Tag Archives: computing education

Global Impact: Empowering young people in Kenya and South Africa

Post Syndicated from Vicky Fisher original https://www.raspberrypi.org/blog/global-impact-empowering-young-people-in-kenya-and-south-africa/

We work with mission-aligned educational organisations all over the world to support young people’s computing education. In 2023 we established four partnerships in Kenya and South Africa with organisations Coder:LevelUp, Blue Roof, Oasis Mathare, and Tech Kidz Africa, which support young people in underserved communities. Our shared goal is to support educators to establish and sustain extracurricular Code Clubs and CoderDojos in schools and community organisations. Here we share insights into the impact the partnerships are having.

A group of young people outside a school.

Evaluating the impact of the training 

In the partnerships we used a ‘train the trainer’ model, which focuses on equipping our partners with the knowledge and skills to train and support educators and learners. This meant that we trained a group of educators from each partner, enabling them to then run their own training sessions for other educators so they can set up coding clubs and run coding sessions. These coding sessions aim to increase young people’s skills and confidence in computing and programming.

We also conducted an evaluation of the impact of our work in these partnerships. We shared two surveys with educators (one shortly after they completed their initial training, a second for when they were running coding sessions), and another survey for young people to fill in during their coding sessions. In two of the partnerships, we also conducted interviews and focus groups with educators and young people. 

Although we received lots of valuable feedback, only a low proportion of participants responded to our surveys, so the data may not be representative of the experience of all participating educators. 

A group of young people coding on a laptop.

New opportunities to learn to code

Following our training, our partners themselves trained 332 educators across Kenya and South Africa to work directly in schools and communities running coding sessions. This led to the setup of nearly 250 Code Clubs and CoderDojos and additional coding sessions in schools and communities, reaching more than 11,500 young people.

As a result, access to coding and programming has increased in areas where this provision would otherwise not be available. One educator told us:

“We found it extremely beneficial, because a lot of our children come from areas in the community where they barely know how to read and write, let alone know how to use a computer… [It provides] the foundation, creating a fun way of approaching the computer as opposed to it being daunting.”

Curiosity, excitement and increased confidence

We found encouraging signs of the impact of this work on young people.

Nearly 90% of educators reported seeing an increase in young people’s computing skills, with over half of educators reporting that this increase was large. Over three quarters of young people who filled in our survey reported feeling confident in coding and computer programming.

The young people spoke enthusiastically about what they had learned and the programs they had created. They told us they felt inspired to keep learning, linking their interests to what they wanted to do in coding sessions. Interests included making dolls, games, cartoons, robots, cars, and stories. 

A young person points at a screen.

When we spoke with educators and young people, a key theme that emerged was the enthusiasm and curiosity of the young people to learn more. Educators described how motivated they felt by the excitement of the young people. Young people particularly enjoyed finding out the role of programming in the world around them, from understanding traffic lights to knowing more about the games they play on their phones.

One educator told us:

“…students who knew nothing about technology are getting empowered.” 

This confidence is particularly encouraging given that educators reported a low level of computer literacy among young people at the start of the coding sessions. One educator described how coding sessions provided an engaging hook to support teaching basic IT skills, such as mouse skills and computer-related terms, alongside coding. 

Addressing real-world problems

One educator gave an example of young people using what they are learning in their coding club to solve real-world problems, saying:

“It’s life-changing because some of those kids and the youths that you are teaching… they’re using them to automate things in their houses.” 

Many of these young people live in informal settlements where there are frequent fires, and have started using skills they learned in the coding sessions to automate things in their homes, reducing the risk of fires. For example, they are programming a device that controls fans so that they switch on when the temperature gets too high, and ways to switch appliances such as light bulbs on and off by clapping.

A young learner coding on a laptop.

Continuing to improve our support

From the gathered feedback, we also learned some useful lessons to help improve the quality of our offer and support to our partners. For example, educators faced challenges including lack of devices for young people, and low internet connectivity. As we continue to develop these partnerships, we will work with partners to make use of our unplugged activities that work offline, removing the barriers created by low connectivity.

We are continuing to develop the training we offer and making sure that educators are able to access our other training and resources. We are also using the feedback they have given us to consider where additional training and support may be needed. Future evaluations will further strengthen our evidence and provide us with the insights we need to continue developing our work and support more educators and young people.

Our thanks to our partners at Coder:LevelUp, Blue Roof, Oasis Mathare, and Tech Kidz Africa for sharing our mission to enable young people to realise their full potential through the power of computing and digital technologies. As we continue to build partnerships to support Code Clubs and CoderDojos across South Africa and Kenya, it is heartening to hear first-hand accounts of the positive impact this work has on young people.

