Tag Archives: quick reads

How to improve students’ problem-solving skills using subgoal labels

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-improve-students-problem-solving-skills-using-subgoal-labels/

When faced with a programming problem, computing educators often start solving it without a second thought. Before writing a single line of code, experienced programmers use a range of skills to choose their approach and make other key decisions. Thanks to repeated practice, many of these decisions feel automatic and require little conscious thought. However, for beginner programmers, starting a programming problem can feel overwhelming, requiring intense thought and concentration. 

Graphic displaying the Raspberry Pi Foundation's Subgoal labels Quick Read
The Quick Read on subgoal labels

So how can we be more aware of the automatic steps we take and choices we make so that we can break them down for learners, and make it easier for them to solve problems?

In today’s blog, we look at what ‘subgoal labels’ are and how they can be used as a form of scaffolding to support learners in breaking down computer science and programming problems. 

We also share the new subgoal labels Quick Read, which you can download for free to:

  • Find practical tips for using subgoal labels into your lessons
  • Read a summary of the research related to adopting and using subgoal labels in computing education

What are subgoal labels?

Subgoal labels are simple instructions that can be added to tasks — they are particularly useful when added to worked examples. They act as signposts to provide clear directions for a larger task.

Photo of educators programming on Scratch in a computing classroom

Let’s look at the following example: You’re working through a programming problem with your students. The task requires them to draw a shape using a turtle sprite. Instead of just showing learners a complete script, you could instead add these subgoal labels to the worked example. 

Programming problem: Draw a blue square in the top right corner of the screen using a screen turtle.

  • Subgoal 1: Set pen properties (e.g. width and colour)
  • Subgoal 2: Move turtle
  • Subgoal 3: Orient turtle
  • Subgoal 4: Call function

The labels act as scaffolding for students, helping them break down the task and work through it. While the exact number or specific context of the goals might change from one project to the next, the idea is always to break down tasks into smaller, more manageable actions.

How can you use subgoal labels in practice?

You do not need to redesign your entire curriculum to start seeing the benefits of this approach. Here are three practical ways to introduce subgoal labels in your next computing lesson:

  1. Create some labels on any worked examples in your next lesson. You could use this as an opportunity to collaborate with colleagues, and come up with the labels together.
  2. Co-create with AI. Have your students use a generative AI tool to suggest subgoal labels for a piece of code they’ve written, using it as a starting point for a class discussion on structure.
  3. Teach your students how to write their own subgoal labels. This helps them look past the surface details of a task and build a portable problem-solving strategy they can apply to future projects.

Why use subgoal labels in your classroom?

Integrating these labels into your teaching practice offers lots of benefits, for example:

  • Help reduce mental load: Worked examples offer a brilliant way to introduce new programming concepts, but they can actually add to students’ cognitive load. This is because learners are required to process the specific context a problem is set in, in addition to the actual problem they need to solve. Adding labels eases this mental load by directing attention back to the structural steps needed to solve the problem, rather than its surface-level context.
  • Make implicit knowledge explicit: As discussed above, the skill of programming can feel automatic for experienced educators, making it difficult to explain why you’re doing things the way you are. Subgoal labels help you to clearly break down your thoughts and reasoning, making your decision-making visible and structured for your learners.
  • Boost classroom performance and persistence: Research shows that using subgoal labels can improve student performance. In studies using block-based programming, students using subgoal-oriented materials scored 7 to 8% better on assessments. Additionally, students using subgoal labels as part of text-based introductory courses were half as likely to fail or withdraw compared to students who did not use subgoal labels.

Want to know more?

Download the full Subgoal Labels Pedagogy Quick Read as a PDF:

Download the Quick Read

The post How to improve students’ problem-solving skills using subgoal labels appeared first on Raspberry Pi Foundation.

How to design and present clear computing lessons

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-design-and-present-clear-computing-lessons-mayers-principles/

Learning something new requires effort. Learners take in new information by listening and observing. When a lot of information is presented at once in a lesson, that can create too much cognitive load for learners — a barrier to understanding and engagement.

To help you design and deliver great computing lessons, we’ve written two new Pedagogy Quick Reads focused on Mayer’s Principles of Multimedia Learning. These research-backed principles give you practical strategies to lower your students’ unnecessary cognitive load during lessons, leading to better learning outcomes.

A snapshot of our pedagogy quick reads.

In this blog, we introduce the two new Quick Reads (Designing multimedia for clarity and Designing multimedia for understanding), which you can download for free to:

  • Find practical tips for how you can apply Mayer’s Principles to your lessons
  • Read a summary of the research behind them

The blog also includes some examples for how to apply the principles in your computing lessons.

If you’d like an introduction to the idea of cognitive load, you can find the Quick Read about cognitive load theory here.

In a computing classroom, a girl looks at a computer screen.

What are Mayer’s Principles?

Mayer’s Principles of Multimedia Learning are practical principles that will help you create clearer resources and present information in a way that avoids unnecessary cognitive load for your learners.

Mayer’s Principles are based on three related facts:

  1. You can present information to learners in auditory form (e.g. spoken explanations) and visual form (e.g. written text, diagrams)
  2. There are limits on how much new information people can take in at the same time
  3. Teaching materials that are not well-structured can cause too much cognitive load, which negatively affects learning

Designing lessons for clarity

Our first new Quick Read focuses on the following Mayer’s Principles for making your lessons as clear as possible, so that learners can connect the information they see and hear in real time.

