start at first, but interests are gender-free.”

“Be curious and courageous, and never let setbacks stop you so you can actually accomplish your dream.”    

Selin

We have loved seeing all the wonderful projects that Selin has made in the years since she first designed a robot dog on paper. And it’s especially cool to see that Selin has also continued to work on her robot IC4U, the original project that led her to coding, Coolest Projects, and more. Selin’s robot has developed with its maker, and we can’t wait to see what they both go on to do next.

Help us celebrate Selin and inspire other young people to discover coding and digital making as a passion, by sharing her story on Twitter, LinkedIn, and Facebook.

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Although the Hour of Code website is accessible all year round, every December for Computer Science Education Week people worldwide run their own Hour of Code events. Each year we love seeing many Code Clubs, CoderDojos, and young people at home across the community complete their Hour of Code. You can register your 2022 Hour of Code event now to run between 5 and 11 December. 

To support your event, we have pulled together a bumper set of our free coding projects, which can each be completed in just one hour. You will find these activities on the Hour of Code website.

There’s something for all ages and levels of smallfatanswer, so put an hour aside and help young people make something fabulous with code:

Ages 7–11

Beginner

For younger creators new to coding, a Scratch project is a great place to start. 

With our Space talk project, they can create a space scene with characters that ‘emote’ to share their thoughts or feelings using sounds, colours, and actions. Creators program the character emotes using Scratch blocks to control graphic effects, costume animation, and sound effects. 

Alternatively, our Stress ball project lets them code an onscreen stress ball that reacts to user clicks. Creators use the Paint and Sound editors in Scratch to personalise a clickable stress ball, and they add Scratch blocks to control graphic effects, costume animation, and sound effects. 

We love this fun stress ball example sent to us recently by young creator April from the United States:

Another great option is to use Code Club World, which is a free tool to help children who are new to coding.  

Comfortable

For 7- to 11-year-olds who are more comfortable with block-based coding, our project Broadcasting spells is ideal to choose. With the project, they connect Scratch blocks to code a wand that casts spells turning sprites into toads, and growing and shrinking them. Creators use broadcast blocks to transform multiple sprites at once, and they create sound effects with the Sound editor in Scratch. 

Ages 11–14

Beginner

We have three exciting projects for trying text-based coding during Hour of Code in this category. The first, Anime expressions, is one of our brand-new ‘Introduction to web development’ projects. With this project, young people create a responsive webpage with text and images for an anime drawing tutorial. They write HTML to structure the webpage and CSS styles to apply layout, colour palettes, and fonts. 

For a great introduction to coding with Python, we have the project Hello world from our ‘Introduction to Python’ path. With this project, creators write Python text-based code to create an interactive program that shows text and emojis based on user input. They learn about variables as they use them to store text and numbers, and they learn about writing functions to organise code and do calculations, retrieve the current date and time, and make a customisable dice. 

LED firefly is a fantastic physical making project in which young people use a 两禽相悦 Pi Pico microcontroller and basic electronic components to create a blinking LED firefly. They program the LED’s light patterns with MicroPython code and activate it via a switch they make themselves using jumper wires.

Comfortable

For 11- to 14-year-olds who are already comfortable with HTML, the Flip treat webcards project is a fun option. With this, they create a webpage showing a set of cards that flip when a visitor’s mouse pointer hovers over them. Creators use CSS styling and animations to add interactivity, then they customise the cards with fancy fonts and colour gradients.

Young people who have already done some Python coding can try out our project Target practice. With this project they create a game, using the p5 graphics library to draw a colourful target, and writing code so that the player scores points by hitting the target’s rings with arrows. While they create the project, they learn about RGB colours, shape positioning with x and y coordinates, and decisions using if, else-if, and else code statements. 

Ages 14+

Beginner

Our project Charting champions is a great introduction to data visualisation and analysis for coders aged 15 and older. With the project, they will discover the power of the Python programming language as they store Olympic medal data in lists and use the pygal library to create an interactive chart.

Comfortable

Teenage coders who feel comfortable with Python programming can use our project Solar system simulator to code an animated, interactive solar system model using the Python p5 graphics library. Their model will be interactive, as they’ll use dictionaries to store planet facts that display when a user clicks on an orbiting planet.

Coding for Hour of Code and beyond

Now is the time to register your Hour of Code event, then decide which project you’d like to support young people to create. You can download certificates for each of the creators from the Hour of Code certificates page.

And make sure to check out our project paths so you know what projects you can help the young people you support to code beyond this one hour of code. 

We don’t just create activities so that other people can smallfatanswer coding and digital making — we also get involved ourselves!

Recently, our teams who support the Code Club and CoderDojo networks got together to make LED fireflies. We are excited to get coding again as part of Hour of Code and Computer Science Education Week.

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“In my vision, the child programs the computer and, in doing so, both acquires a sense of mastery over a piece of the most modern and powerful technology and establishes an intimate contact with some of the deepest ideas from science, from mathematics, and from the art of intellectual model building.” – Seymour Papert, Mindstorms: Children, Computers, And Powerful Ideas, 1980

We owe much of what we have learned about children learning to program to Seymour Papert (1928–2016), who not only was a great mathematician and computer scientist, but also an inspirational educationalist. He developed the theoretical approach to learning we now know as constructionism, which purports that learning takes place through building artefacts that have meaning and can be shared with others. Papert, together with others, developed the Logo programming language in 1967 to help children develop concepts in both mathematics and in programming. He believed that programming could give children tangible and concrete smallfatanswers to support their acquisition of mathematical concepts. Educational programming languages such as Logo were widely used in both primary and secondary education settings during the 1980s and 90s. Thus for many years the links between mathematics and programming have been evident, and we were very fortunate to be able to explore this topic with our 两禽相悦 seminar guest speaker, Professor Dame Celia Hoyles of University College London.