If your organisation would like to partner with us to bring computing education to young people you support, please send us a message with the subject ‘Partnerships’.

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Insights into students’ attitudes to using AI tools in programming education

Post Syndicated from Katharine Childs original https://www.raspberrypi.org/blog/insights-into-students-attitudes-to-using-ai-tools-in-programming-education/

Educators around the world are grappling with the problem of whether to use artificial intelligence (AI) tools in the classroom. As more and more teachers start exploring the ways to use these tools for teaching and learning computing, there is an urgent need to understand the impact of their use to make sure they do not exacerbate the digital divide and leave some students behind.

A teenager learning computer science.

Sri Yash Tadimalla from the University of North Carolina and Dr Mary Lou Maher, Director of Research Community Initiatives at the Computing Research Association, are exploring how student identities affect their interaction with AI tools and their perceptions of the use of AI tools. They presented findings from two of their research projects in our March seminar.

How students interact with AI tools 

A common approach in research is to begin with a preliminary study involving a small group of participants in order to test a hypothesis, ways of collecting data from participants, and an intervention. Yash explained that this was the approach they took with a group of 25 undergraduate students on an introductory Java programming course. The research observed the students as they performed a set of programming tasks using an AI chatbot tool (ChatGPT) or an AI code generator tool (GitHub Copilot). 

The data analysis uncovered five emergent attitudes of students using AI tools to complete programming tasks: 

  • Highly confident students rely heavily on AI tools and are confident about the quality of the code generated by the tool without verifying it
  • Cautious students are careful in their use of AI tools and verify the accuracy of the code produced
  • Curious students are interested in exploring the capabilities of the AI tool and are likely to experiment with different prompts 
  • Frustrated students struggle with using the AI tool to complete the task and are likely to give up 
  • Innovative students use the AI tool in creative ways, for example to generate code for other programming tasks

Whether these attitudes are common for other and larger groups of students requires more research. However, these preliminary groupings may be useful for educators who want to understand their students and how to support them with targeted instructional techniques. For example, highly confident students may need encouragement to check the accuracy of AI-generated code, while frustrated students may need assistance to use the AI tools to complete programming tasks.

An intersectional approach to investigating student attitudes

Yash and Mary Lou explained that their next research study took an intersectional approach to student identity. Intersectionality is a way of exploring identity using more than one defining characteristic, such as ethnicity and gender, or education and class. Intersectional approaches acknowledge that a person’s experiences are shaped by the combination of their identity characteristics, which can sometimes confer multiple privileges or lead to multiple disadvantages.

A student in a computing classroom.

In the second research study, 50 undergraduate students participated in programming tasks and their approaches and attitudes were observed. The gathered data was analysed using intersectional groupings, such as:

  • Students who were from the first generation in their family to attend university and female
  • Students who were from an underrepresented ethnic group and female 

Although the researchers observed differences amongst the groups of students, there was not enough data to determine whether these differences were statistically significant.

Who thinks using AI tools should be considered cheating? 

Participating students were also asked about their views on using AI tools, such as “Did having AI help you in the process of programming?” and “Does your experience with using this AI tool motivate you to continue learning more about programming?”

The same intersectional approach was taken towards analysing students’ answers. One surprising finding stood out: when asked whether using AI tools to help with programming tasks should be considered cheating, students from more privileged backgrounds agreed that this was true, whilst students with less privilege disagreed and said it was not cheating.

This finding is only with a very small group of students at a single university, but Yash and Mary Lou called for other researchers to replicate this study with other groups of students to investigate further. 

You can watch the full seminar here:

Acknowledging differences to prevent deepening divides

As researchers and educators, we often hear that we should educate students about the importance of making AI ethical, fair, and accessible to everyone. However, simply hearing this message isn’t the same as truly believing it. If students’ identities influence how they view the use of AI tools, it could affect how they engage with these tools for learning. Without recognising these differences, we risk continuing to create wider and deeper digital divides. 

Join our next seminar

The focus of our ongoing seminar series is on teaching programming with or without AI. 

For our next seminar on Tuesday 16 April at 17:00 to 18:30 GMT, we’re joined by Brett A. Becker (University College Dublin), who will talk about how generative AI can be used effectively in secondary school programming education and how it can be leveraged so that students can be best prepared for continuing their education or beginning their careers. To take part in the seminar, click the button below to sign up, and we will send you information about how to join. We hope to see you there.

I want to join the next seminar

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

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New resource to help teachers make Computing culturally relevant

Post Syndicated from Claire Johnson original https://www.raspberrypi.org/blog/new-resource-to-help-teachers-make-computing-culturally-relevant/

Here at the Raspberry Pi Foundation, we believe that it’s important that our academic research has a practical application. An important area of research we are engaged in is broadening participation in computing education by investigating how the subject can be made more culturally relevant — we have published several studies in this area. 