  • Make all the information you include coherent, meaning that it is directly relevant to the learning objectives and does not distract learners’ attention
  • Guide your learners’ attention by using signals such as arrows, bold text, colour, or auditory cues
  • Avoid redundant information, such as a slide with a diagram and a paragraph explaining the diagram, or a slide that you speak about without adding new, complementing information
  • Present related words and visuals in the same space, e.g. place your text labels, or explanations directly adjacent to diagrams, images or code segments they describe
  • Present related words and visuals at the same time, e.g. by pairing narration with imagery

Designing lessons for understanding

Our second new Quick Read shares three Mayer’s Principles for how you can structure your lesson delivery to support your learners’ understanding:

  • Structure lessons or demonstrations into clear, manageable stages or segments, rather than presenting the information all at once
  • When you start a new topic, begin with some pre-training by introducing key terms, components, or goals and how they relate
  • When you present diagrams, flowcharts, or code examples, explain this visual information using the other modality, meaning spoken narration, instead of using paragraphs of text

Applying Mayer’s Principles to your computing lessons

We suggest you consider implementing Mayer’s Principles when you next design new lessons or want to adapt materials that you reuse regularly.

Here are some ideas on how you use both sets of principles in common computing teaching scenarios.

Live coding and code walkthroughs

When displaying a new Python script or Scratch project, avoid adding long, written paragraphs of commentary to explain the code. Instead, place short text annotations or sub-goal labels directly next to the relevant lines or blocks. As you run through the code, use your pointer or live typing to guide your learners’ focus (signalling) and explain in words how the program works at the same time.

Starting a new topic such as networking

Before students move to a new topic, for example networking, consider what words or concepts your class needs to be familiar with. Allocate a few minutes at the start of your lesson for pre-training to introduce terms like LAN or bandwidth and how they relate to the lesson.

Learners in a computing classroom.

Consider how your lesson can be divided into stages to allow for better understanding (segmenting). Each stage should build on the previous one and feed into the next one. For example, when you explain how data moves across a network, you can introduce each step separately before combining them all into a complete model of a network.

Consider how you display visual information to your class. Ensuring related diagrams and labels appear close together, only include relevant materials and no decoration on your slides (coherence), and avoid simply reading out words on the slide identical forms of information (redundancy).

Supporting multilingual learners with Mayer’s Principles

Mayer’s Principles are even more important for educators teaching multilingual learners or non-native speakers. When learners need to work harder to understand the language, poor lesson design can slow down their learning significantly.

Mayer’s Principles can help you with this challenge:

  • Applying the coherence and redundancy principles will allow you to make your explanations and slides as clear and concise as possible
  • Using signaling will mean you help learners to follow along and know what is most important
  • Presenting diagrams that illustrate computing concepts clearly will help your multilingual learners understand your spoken explanation much more easily (modality)

Intentional design for lasting understanding

By intentionally designing and presenting lessons to give the right amount of information in the clearest way, you make it easier for your students to focus and build a lasting understanding of computing concepts. When your lesson materials align with how our brains process information, learners can build stronger mental models and approach independent learning activities with greater confidence.

Read our new Quick Reads to find out more and discover the research behind Mayer’s Principles:

Download the ‘Designing multimedia for clarity’ Quick Read
Download the ‘Designing multimedia for understanding’ Quick Read

The post How to design and present clear computing lessons appeared first on Raspberry Pi Foundation.

Support your young people with our AI literacy resources

Post Syndicated from Jenni Hutchings original https://www.raspberrypi.org/blog/ai-education-resources-ai-awareness-day/

At the Raspberry Pi Foundation, we believe that alongside learning to code, a crucial part of computing education is building AI literacy skills. Amidst the rapid pace of development and the growing impact of AI tools, it is increasingly important for educators everywhere to feel equipped to address the topic of AI with their learners, to help young people understand their world, be responsible users of AI technologies, and prepare to become the future creators of these technologies. 

We work at the leading edge of AI education, combining research and industry expertise with practical classroom experience to define what AI means for computing education, and how to best support teachers and learners to understand these technologies. 

Whether you are a teacher, a Code Club mentor, or a parent, we have a wide range of free resources to help you teach your young people about AI, and learn more about it yourself.

Explore our teaching resources

We offer a variety of teaching materials to help you bring AI into your setting. You do not need to be a professional educator or have a background in computer science to use these resources, and we provide everything you need to guide your learners with confidence.

Experience AI is our free AI literacy programme, developed in collaboration with Google DeepMind. Through ready-to-use classroom resources, including lesson plans, presentations, and hands-on activities, the programme helps educators all over the world teach their learners about how AI works, as well as its wider social and ethical implications. You and your learners will investigate AI tools, explore real-world uses of AI, and engage with critical issues such as bias, fairness, and transparency, helping learners to understand AI and use it responsibly. The lessons currently available are designed for learners aged 11–14, and we are releasing resources for other age groups this year.

To help bring Experience AI to more educators and learners around the world, we work with a global network of partner organisations, who help us provide tailored and translated resources and offer localised, high-quality training and support for educators in their regions. Experience AI resources are currently available in 19 languages, and have already been downloaded in more than 180 countries. In recognition of its impact, in 2025 Experience AI was named a laureate of the UNESCO King Hamad Bin Isa Al-Khalifa Prize for the Use of ICT in Education.

“[Experience AI] has definitely changed my outlook on AI. I went from knowing nothing about it to understanding how it works, why it acts in certain ways, and how to actually create my own AI models and what data I would need for that. I would 100% recommend others who don’t know much about AI to try it out.” – Student, Arthur Mellows Village College, UK

If you are looking to introduce school-aged young people to AI with short, beginner-friendly coding  and digital making projects, take a look at our collection of Code Club projects about AI and machine learning. These projects are a great way to spark curiosity and investigate how AI and machine learning works.

In the projects, learners get hands-on with a range of AI tools and platforms, and explore different applications of AI, such as image recognition, voice recognition, and (for learners aged 13 and over) generative AI. For example, in Doodle detector, learners use Machine Learning for Kids with Scratch to create a machine learning application that can identify what they have drawn. 