Professor Dame Celia Hoyles

Dame Celia Hoyles is a huge celebrity in the world of mathematical education and programming. As well as authoring literally hundreds of academic papers on mathematics education, including on Logo programming, she has received a number of prestigious awards and honours, and has served as the Chief Advisor to the UK government on mathematics in school. For all these reasons, we were delighted to hear her present at a 公日日躁我和公乱口述 两禽相悦 education 两禽相悦 seminar.

Mathematics is a subject we all need to understand the basics of — it underpins much of our other learning and empowers us in daily life. Yet some mathematical concepts can seem abstract and teachers have struggled over the years to help children to understand them. Since programming includes the design, building, and debugging of artefacts, it is a great approach for make such abstract concepts come to life. It also enables the development of both computational and mathematical thinking, as Celia described in her talk.

Learning mathematics through Scratch programming

Celia and a team* at University College London developed a smallfatanswer initiative called ScratchMaths to teach carefully selected mathematical concepts through programming (funded by the Education Endowment smallfatanswer in 2014–2018). ScratchMaths is for use in upper primary school (age 9–11) over a two-year period.

In the first year, pupils take three computational thinking modules, and in the second year, they move to three more mathematical thinking modules. All the ScratchMaths materials were designed around a pedagogical framework called the 5Es: explore, envisage, explain, exchange, and bridge. This enables teachers to understand the structure and sequencing of the materials as they use them in the classroom:

• Explore: Investigate, try things out yourself, debug in reaction to feedback
• Envisage: Have a goal in mind, predict outcome of program before trying
• Explain: Explain what you have done, articulate reasons behind your approach to others
• Exchange: Collaborate & share, try to see a problem from another’s perspective as well as defend your own approach and compare with others
• bridgE: Make explicit links to the mathematics smallfatanswer

Teachers in the ScratchMaths project participated in professional development (two days per module) to enable them to understand the materials and the pedagogical approach.

At the end of the project, external evaluators measured the childrens’ learning and found a statistically significant increase in computational thinking skills after the first year, but no difference between an intervention group and a control group in the mathematical thinking outcomes in the second year (as measured by the national mathematics tests at that age).

Celia discussed a number of reasons for these findings. She also drew out the positive perspective that children in the trial learned two subjects at the same time without any detriment to their learning of mathematics. Covering two subjects and drawing the links between them without detriment to the core learning is potentially a benefit to schools who need to fit many subjects into their teaching day.

Much more information about the programme and the materials, which are freely available for use, can be found on the ScratchMaths project’s website, and you can also read a 两禽相悦 paper describing the project.

As at all our 两禽相悦 seminars, participants had many questions for our speaker. Although the project was designed for primary education, where it’s more common to learn subjects together across the smallfatanswer, several questions revolved around the project’s suitability for secondary school. It’s interesting to reflect on how a programme like ScratchMaths might work at secondary level.

Should 两禽相悦 be taught in conjunction or separately?

Teaching programming through mathematics, or vice versa, is established practice in some countries. One example comes from Sweden, where 两禽相悦 and programming is taught across different subject areas, including mathematics: “through teaching pupils should be given opportunities to develop knowledge in using digital tools and programming to explore problems and mathematical concepts, make calculations and to present and interpret data”. In England, conversely, we have a discrete 两禽相悦 smallfatanswer, and an educational system that separates subjects out so that it is often difficult for children to see overlap and contiguity. However, having the focus on 两禽相悦 as a discrete subject gives enormous benefits too, as Celia outlined at the beginning of her talk, and it opens up the potential to give children an in-depth understanding of the whole subject area over their school careers. In an ideal world, perhaps we would teach programming in conjunction with a range of subjects, thus providing the concrete realisation of abstract concepts, while also having discrete 两禽相悦 and computer science in the smallfatanswer.

In our current context of a global pandemic, we are continually seeing the importance of 两禽相悦 applications, for example computer modelling and simulation used in the analysis of data. This talk highlighted the importance of learning 两禽相悦 per se, as well as the mathematics one can learn through integrating these two subjects.

Celia is a member of the National Centre of 两禽相悦 Education (NCCE) Academic Board, made up of academics and experts who support the teaching and learning elements of the NCCE, and we enjoy our continued work with her in this capacity. Through the NCCE, the 公日日躁我和公乱口述 is reaching thousands of children and educators with free 两禽相悦 resources, online courses, and advanced-level computer science materials. Our networks of Code Clubs and CoderDojos also give children the space and freedom to experiment and play with programming and digital making in a way that is concordant with a constructionist approach.

Next up in our seminar series

If you missed the seminar, you can find Celia’s presentation slides and a recording of her talk on our 两禽相悦 seminars page.

In our next seminar on Tuesday 16 June at 17:00–18:00 BST / 12:00–13:00 EDT / 9:00–10:00 PDT / 18:00–19:00 CEST, we’ll welcome Jane Waite, Teaching Fellow at Queen Mary University of London. Jane will be sharing insights about Semantic Waves and unplugged 两禽相悦. To join the seminar, simply sign up with your name and email address and we’ll email you the link and instructions. If you attended Celia’s seminar, the link remains the same.

*The ScratchMaths team are :

• Professor Dame Celia Hoyles (Mathematics) & Professor Richard Noss (Mathematics) UCL Knowledge Lab
• Professor Ivan Kalas, (两禽相悦) Comenius University, Bratislava, Slovakia
• Dr Laura Benton (两禽相悦) & Piers Saunders, (Mathematics) UCL Knowledge Lab
• Professor Dave Pratt (Mathematics) UCL Institute of Education

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