Licensed under the Open Government Licence.

However, we know that busy teachers do not have time to keep abreast of all the latest research. This is where our Pedagogy Quick Reads come in. They show teachers how an area of current research either has been or could be applied in practice. 

Our new Pedagogy Quick Reads summarises the central tenets of culturally relevant pedagogy (the theory) and then lays out 10 areas of opportunity as concrete ways for you to put the theory into practice.

Download the Quick Read

Why is culturally relevant pedagogy necessary?

Computing remains an area where many groups of people are underrepresented, including those marginalised because of their gender, ethnicity, socio-economic background, additional educational needs, or age. For example, recent stats in the BCS’ Annual Diversity Report 2023 record that in the UK, the proportion of women working in tech was 20% in 2021, and Black women made up only 0.7% of tech specialists. Beyond gender and ethnicity, pupils who have fewer social and economic opportunities ‘don’t see Computing as a subject for somebody like them’, a recent report from Teach First found. 

In a computing classroom, a girl laughs at what she sees on the screen.

The fact that in the UK, 94% of girls and 79% of boys drop Computing at age 14 should be of particular concern for Computing educators. This last statistic makes it painfully clear that there is much work to be done to broaden the appeal of Computing in schools. One approach to make the subject more inclusive and attractive to young people is to make it more culturally relevant. 

As part of our research to help teachers effectively adapt their curriculum materials to make them culturally relevant and engaging for their learners, we’ve identified 10 areas of opportunity — areas where teachers can choose to take actions to bring the latest research on culturally relevant pedagogy into their classrooms, right here, right now. 

Applying the areas of opportunity in your classroom

The Pedagogy Quick Read gives teachers ideas for how they can use the areas of opportunity (AOs) to begin to review their own curriculum, teaching materials, and practices. We recommend picking one area initially, and focusing on that perhaps for a term. This helps you avoid being overwhelmed, and is particularly useful if you are trying to reach a particular group, for example, Year 9 girls, or low-attaining boys, or learners who lack confidence or motivation. 

Two learners do physical computing in the primary school classroom.

For example, one simple intervention is AO1 ‘Finding out more about our learners’. It’s all too easy for teachers to assume that they know what their students’ interests are. And getting to know your students can be especially tricky at secondary level, when teachers might only see a class once a fortnight or in a carousel. 

However, finding out about your learners can be easily achieved in an online survey homework task, set at the beginning of a new academic year or term or unit of work. Using their interests, along with considerations of their backgrounds, families, and identities as inputs in curriculum planning can have tangible benefits: students may begin to feel an increased sense of belonging when they see their interests or identities reflected in the material later used. 

How we’re using the AOs

The Quick Read presents two practical case studies of how we’ve used the 10 AO to adapt and assess different lesson materials to increase their relevance for learners. 

Case study 1: Teachers in UK primary school adapt resources

As we’ve shared before, we implemented culturally relevant pedagogy as part of UK primary school teachers’ professional development in a recent research project. The Quick Read provides details of how we supported teachers to use the AOs to adapt teaching material to make it more culturally relevant to learners in their own contexts. Links to the resources used to review 2 units of work, lesson by lesson, to adapt tasks, learning material, and outcomes are included in the Quick Read. 

A table laying out the process of adapting a computing lesson so it's culturally relevant.
Extract from the booklet used in a teacher professional development workshop to frame possible adaptations to lesson activities.

Case study 2: Reflecting on the adaption of resources for a vocational course for young adults in a Kenyan refugee camp

In a different project, we used the AOs to reflect on our adaptation of classroom materials from The Computing Curriculum, which we had designed for schools in England originally. Partnering with Amala Education, we adapted Computing Curriculum materials to create a 100-hour course for young adults at Kakuma refugee camp in Kenya who wanted to develop vocational digital literacy skills. 

The diagram below shows our ratings of the importance of applying each AO while adapting materials for this particular context. In this case, the most important areas for making adaptations were to make the context more culturally relevant, and to improve the materials’ accessibility in terms of readability and output formats (text, animation, video, etc.). 

Importance of the areas of opportunity to a course adaptation.

You can use this method of reflection as a way to evaluate your progress in addressing different AOs in a unit of work, across the materials for a whole year group, or even for your school’s whole approach. This may be useful for highlighting those areas which have, perhaps, been overlooked. 

Applying research to practice with the AOs

The ‘Areas of opportunity’ Pedagogy Quick Read aims to help teachers apply research to their practice by summarising current research and giving practical examples of evidence-based teaching interventions and resources they can use.

Two children code on laptops while an adult supports them.