The projects feature clear step-by-step instructions, and many include video tutorials, to help learners work at their own pace and in a style that suits them. We also provide mentor guidance to help you prepare.

An illustration of an image classification application correctly identifying a drawing of an apple.
Learners can explore topics such as image classification through our collection of Code Club projects about AI and machine learning

For resources to support older learners to build their understanding of AI, head to Ada Computer Science. Ada Computer Science is our free online platform for computer science students and teachers, developed in partnership with the University of Cambridge. It provides comprehensive resources for learners aged 14–19 across the breadth of computer science, including detailed learning materials about AI and machine learning. The materials include helpful definitions, clear explanations, and carefully designed self-marking questions to support young people’s learning.

Learners aged 14–19 can build their knowledge of AI and machine learning on our Ada Computer Science platform
Learners aged 14–19 can build their knowledge of AI and machine learning on our Ada Computer Science platform

Explore our learning and training opportunities for educators

To help you build your knowledge around AI technologies and grow your confidence to teach your young people about this important topic, we offer a range of learning resources and professional development opportunities, all for free. They are open to everyone, so we invite you to dive into any that interest you.

For flexible, self-paced learning options, take a look at the following free online courses, which cover a range of topics within AI:

  • Introducing AI: Investigate how AI systems work and how to evaluate them, and explore the benefits, risks, and ethical issues related to them. This course is made up of 2 modules, and takes around 2–4 hours to complete.
  • AI literacy for teachers and school leaders: Learn how to support your students and staff to understand, use, and critically assess AI technologies. This course takes around 1–2 hours to complete. 
  • Machine learning and AI: Discover machine learning and how it works, and train your own AI models using free online tools. This course is made up of 4 modules, and takes around 4–8 hours to complete.
Learn more about AI through our free online courses for educators
Learn more about AI through our free online courses for educators

You might also be interested in Hello World, our free magazine and podcast for educators teaching computing and AI. Each magazine is packed with resources, discussions, news, and ideas, and you can subscribe to receive each issue as soon as it is released. The next issue, coming in July, will focus on critical thinking in the age of AI. You can download our previous issues to explore articles about a variety of topics within AI too. What’s more, you can continue your learning with the Hello World podcast, which accompanies the magazine and features discussions with educators and researchers from around the world. Visit the podcast page to discover previous episodes exploring vibe coding and programming education, AI education around the world, and more.

Hello World Issue 29 - Safety & security
Hello World Issue 29 – Safety & security

To learn about research-informed teaching strategies to help you as you explore AI with your learners, you can read these short Pedagogy Quick Reads:

  • Anthropomorphism: Explore how to help learners avoid thinking of AI systems as human-like, to support their understanding.
  • Computational Thinking 2.0: Consider how computational thinking is evolving and how to help learners develop the computational thinking skills they need to understand modern digital systems involving AI.
  • Feedback literacy: Explore how feedback literacy can help teachers and learners interact effectively with feedback generated by AI tools.
A Pedagogy Quick Read entitled ‘The effects of anthropomorphisation on students’ mental models of AI’.
A Pedagogy Quick Read entitled ‘The effects of anthropomorphisation on students’ mental models of AI’.

For more insights from computing education research, you can join our monthly online research seminars. Our 2026 research seminar series focuses on teaching about AI across the curriculum, delving into research on teaching and learning about AI from disciplines beyond computer science, including the arts, sciences, and humanities. Our next seminar takes place on 16 June, and you can catch up on previous seminars from our current series here. You can also explore our archive of recordings from previous seminar series, with themes including teaching about AI and data science, teaching programming (with or without AI), and more.

Bring AI into your classroom today

All of these resources and learning opportunities are available to anyone interested in educating young people about AI, anywhere in the world. We hope they help you gain understanding, confidence, and inspiration to guide your young learners to engage with AI safely and responsibly, and to learn valuable skills that will help them navigate their world.

“Let the students explore, advance, and grow. And who knows — maybe one of our students will go on to become a mentor or leader in this field someday.” – Ana Judith Zavaleta, computer science teacher, Mexico, speaking about Experience AI

If you are in the UK, you can also use these resources to get involved with the first-ever AI Awareness Day, a new nationwide campaign designed to build AI literacy across UK schools, which is taking place on 4 June.

The post Support your young people with our AI literacy resources appeared first on Raspberry Pi Foundation.

Professional development: How to stay ahead in a fast-changing subject

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/professional-development-how-to-stay-ahead-in-a-fast-changing-subject/

What does great training for computing teachers look like?

High-quality professional development (PD) is one of the most effective ways to improve your students’ outcomes, and participating in PD is a core part of being a teacher. By changing and refining your teaching practices, you can create a direct, positive impact on the young people we teach.

Image displaying the Professional Development Pedagogy Quick Read, from the Raspberry Pi Foundation.

In this blog, we share our new professional development Quick Read, which you can download for free to:

  • Find practical tips for how to use and design effective professional development opportunities
  • Read a summary of the research behind effective PD

The unique impact of professional development for computer science educators

Professional development is vital for anyone teaching computing. In many subjects, the curriculum stays the same for decades. Computer science, however, can change quickly — as with the development of new technologies such as AI and quantum computing, and new hardware — and PD can help you stay up to date.

An educator teaches students to create with technology.

Another challenge is that many educators who teach computing are not necessarily subject specialists. So educators often benefit from building their own subject knowledge and learning new computing-specific pedagogical approaches through PD.

What makes effective professional development?