The set of AOs was developed as part of a wider research project, and each one is itself research-informed. The Quick Read includes references to that research for everyone who wants to know more about culturally relevant pedagogy. This supporting evidence will be useful to teachers who want to address the topic of culturally relevant pedagogy with senior or subject leaders in their school, who often need to know that new initiatives are evidence-based.

Our goal for the Quick Read is to raise awareness of tried and tested pedagogies that increase accessibility and broaden the appeal of Computing education, so that all of our students can develop a sense of belonging and enjoyment of Computing.

Access the Quick Read PDF

Let us know if you have a story to tell about how you have applied one of the areas of opportunity in your classroom.

To date, our research in the field of culturally relevant pedagogy has been generously supported by funders including Cognizant and Google. We are very grateful to our partners for enabling us to learn more about how to make computing education inclusive for all.

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Our new theory of change

Post Syndicated from Ben Durbin original https://www.raspberrypi.org/blog/theory-of-change-2024/

One of the Raspberry Pi Foundation’s core values is our focus on impact. This means that we are committed to learning from the best available evidence, and to being rigorous and transparent about the difference we’re making.

A smiling girl holding a robot buggy in her lap

Like many charities, an important part of our approach to achieving and measuring our impact is our theory of change. We are excited to launch a newly refreshed theory of change that reflects our mission and strategy to ensure that young people can realise their full potential through the power of computing and digital technologies.

Read our theory of change

What is a theory of change?

A theory of change describes the difference an organisation aims to make in the world, the actions it takes to achieve this, and the underlying assumptions about how its actions will create change.

Two learners sharing a laptop in a coding session.

It’s like a good cake recipe. It describes the ingredients and tools that are required, how these are combined, and what the results should be. But a theory of change goes further: it also addresses why you need the cake in the first place, and the reasons why the recipe will produce such a good cake if you follow it correctly!

What is the change we want to make?

Our theory of change begins with a statement of the problem that needs solving: too many young people are missing out on the enormous opportunities from digital technologies, and access to opportunities to learn depends too much on who you are and where you were born.

We want to see a world where young people can take advantage of the opportunities that computers and digital technologies offer to transform their own lives and communities, to contribute to society, and to help address the world’s challenges.

Learners in a computing classroom.

To help us empower young people to do this, we have identified three broad sets of outcomes that we should target, measure, and hold ourselves accountable for. These map roughly to the COM-B model of behaviour change. This model suggests that for change to be achieved, people need a combination of capabilities, opportunities, and motivation.

Our identified outcomes are that we support young people to:

  1. Build knowledge and skills in computing
  2. Understand the opportunities and risks associated with new technologies
  3. Develop the mindsets to confidently engage with technological change

How do we make a difference?

We work at multiple levels throughout education systems and society, which together will achieve deep and long-lasting change for young people. We design learning experiences and initiatives that are fun and engaging, including hundreds of free coding and computing projects, the Coolest Projects showcase for young tech creators, and the European Astro Pi Challenge, which gives young people the chance to run their computer programs in space.

Three learners working at laptops.

We also support teachers, youth workers, volunteers, and parents to develop their skills and knowledge, and equip them to inspire young people and help them learn. For example, The Computing Curriculum provides a complete bank of free lesson plans and other resources, and Experience AI is our educational programme that includes everything teachers need to deliver lessons on artificial intelligence and machine learning in secondary schools.

Finally, we aim to elevate the state of computing education globally by advocating for policy and systems change, and undertaking our own original research to deepen our understanding of how young people learn about computing.

How will we use our theory of change?

Our theory of change is an important part of our approach to evaluating the impact of our resources and programmes, and it informs all our monitoring and evaluation plans. These plans identify the questions we want to answer, key metrics to monitor, and the data sources we use to understand the impact we’re having and to gather feedback to improve our impact in future.

An educator teaches students to create with technology.

The theory of change also informs a shared outcomes framework that we are applying consistently across all of our products. This framework supports planning and helps keep us focused as we consider new opportunities to further our mission.

A final role our theory of change plays is to help communicate our mission to other stakeholders, and explain how we can work with our partners and communities to achieve change.

You can read our new theory of change here and if you have any questions or feedback on it, please do get in touch.

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Supporting Computing in England through our renewed partnership with Oak National Academy

Post Syndicated from Rik Cross original https://www.raspberrypi.org/blog/supporting-computing-in-england-with-oak-national-academy/

We are pleased to announce that we are renewing our partnership with Oak National Academy in England to provide an updated high-quality Computing curriculum and lesson materials for Key Stages 1 to 4.

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

New curriculum and materials for the classroom

In 2021 we partnered with Oak National Academy to offer content for schools in England that supported young people to learn Computing at home while schools were closed as a result of the coronavirus pandemic.

A teacher and learner at a laptop doing coding.

In our renewed partnership, we will create new and updated materials for primary and secondary teachers to use in the classroom. These classroom units will be available for free on the Oak platform and will include everything a teacher needs to deliver engaging lessons, including slide decks, worksheets, quizzes, and accompanying videos for over 550 lessons. The units will cover both the general national Computing curriculum and the Computer Science GCSE, supporting teachers to provide a high-quality Computing offering to all students aged 5 to 16.

Secondary school age learners in a computing classroom.

These new resources will update the very successful Computing Curriculum and will be rigorously tested by a Computing subject expert group.

“I am delighted that we are continuing our partnership with Oak National Academy to support all teachers in England with world-leading resources for teaching Computing and Computer Science. This means that all teachers in England will have access to free, rigorous and tested classroom resources that they can adapt to suit their context and students.” – Philip Colligan, CEO

All our materials on the Oak platform will be free and openly available, and can be accessed by educators worldwide.

Research-informed, time-saving, and adaptable resources

As we did with The Computing Curriculum, we’ll design these teaching resources to model best practice, and they will be informed by leading research into pedagogy and computing education, as well as by user testing and feedback. 

Young learners at computers in a classroom.

The materials will bring teachers the added benefit of saving valuable time, and schools can choose to adapt and use the resources in the way that works best for their students

Supporting schools in England and worldwide

We have already started work and will begin releasing units of lessons in autumn 2024. All units across Key Stages 1 to 4 will be available by autumn 2025.

A teenager learning computer science.

We’re excited to continue our partnership with Oak National Academy to provide support to teachers and students in England. 

And as always, our comprehensive classroom resources can be downloaded for free, by anyone in the world, from our website.

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How we’re creating more impact with Ada Computer Science

Post Syndicated from Ben Durbin original https://www.raspberrypi.org/blog/how-were-creating-more-impact-with-ada-computer-science/

We offer Ada Computer Science as a platform to support educators and learners alike. But we don’t take its usefulness for granted: as part of our commitment to impact, we regularly gather user feedback and evaluate all of our products, and Ada is no exception. In this blog, we share some of the feedback we’ve gathered from surveys and interviews with the people using Ada.

A secondary school age learner in a computing classroom.

What’s new on Ada?

Ada Computer Science is our online learning platform designed for teachers, students, and anyone interested in learning about computer science. If you’re teaching or studying a computer science qualification at school, you can use Ada Computer Science for classwork, homework, and revision. 

Launched last year as a partnership between us and the University of Cambridge, Ada’s comprehensive resources cover topics like algorithms, data structures, computational thinking, and cybersecurity. It also includes 1,000 self-marking questions, which both teachers and students can use to assess their knowledge and understanding. 

Throughout 2023, we continued to develop the support Ada offers. For example, we: 

  • Added over 100 new questions
  • Expanded code specimens to cover Java and Visual Basic as well as Python and C#
  • Added an integrated way of learning about databases through writing and executing SQL
  • Incorporated a beta version of an embedded Python editor with the ability to run code and compare the output with correct solutions 

A few weeks ago we launched two all-new topics about artificial intelligence (AI) and machine learning.

So far, all the content on Ada Computer Science is mapped to GCSE and A level exam boards in England, and we’ve just released new resources for the Scottish Qualification Authority’s Computer Systems area of study to support students in Scotland with their National 5 and Higher qualifications.

Who is using Ada?

Ada is being used by a wide variety of users, from at least 127 countries all across the globe. Countries where Ada is most popular include the UK, US, Canada, Australia, Brazil, India, China, Nigeria, Ghana, Kenya, China, Myanmar, and Indonesia.

Children in a Code Club in India.

Just over half of students using Ada are completing work set by their teacher. However, there are also substantial numbers of young people benefitting from using Ada for their own independent learning. So far, over half a million question attempts have been made on the platform.

How are people using Ada?

Students use Ada for a wide variety of purposes. The most common response in our survey was for revision, but students also use it to complete work set by teachers, to learn new concepts, and to check their understanding of computer science concepts.

Teachers also use Ada for a combination of their own learning, in the classroom with their students, and for setting work outside of lessons. They told us that they value Ada as a source of pre-made questions.

“I like having a bank of questions as a teacher. It’s tiring to create more. I like that I can use the finder and create questions very quickly.” — Computer science teacher, A level

“I like the structure of how it [Ada] is put together. [Resources] are really easy to find and being able to sort by exam board makes it really useful because… at A level there is a huge difference between exam boards.” — GCSE and A level teacher

What feedback are people giving about Ada?