Drawing on academic research and our own expertise, we’ve identified several key principles that make professional development effective for computer science educators:

  • Learner-focused and research-informed: PD should be based on evidence and equip you with the skills and confidence to make real changes in your practice
  • Sustained and actionable: The best outcomes happen when you can select your own learning pathways and you’re given the time to test, adapt, and reflect on new approaches
  • Collaborative and contextual: Sharing ideas and new ways of thinking with other educators in a low-stakes environment can help you and your peers benefit from different perspectives and experiences

There may be factors that influence your teaching that you have little control over: you might teach computing as a standalone subject, or you may be required to weave computer science into other lessons across the curriculum. Or you might be working with older devices or limited internet access, all of which have an impact on your practice.

Effective PD should recognise these realities, and offer practical tools that work for your specific classroom and students.

How to find or design PD for computing educators

You can use the principles in our latest Quick Read when you’re looking for your next training course or if you are designing a session for your team. The full list of principles is available in our Quick Read, but here are some ideas for you to consider:

  • Focus on small, manageable changes: Rather than trying to overhaul your entire teaching practice at once, reflect on one approach at a time and adapt it as necessary before moving on to the next
  • Encourage low-stakes rehearsal: Practise new techniques with peers before implementing them in a live lesson
  • Align with school priorities: Ensure your self-directed learning also meets the wider needs of your department or school

You can read more about the principles of effective PD in our Quick Read.

The benefits of professional development

Potential benefits for teachers:

  • Provides a clear structure for updating your subject knowledge and teaching methods
  • Helps you feel more confident teaching 
  • Allows you to take ownership of your career journey and focus on what matters most to your students

Potential benefits for learners:

  • Improved learning outcomes through:
    • Higher quality lessons
    • More engaging lessons 
    • Lessons better suited to their individual needs

Our new Quick Read shares tips on how to best use these principles in your setting.

Download the Quick Read

The post Professional development: How to stay ahead in a fast-changing subject appeared first on Raspberry Pi Foundation.

How to evaluate your use of classroom technology with the PICRAT framework

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-evaluate-your-use-of-classroom-technology-with-the-picrat-framework/

There’s always something new to consider when teaching with technology. From the latest advancements in AI, to new software and hardware updates, it can be difficult to know which tools to use and how to incorporate it effectively into your lessons.

In today’s blog, we explore the PICRAT framework and how it can help you reflect on your use of technology in the classroom. 

We also share our new PICRAT Quick Read, which you can download for free to: 

  • Find practical tips on how to use the PICRAT model when planning your lessons
  • Read a summary of the research behind the framework

What is the PICRAT framework?

Technology is constantly changing, and educators must continually decide what tools to use in their practice. To help with this challenge, researchers started developing theoretical models that teachers (especially student teachers) could use to reflect on how they integrate technology in their classrooms.

You might already be familiar with frameworks like TPACK (Technology, Pedagogy, and Content Knowledge) and SAMR (Substitution, Augmentation, Modification, Redefinition). While these models are useful, the PICRAT framework was created to address gaps in these earlier models, offering a clearer, student-focused approach. Significantly, it encourages you to treat technology as a tool to support learning, rather than the goal itself.

It asks two simple questions: “How are students experiencing the technology?” and “How does this impact your practice?”. The answers to these questions form a matrix as pictured below. 

PIC (which runs along the y-axis) refers to the student’s relationship to the technology:

  • Passive – Students receive learning through technology
  • Interactive – Students interact with the content or other learning through technology 
  • Creative – Students construct knowledge using technology

RAT (which runs along the x-axis) refers to how the teacher uses the technology:

  • Replaces – Using technology but with an existing pedagogy
  • Amplifies – Using technology to improve pedagogy or outcomes
  • Transforms – Using technology to create new pedagogical practices

How can I apply the PICRAT model?

First choose the lesson you’re planning to deliver. Consider what activities you’ll be running and the technologies involved. You’ll then be able to plot where they sit on the matrix using the PICRAT acronym.

For example, if you are teaching a lesson on Python loops, you might initially plan for students to watch a pre-recorded coding tutorial on their laptops. In this scenario, the student experience is Passive (receiving info via tech), and the teacher’s use is Replacement because the video simply replaces a live lecture. To move up the matrix, you could instead have students use an online IDE to complete a “Parson’s Problem” puzzle where they rearrange blocks of code to fix a loop. This shifts the activity to Interactive and Amplification, as the digital tool provides immediate debugging feedback that a paper-based exercise could not.

Educator presenting in a classroom.

Next, think about how you might move your practice forwards. Although every position on the matrix has its own value, the framework is hierarchical. The overall goal is to try to move your practice towards the top right of the matrix to be Creative and Transformative.

To help you achieve this, take some time to reflect on your current lessons, activities, and the technologies you use. Ask yourself questions like:

  • What does the technology I’m using offer that could be used to amplify my practice?
    • What benefits would this have for students?
  • Does the technology present opportunities for students to interact with each other, not just the technology?
  • What other technological tools might support collaboration? 

Research highlights that technology is rarely used in ways that allow young people to be creative. By using the PICRAT matrix, teachers can identify missed opportunities and explore ways to transform their lessons, ensuring learners can be creative and thrive.

The benefits of the PICRAT model

Potential benefits for educators:

  • The framework encourages meaningful reflections, allowing teachers to easily evaluate how they’re using technology within their lessons
  • Reflections and the PICRAT matrix helps teachers to identify missed opportunities and gaps in their practice, ultimately leading to better student experiences
Photo of educators sharing ideas in a classroom.

You can use the PICRAT framework as part of your own reflections, or as part of a group activity. It’s a great way to spark discussion about technology integration with colleagues and improve best practices.

Want to find out more about the PICRAT framework?

If you’d like to learn more about the PICRAT model, you can download our Quick Read for free via our new Pedagogy Quick Reads page.