Students and teachers alike were very positive about the quality and usefulness of Ada Computer Science. Overall, 89% of students responding to our survey agreed that Ada is useful for helping them to learn about computer science, and 93% of teachers agreed that it is high quality.

“The impact for me was just having a resource that I felt I always could trust.” — Head of Computer Science

A graph showing that students and teachers consider Ada Computer Science to be useful and high quality.

Most teachers also reported that using Ada reduces their workload, saving an average of 3 hours per week.

“[Quizzes] are the most useful because it’s the biggest time saving…especially having them nicely self-marked as well.” — GCSE and A level computer science teacher

Even more encouragingly, Ada users report a positive impact on their knowledge, skills, and attitudes to computer science. Teachers report that, as a result of using Ada, their computer science subject knowledge and their confidence in teaching has increased, and report similar benefits for their students.

“They can easily…recap and see how they’ve been getting on with the different topic areas.” — GCSE and A level computer science teacher

“I see they’re answering the questions and learning things without really realising it, which is quite nice.” — GCSE and A level computer science teacher

How do we use people’s feedback to improve the platform?

Our content team is made up of experienced computer science teachers, and we’re always updating the site in response to feedback from the teachers and students who use our resources. We receive feedback through support tickets, and we have a monthly meeting where we comb through every wrong answer that students entered to help us identify new misconceptions. We then use all of this to improve the content, and the feedback we give students on the platform.

A computer science teacher sits with students at computers in a classroom.

We’d love to hear from you

We’ll be conducting another round of surveys later this year, so when you see the link, please fill in the form. In the meantime, if you have any feedback or suggestions for improvements, please get in touch.

And if you’ve not signed up to Ada yet as a teacher or student, you can take a look right now over at adacomputerscience.org

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Using an AI code generator with school-age beginner programmers

Post Syndicated from Bobby Whyte original https://www.raspberrypi.org/blog/using-an-ai-code-generator-with-school-age-beginner-programmers/

AI models for general-purpose programming, such as OpenAI Codex, which powers the AI pair programming tool GitHub Copilot, have the potential to significantly impact how we teach and learn programming. 

Learner in a computing classroom.

The basis of these tools is a ‘natural language to code’ approach, also called natural language programming. This allows users to generate code using a simple text-based prompt, such as “Write a simple Python script for a number guessing game”. Programming-specific AI models are trained on vast quantities of text data, including GitHub repositories, to enable users to quickly solve coding problems using natural language. 

As a computing educator, you might ask what the potential is for using these tools in your classroom. In our latest research seminar, Majeed Kazemitabaar (University of Toronto) shared his work in developing AI-assisted coding tools to support students during Python programming tasks.

Evaluating the benefits of natural language programming

Majeed argued that natural language programming can enable students to focus on the problem-solving aspects of computing, and support them in fixing and debugging their code. However, he cautioned that students might become overdependent on the use of ‘AI assistants’ and that they might not understand what code is being outputted. Nonetheless, Majeed and colleagues were interested in exploring the impact of these code generators on students who are starting to learn programming.

Using AI code generators to support novice programmers

In one study, the team Majeed works in investigated whether students’ task and learning performance was affected by an AI code generator. They split 69 students (aged 10–17) into two groups: one group used a code generator in an environment, Coding Steps, that enabled log data to be captured, and the other group did not use the code generator.

A group of male students at the Coding Academy in Telangana.

Learners who used the code generator completed significantly more authoring tasks — where students manually write all of the code — and spent less time completing them, as well as generating significantly more correct solutions. In multiple choice questions and modifying tasks — where students were asked to modify a working program — students performed similarly whether they had access to the code generator or not. 

A test was administered a week later to check the groups’ performance, and both groups did similarly well. However, the ‘code generator’ group made significantly more errors in authoring tasks where no starter code was given. 

Majeed’s team concluded that using the code generator significantly increased the completion rate of tasks and student performance (i.e. correctness) when authoring code, and that using code generators did not lead to decreased performance when manually modifying code. 

Finally, students in the code generator group reported feeling less stressed and more eager to continue programming at the end of the study.

Student perceptions when (not) using AI code generators

Understanding how novices use AI code generators

In a related study, Majeed and his colleagues investigated how novice programmers used the code generator and whether this usage impacted their learning. Working with data from 33 learners (aged 11–17), they analysed 45 tasks completed by students to understand:

  1. The context in which the code generator was used
  2. What learners asked for
  3. How prompts were written
  4. The nature of the outputted code
  5. How learners used the outputted code 

Their analysis found that students used the code generator for the majority of task attempts (74% of cases) with far fewer tasks attempted without the code generator (26%). Of the task attempts made using the code generator, 61% involved a single prompt while only 8% involved decomposition of the task into multiple prompts for the code generator to solve subgoals; 25% used a hybrid approach — that is, some subgoal solutions being AI-generated and others manually written.