Download the PICRAT Pedagogy Quick Read

The post How to evaluate your use of classroom technology with the PICRAT framework appeared first on Raspberry Pi Foundation.

How to strategically plan your computing curriculum

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-strategically-plan-your-computing-curriculum/

Traditionally, curriculum planning has often looked like a linear list: Topic A leads to Topic B, which leads to Topic C. However, as educators we know that learning rarely happens in such a simple, linear way. Concepts are regularly covered in different overlapping topics, and students can often take different routes to reach the same destination.

Image displaying the Learning Graphs Quick Read.

In today’s blog we’re exploring learning graphs, a helpful tool that you can use to plan your computer science curriculum. We’ll share how they can provide educators with a clear, structured way to visualise students’ non-linear progression in a subject.

We also share our new Pedagogy Quick Read about learning graphs, which you can download for free to:

  • Find practical tips on how you can use learning graphs to design your curriculum
  • Read a summary of the research behind them

What is a learning graph?

A learning graph is a visual tool for curriculum planning that moves beyond simple lists. At its core, a learning graph is a network of ‘nodes’ (specific concepts and skills) and ‘links’ (the connections between them).

Image from the Learning Graphs Quick Read that showcases an example of a learning graph.

Learning graphs build on research into ‘learning progressions’ and ‘knowledge maps’. They are a practical tool that educators can use to design and validate different curricula. For example, they can help teachers to:

  • Visualise and map progression
  • Identify curriculum gaps, so educators can shape and restructure learning experiences as necessary
  • Ensure the use of consistent terminology
  • Sequence learning and manage cognitive load

How to create a learning graph

Building a learning graph is an iterative process that helps you think critically about how different parts of your curriculum relate to each other.

Nodes and links

The first step in creating a learning graph is often to identify your start and end nodes. First, you consider the key concepts and skills that your learners must acquire by the end of a series of lessons. This gives you some end nodes to work towards. Then, you think about learners’ existing knowledge, to help determine your start point. You then work backwards and forwards between these points to identify the different nodes that learners need to cover to get from the beginning to the end.

Educators sharing ideas around a table.

Once you have determined your nodes, you add them to your graph and connect them via ‘links’ until your graph is complete. Where knowledge of particular concepts or skills is essential for learning others, you connect the nodes with solid lines. For prior learning that is helpful but not essential, you use dotted lines.

When developing a learning graph, there isn’t a specific level of granularity that you have to work towards. Progression can be as detailed or as high-level as you need. This makes them a helpful tool in creating bespoke learning experiences and curricula for learners.

Collaboration and development

It is most effective to design learning graphs collaboratively within a small group. This allows curriculum designers to discuss their ideas and challenge each other’s thinking, which helps hone the designs.

Educators collaborating using post-it notes, planning currciulum.

When creating learning graphs, it can be extremely useful to use a tool that is dynamic and allows you to move elements and make changes quickly and easily. At the Raspberry Pi Foundation, our team has experimented with a range of tools, including using editable shapes in Google Slides, collaborating in Figma, and arranging sticky notes on paper. We recommend finding a tool that works for you and the educators you are working with. Although it can work, we suggest avoiding using a pen and paper if possible, as designs can quickly become messy and difficult to navigate after lots of iterations.

The process of designing learning graphs has strong links to ABC learning design and the creation of concept maps, which can also be used for curriculum planning.

Learning graphs in your teaching

Once created, learning graphs can support you to design and adapt your curricula and assess your students’ learning.

For example, to help sequence learning, you can track or predict the paths through a topic most commonly taken by learners and use this to inform your curriculum design.

If you are adapting a unit of work for a specific qualification or new context, you can prune nodes that are not relevant and add any further knowledge and skills your learners need, then use the new learning graph to guide you as you develop the unit.

Finally, you can assess which node a learner has completed, and use this to identify the next logical step in their learning, ensuring the difficulty level is always appropriate.

Using learning graphs to support analysis

Another benefit of learning graphs is that they can be combined with lots of other frameworks, for example, Bloom’s taxonomy. This allows you to better assess and validate the learning journeys you have designed, and ensure that they are suitably accessible, challenging, and relevant for your learners.

Photo of an educator presenting at the front of a classroom of other teachers.

There are a number of ways that you could link your learning graphs to other frameworks, such as annotating nodes with extra information, or using colour coding.

As well as working with learning graphs for specific learning experiences, you can connect multiple learning graphs together and analyse how they intersect. This can help identify inconsistencies between connected sequences of lessons. It can also help uncover broader themes of progression and highlight alternative learning pathways you might not have considered.

Find out more about learning graphs

If you’d like to find out more about learning graphs, you can download our Pedagogy Quick Read for free.

Download the learning graphs Pedagogy Quick Read

To find out more about how we use learning graphs when planning curriculum resources at the Raspberry Pi Foundation, take a look at our teaching and learning design principles.

The post How to strategically plan your computing curriculum appeared first on Raspberry Pi Foundation.

How social learning can lead to better outcomes in your computing classroom

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-social-learning-can-lead-to-better-outcomes-in-your-computing-classroom/

Throughout our lives, we’re constantly learning from others. Whether we’re interacting with teachers or trainers, or observing friends or strangers, we’re learning either deliberately or inadvertently. This process is known as ‘social learning’. 

In today’s blog, you’ll dive into what social learning is and how you can use it to create more engaging and effective learning experiences in your computing classroom.

Image of our latest Pedagogy Quick Read

You’ll also find our latest Pedagogy Quick Read, which explores social learning. It’s free to download and includes: 

  • Practical tips for how to use social learning and related approaches with your learners
  • A summary of the research behind social learning

What is social learning?

Social learning is simply any learning that involves other people. It can take any form, from watching a video, to taking part in a classroom discussion. It can take place in person or online, and it can happen without people realising they’re learning something.

Social learning is based on modelling and involves people observing and imitating the behaviours that others model. Albert Bandura, the acknowledged originator of social learning theory, suggested that social learning is guided by four related processes:

  • Attention: Recognising and focusing on someone’s behaviour and its vital elements
  • Retention: Creating a mental image and description to help you recall what you observed; practising responses (mentally or actively)
  • Reproduction: Translating the mental image back into actions
  • Motivation: Having a good reason to repeat (or avoid) the behaviours, depending on the rewards or punishments involved

How can I enable social learning?

There’s lots of ways you can involve social learning in your computing classroom, including through other teaching approaches and frameworks. 

4 children social learning in the classroom

To help your learners get the most out of social learning, it’s best to:

  • Create a safe environment for learners to share learnings, ask questions, and actively engage in the learning process
  • Include a mix of resources and activities to ensure inclusion and accessibility
  • Set clear expectations and instructions, and ensure that social learning is key to achieve learning objectives

Applying social learning: Some teaching approaches

Among our pedagogy resources, you’ll find lots of practical advice for teaching approaches that promote social learning. The approaches we recommend for the pedagogy principles ‘Work together’ and ‘Model everything’ are especially suitable.

Work together:

Model everything:

Using a PRIMM (PDF) approach for structuring programming lessons, and encouraging students to talk about code as part of these, also works well for social learning.

Applying social learning: Practical examples

Let’s look at pair programming as an example. In this activity, pairs of learners work together to create a computer program, taking on distinct roles that they swap regularly. One learner acts as the ‘driver’, writing the code, while the other is the ‘navigator’, guiding the process, reviewing the code, and identifying potential issues. 

As they work, each learner is able to observe the other person’s approach, learning with and from their partner throughout the activity. This constant interaction and shared problem solving can help them to understand programming concepts better and to build stronger teamwork skills.

Children in the classroom social learning

Another example is setting your class the task to create shared digital resources on several topics everyone needs to learn about. In this activity, you split learners into small groups or pairs, and assign them a topic to later explain to the whole group. Grouped learners work together to create a resource explaining their topic. As the facilitator, you can either provide the information they need, or let them conduct their own research. At the end of the activity, each group presents their resource to the wider class.

An activity like this helps learners develop their knowledge through working together and talking to each other, and also provides the class with resources they can keep using.

The benefits of social learning

Potential benefits for teachers:

  • Improved student engagement and learning
  • Enhanced professional development experiences, leading to more confident teaching

Potential benefits for students:

  • Improved social skills
  • Opportunities to build higher-level thinking skills
  • Deeper understanding and a greater ability to remember knowledge in the long term
Download the Quick Read on social learning

A social approach to shaping the future

In a world filled with complex challenges, there’s more need than ever for people to work together. By using social learning approaches in your classroom, you help your students to engage more deeply with your teaching and to develop the skills to succeed in collaboration with others. In this way, you’ll prepare them for navigating technological change as well as for shaping a common future where everyone can thrive.

The post How social learning can lead to better outcomes in your computing classroom appeared first on Raspberry Pi Foundation.

How to rapidly design and adapt quality learning experiences for your students

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-rapidly-design-and-adapt-quality-learning-experiences-for-your-students/

At this time of year, many educators are considering ways to update their content ahead of the new school term. Whether you’re a teaching assistant or head of department, it’s important to ensure that the content you’re updating — or even designing anew — is relevant and high quality, and meet learners’ needs. In today’s blog we’re highlighting ‘ABC learning design’, and how it can be used to rapidly design and improve learning experiences.

Educators in the classroom

We also share our new ABC-focused Pedagogy Quick Read, which you can download for free to: 

  • Find practical tips on how to use the ABC process and related approaches with your learners
  • Read a summary of the research behind the framework

What is ABC learning design?

ABC learning design is a rapid, hands-on approach to design and develop blended learning experiences. The framework has traditionally been used at undergrad level, and had a lot of success when used in response to the global pandemic in 2020, when learning experiences had to quickly transition from being delivered in-person to being accessible remotely. 

The model is centred around six learning types:

  • Acquisition: Learning by reading, listening, or watching
  • Collaboration: Learning by working with others towards a common goal, involving co-creation and shared outputs
  • Discussion: Learning through dialogue, sharing ideas, and responding to others
  • Investigation: Learning by exploring, comparing, and evaluating new information or experiences
  • Practice: Learning by applying knowledge and skills, receiving feedback, and refining understanding
  • Production: Learning by expressing understanding or creating something to demonstrate knowledge and skills

Before continuing, it’s important to distinguish between ‘learning types’ and the widely discredited concept of ‘learning styles’. Whilst learning styles refer to fixed characteristics or preferences of learners, learning types refer to different kinds of learning activities and pedagogical approaches that can be designed into a course.

Copy of the ABC learning design Pedagogy Quick Read

These learning types are representative simplifications of pre-existing learning theories. For each learning type, educators can use different activities to deliver that type of learning. The activities will depend on your context and what’s right and applicable for your students.

How can I apply ABC learning design?

ABC learning design is often done in a team-based workshop setting (you can do it by yourself as well). Firstly, you analyse your existing content. Consider the goal of your current learning sequence, and assess how your learners are going to reach that goal with the different learning types.

Educators in the classroom

By analysing existing content and activities, you can then identify what’s missing from your sequence. This allows you to build on existing gaps and consider different types of activities you could implement. You then create a set of learning cards, which help you to storyboard and plan your new learning sequence.