In a comparison of students against their post-test evaluation scores, there were positive though not statistically significant trends for students who used a hybrid approach (see the image below). Conversely, negative though not statistically significant trends were found for students who used a single prompt approach.

A positive correlation between hybrid programming and post-test scores

Though not statistically significant, these results suggest that the students who actively engaged with tasks — i.e. generating some subgoal solutions, manually writing others, and debugging their own written code — performed better in coding tasks.

Majeed concluded that while the data showed evidence of self-regulation, such as students writing code manually or adding to AI-generated code, students frequently used the output from single prompts in their solutions, indicating an over-reliance on the output of AI code generators.

He suggested that teachers should support novice programmers to write better quality prompts to produce better code.  

If you want to learn more, you can watch Majeed’s seminar:

You can read more about Majeed’s work on his personal website. You can also download and use the code generator Coding Steps yourself.

Join our next seminar

The focus of our ongoing seminar series is on teaching programming with or without AI. 

For our next seminar on Tuesday 16 April at 17:00–18:30 GMT, we’re joined by Brett Becker (University College Dublin), who will discuss how generative AI may be effectively utilised in secondary school programming education and how it can be leveraged so that students can be best prepared for whatever lies ahead. To take part in the seminar, click the button below to sign up, and we will send you information about joining. We hope to see you there.

I want to join the next seminar

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

The post Using an AI code generator with school-age beginner programmers appeared first on Raspberry Pi Foundation.

Season 6 of the Hello World podcast is here

Post Syndicated from James Robinson original https://www.raspberrypi.org/blog/hello-world-podcast-season-6-computing-education/

Through the Hello World podcast, we help to connect computing educators around the world and share their experiences. In each episode, we expand on a topic from a recent Hello World magazine issue. After 5 seasons, and a break last year, we are back with season 6 today.

Hello World logo.

Episode 1: Do kids still need to learn how to code?

In the recent ‘Teaching & AI’ issue of Hello World, our CEO Philip Colligan discussed what AI means for computing education, including for learning to program. And our first new podcast episode is all about this question, which every computing educator has probably thought about at least once in recent months: Do kids still need to learn how to code?

Joining my co-host Veronica and me are two computing educators: Pete Dring, Head of Computing at Fulford School in York, and Chris Coetzee, a computer science teacher for 24 years and currently a PhD student in Computer Science Education at Abertay Dundee. Given the recent developments in AI-based code generators, we talk about whether such tools will remove our learners’ need to learn to code or simply change what coding, and learning to code, looks like*.

What’s coming up in future episodes?

New episode of season 6 will come out every 2 weeks. In each episode we explore computing, coding, and digital making education by delving into an exciting topic together with our guests: experts, practitioners, and other members of the Hello World community.

Also in season 6, we’ll explore:

The role of computing communities

We discuss the value and importance of being connected to other computing educators through the many different teaching communities that exist around the world. What makes effective communities, and how do we build and sustain them?

A group of students and a teacher at the Coding Academy in Telangana.

Why is understanding cybersecurity so important?

From classroom lessons to challenges and competitions, there are lots of opportunities for learners to discover cybersecurity. There are also many pitfalls where learners’ online activities put them at risk of breaking the law. We discuss some of these pitfalls along with the many career opportunities in cybersecurity.

How to develop as a computing educator?

What is involved in becoming an effective computing educator? What knowledge, skills, and behaviours are needed, and how do we go about developing them? We sit down with teacher trainers and trainees to explore this topic.

Two learners and a teacher in a physical computing lesson.

What is the state of computing education and where is it heading?

Computing education has come a long way in the last decade in terms of practice and policy, as well as research. Together with our guests we discuss where computing education is today around the world, and we consider the lessons we can learn and the challenges ahead

What is the role of AI in your classroom?

AI continues to be a disruptive technology in many spaces, and the classroom is no exception. We hear examples of practices and approaches being explored by teachers in the classroom.

If you’ve not listened to the Hello World podcast yet, there are 5 whole seasons for you to discover. We talk about everything from ecology and quantum computing to philosophy, ethics, and inclusion, and our conversations always focus on the practicalities of teaching in the classroom.

In our latest issue of Hello World, we feature authors from over 20 countries.

Many of our podcast guests are Hello World authors, so if you’re an educator who wants to share your insights into how to teach young people about digital technology, please let us know. Your words could end up in the pages as well as on the airwaves of Hello World.

You’ll find the upcoming Hello World season and past episodes on your favourite podcast platform, including YouTube now, where you can also subscribe to never miss an episode. Alternatively, you can listen here via your browser.