Learning cards are typically postcard-sized and colour-coded to one of the six learning types. Colour coding helps you to tell the cards apart, and to easily see which learning types are or aren’t included in your sequence. 

Each card has the name and a short description of the learning type on the front, with examples of associated digital or in-person learning activities on the back. The learning cards:

  • Make the design process more engaging
  • Help with decision making
  • Support discussions if you’re working in a team
ABC Learning design cards and their application to an ABC storyboard plan

Adapting ABC learning design for your context

ABC design can be contextualised to your classroom, practices, and school, and to the technologies you have available. For example, on the back of each learning card you could include a set of activities that have been tried and tested in, or approved by, your school. Alternatively, you could link to other frameworks or teaching approaches that work for you and your students. 

Learning cards can also be used to collect other insights about teaching and learning within your context, and used as reminders of pedagogies to implement, as well as practical concerns. They can also help you to consider if there are opportunities for cross-curricular links within your learning sequence.

A shared toolkit you can reuse

In a computing department, ABC learning cards can become a shared resource that give fellow educators an understanding of what’s possible. The cards can be used again and again to help plan future learning experiences. 

Educators sharing ideas on a whiteboard

By running an ABC workshop and creating these learning cards, you and your team will put together a contextualised learning sequence toolkit specific to your school and learners.

Integration with universal design for learning to improve accessibility

In our blog How to build young people’s agency through accessible learning, we explored the universal design for learning (UDL) framework. UDL aims to support educators to reduce barriers for learners. It helps educators to create learning environments that are accessible and effective for all learners by providing multiple means of engagement, representation, and action and expression.

Gormley et al. (2022) described an initiative to integrate UDL within ABC learning design. They developed adapted ABC learning cards where the reverse side included specific UDL prompts, in addition to the usual example activities. For example:

  • An acquisition card could include the prompt “Will materials be available in a variety of formats (text, audio, and visual)? Will videos be captioned and transcribed?”
  • A production card could include the prompt “Are there multiple ways for learners to demonstrate their understanding? Can they choose between writing, presenting, or creating?”

By including these UDL considerations directly on the ABC cards, the design team ensured that accessibility and inclusivity were central to learning design conversations.

Adding UDL prompts to your learning cards is a fantastic way to help you design accessible learning sequences.

Applying ABC learning design: Some ideas for computing educators

In 2020, during the pandemic, the Computing at School (CAS) Research Working Group worked with classroom teachers to apply ABC learning design in their own contexts. 

Following some training, teachers analysed their existing classroom activities and then developed a range of suitable alternatives for remote learning, categorising them into low-tech, mid-tech, and high-tech options. 
The different activity options were then added to their own sets of ABC learning cards and used to help adapt lessons for remote teaching. You can read more about the project and view example cards on the CAS website.

The benefits of using ABC learning design

Potential benefits for educators:

  • Enables more rapid creation and delivery of high-quality content
  • Allows you to audit your current learning sequence and identify gaps that can be improved upon
  • Provides a shared, contextualised toolkit for curriculum design

Potential benefits for students:

  • Tailored, engaging, high-quality learning experiences

Want to hear more about ABC learning design?

If you’d like to find out more about ABC learning design, you can download our Quick Read for free.

Download the ABC learning design Pedagogy Quick Read

You can also listen to a thought-provoking discussion on the topic between James Robinson, Carrie Anne Philbin, Jane Waite, and Matthew Wimpenny-Smith in season 1, episode 6 of the Hello World podcast: Could curriculum design be as simple as ABC?

The post How to rapidly design and adapt quality learning experiences for your students appeared first on Raspberry Pi Foundation.

How to build young people’s agency through accessible learning

Post Syndicated from Sean Sayers original https://www.raspberrypi.org/blog/how-to-build-young-peoples-agency-through-accessible-learning/

We think computing or computer science (CS) needs to be accessible to all learners, and we know that teachers work hard towards this. Traditional CS approaches can lack flexibility, creating barriers to learning and excluding some young people. In today’s blog, we’re highlighting the ‘Universal design for learning’ (UDL) framework and how you can use it to make computing education more accessible to all your learners.

Children in the classroom learning Computer Science

We also share our new UDL-focused Pedagogy Quick Read, which you can download for free to:

  • Find practical tips for how to use the UDL framework and related approaches with your learners
  • Read a summary of the research behind the framework

Universal Design for Learning: Because one size does not fit all

Everyone is different and has their own way of learning. What works for one young person may not work for the next. So why should we expect learners to be taught the same material in the same way? 

Todd Rose, a contributor to the UDL framework, highlights the factors involved with a young person’s ability to engage and participate in learning. These include cognitive, social-emotional, family background and academic factors. He dispels the idea of an “average” learner, and instead suggests the concept of learner variability. 

Picture of our new UDL-focused Pedagogy Quick Read
The new Quick Read

As educators, it’s important to consider that students will likely be at different stages of understanding, and a one-size-fits-all approach isn’t suitable. The UDL framework avoids this mindset and provides teachers with structured guidelines to design accessible lessons from the beginning. 

What is the UDL framework?

The UDL framework encourages educators to provide flexibility for learners in three areas: 

  • Multiple means of engagement: The “why of learning”, which helps to pique students’ curiosity and motivates them to stay engaged
  • Multiple means of representation: The “what of learning”, which focuses on presenting information in different ways to make the content accessible
  • Multiple means of action and expression: The “how of learning”, which relates to different ways for students to access learning and express their understanding

How can I apply the UDL framework?

Two things are key while you are planning how to apply the UDL framework with your learners:

  • Try not to introduce all three areas at once to your practice. Instead, focus on one area of the framework at a time and reflect to identify where there might be gaps. Focus on these first and make changes one by one.
  • Consider how different approaches will work for different groups and individuals. Try to identify what works for your learners and vary or adapt your approach as necessary.

Applying UDL: Some ideas for teaching programming

Multiple means of engagement — show learners different reasons for engaging in programming. For example:

  • Solving real-life problems
  • Interest in technology or logical thinking
  • Creative expression

Multiple means of representation — teach programming concepts in multiple ways. For example:

  • Demonstrate through live coding
  • Write on a blackboard with a flowchart
  • Let learners label and assemble bits of paper into a ‘program’

Multiple means of action and expression — teach with accessibility in mind. For example:

  • Use tools appropriate for learners’ mouse and keyboard skills
  • Let learners demonstrate their understanding in different ways (e.g. verbally, by writing/drawing, by creating a program)

The UDL framework aligns closely with several key research-supported pedagogies that you can use for effective instruction in computational thinking and programming. For example, the pedagogy approach ‘Use-Modify-Create’ (UMC) can be paired with the UDL categories. The new Quick Read explores these connections in more detail.

Students in the classroom

The benefits of the UDL framework

Potential benefits for teachers:

  • The framework provides a clear structure for designing learning activities that appeal to and engage the widest set of learners
  • It can help you consider all the ways you might engage your learners and make CS lessons more accessible.
  • UDL encourages you to reflect on the different ways in which you might represent concepts and ideas
  • It can help you to build learner agency and independence in your students by offering them different ways to express their learning in CS topics. 

Potential benefits for learners:

  • The framework promotes a sense of ownership over their learning. Which can boost their motivation and resilience to sticking with difficult challenges. 
  • They will likely find content that resonates with them, leading to higher engagement and therefore learning.
  • They will be able to demonstrate their CS knowledge confidently and engage limitlessly in CS contexts.

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

Download the Quick Read 

Inclusive computer science: The wider context

We know there is a lack of representation within the field of CS. Our recent position paper ‘Why kids still need to learn to code in the age of AI’ and an episode of the  Hello World podcast, ‘How can we empower girls in computing’ touched on this. Both highlight why it’s important that learners from all backgrounds are empowered to contribute their perspectives and experiences and shape the future with computing.

Photo from the Hello World podcast, ‘How can we empower girls in computing
Guests and host during the recording of our ‘How can we empower girls in computing’ episode

“The reality is that access to the opportunities to learn about computer science, programming, and coding has remained deeply unequal, both within and between countries. That has helped create a technology sector that doesn’t reflect the broad diversity of human backgrounds, perspectives, and experiences. And we are all living with the consequences.” – Philip Colligan, Mark Griffiths, Veronica Cucuiat

“If we don’t have a diverse range of people designing and implementing that tech, then we are going to come across issues.” – Becky Patel, Tech She Can, Hello World podcast”

By embracing the principles of ‘Universal design for learning’ and similar approaches, we can create a more inclusive and equitable learning environment in computer science for everyone.

The post How to build young people’s agency through accessible learning appeared first on Raspberry Pi Foundation.

Pedagogy Quick Reads: turning abstract ideas into classroom practice

Post Syndicated from James Robinson original https://www.raspberrypi.org/blog/pedagogy-quick-reads-turning-abstract-ideas-into-classroom-practice/

What does outstanding computing education look like in the age of AI? We’ve just released a new series of Pedagogy Quick Reads exploring this vital question. Focusing on three aspects of AI in computing education, these short guides offer practical insights and new strategies for your classroom practice.

In a computing classroom, a smiling girl raises her hand.

Each Pedagogy Quick Read is designed to help educators explore, understand, and apply one area of research evidence.

You get:

  • An introduction to the topic or idea, putting it into context
  • A summary of the key concepts and takeaways for educators
  • Sections elaborating on each key concept and relevant research
  • A diagram presenting the same ideas in visual form
  • Links to referenced resources for further reading

Introducing our AI Pedagogy Quick Reads

Computational Thinking 2.0

This Quick Read explores how the concept of computational thinking is evolving, particularly in the context of AI. It offers guidance on how to teach computational thinking skills that are relevant to and enhanced by AI technologies.

“Without CT2.0, today’s learners will remain passive consumers rather than informed participants in a world increasingly shaped by data-driven AI technologies.”

Download

Anthropomorphism

As AI becomes widely used, it’s important to consider how students understand and view these technologies. This Quick Read discusses anthropomorphism (attributing human-like qualities to AI) and provides strategies for teaching about AI in a way that avoids common misconceptions.

“If young people see this technology as innately human-like, we run the risk of impacting their…sense of agency…safety…social connection…curiosity.”

Download

Feedback Literacy

Effective feedback is important for student learning, especially in a rapidly changing field like AI. This Quick Read examines how to develop “feedback literacy” in both educators and students, enabling them to give, receive, and use feedback more effectively.

“How do we ensure that all students get the most out of AI system-produced feedback? Feedback literacy is a theory-driven framework that can help…answer this question.”

Download

Browse our library of pedagogy resources

The new AI-themed reads join our bank of other Pedagogy Quick Reads, which cover a wide range of topics related to computing education. You can find these resources and more on our pedagogy page, all organised around our 12 pedagogy principles for computing education.

a teenage boy does coding during a computer science lesson.

Other resources 

As well as our Pedagogy Quick Reads, we also offer lots of other resources to support computing educators:

  • The Hello World Big Book of Computing Pedagogy is an in-depth guide to research-backed computing education pedagogy, covering a wide range of topics and offering practical advice for teachers.
  • The Hello World magazine and podcast feature insights from educators in computing education, exploring current research, best classroom practices, and innovative teaching strategies.
  • Our AI literacy programme, Experience AI, provides teachers with cutting-edge resources on AI and machine learning, based on proven pedagogical principles to support effective learning and teaching.

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