Listen on Spotify
Listen on Apple Podcasts
Listen on Amazon Music
Listen on Podcast Addict
RSS feed

* If you want to dive into the newest research on programming education with and without AI, check out our current seminar series.

The post Season 6 of the Hello World podcast is here appeared first on Raspberry Pi Foundation.

Hello World #23 out now: Global exchange of computing education ideas

Post Syndicated from Meg Wang original https://www.raspberrypi.org/blog/hello-world-23-global-computing-education-ideas/

How is computing taught around the globe? Our brand-new, free issue of Hello World, out today, paints a picture for you. It features stories from over 20 countries, where educators, researchers, and volunteers share their work and their personal challenges and joys in bringing computing education to their part of the world.

The Hello World Global Exchange magazine cover on a plain background.

Global exchange in a worldwide community

In Hello World issue 23, you’ll hear about countries where computing is an official school subject and how it was set up that way, and you’ll hear about countries that are newer to computing education and working to fast-track their students’ learning.

  • Ethel Tshukudu’s article on her research using the CAPE framework is a fascinating comparison of computer science education in four African countries
  • Iliana Ramirez describes how volunteers are at the heart of Ciberistas, a technology training programme for young people in Mexico
  • Matthew Griffin’s article highlights how computing education works in Canada, a large country with two official languages
  • Dana Rensi’s article about a solar-powered Raspberry Pi computing lab in the middle of the Peruvian rainforest will surprise and delight you
  • Randal Rousseau, a librarian in Cape Town, South Africa, shares how he teaches children to code through unplugged activities

And there is lots more for you to discover in issue 23.

Download your free digital copy

Sue Sentance, director of the Raspberry Pi Computing Education Research Centre at the University of Cambridge, says in her article:

“Our own experience of implementing computing education in England since 2014 has shown the importance of teachers supporting each other, and how various networks … are instrumental in bringing computing teachers together to share knowledge and experiences. With so many countries introducing computing education, and teachers around the globe facing similar challenges, maybe we need to extend this to a global teacher network, where teachers and policymakers can share good practice and learn from each other. “

We aim for Hello World magazine to be one of the places where this sharing, exchange, and learning can take place. Subscribe for free to never miss an issue, and find out how you can write for the magazine.

Download Hello World issue 23 for free

Research highlights the importance of computing education to young people’s futures, whether or not they pursue a degree or career in the area. From teaching computing in schools where the electricity cuts out, to incorporating artificial intelligence into curricula in different countries, and to teaming up with local governments when there isn’t a national computing curriculum, educators are doing wonderful things around the globe to make sure the young people they support have the opportunity to learn. Read their stories today.

Also in issue 23:

  • Research on culturally adapted resources 
  • How community building enhances computing education
  • Tips for hosting a STEM event in school

And much, much more.

Download issue 23 now

Send us a message or tag us on social media to let us know which articles have made you think, and most importantly, which will help you with your teaching. And to hear monthly news about Hello World and the whole Raspberry Pi Foundation, sign up to the Hello World newsletter.

The post Hello World #23 out now: Global exchange of computing education ideas appeared first on Raspberry Pi Foundation.

Supporting learners with programming tasks through AI-generated Parson’s Problems

Post Syndicated from Veronica Cucuiat original https://www.raspberrypi.org/blog/supporting-learners-with-programming-tasks-through-ai-generated-parsons-problems/

The use of generative AI tools (e.g. ChatGPT) in education is now common among young people (see data from the UK’s Ofcom regulator). As a computing educator or researcher, you might wonder what impact generative AI tools will have on how young people learn programming. In our latest research seminar, Barbara Ericson and Xinying Hou (University of Michigan) shared insights into this topic. They presented recent studies with university student participants on using generative AI tools based on large language models (LLMs) during programming tasks. 

A girl in a university computing classroom.

Using Parson’s Problems to scaffold student code-writing tasks

Barbara and Xinying started their seminar with an overview of their earlier research into using Parson’s Problems to scaffold university students as they learn to program. Parson’s Problems (PPs) are a type of code completion problem where learners are given all the correct code to solve the coding task, but the individual lines are broken up into blocks and shown in the wrong order (Parsons and Haden, 2006). Distractor blocks, which are incorrect versions of some or all of the lines of code (i.e. versions with syntax or semantic errors), can also be included. This means to solve a PP, learners need to select the correct blocks as well as place them in the correct order.

A presentation slide defining Parson's Problems.

In one study, the research team asked whether PPs could support university students who are struggling to complete write-code tasks. In the tasks, the 11 study participants had the option to generate a PP when they encountered a challenge trying to write code from scratch, in order to help them arrive at the complete code solution. The PPs acted as scaffolding for participants who got stuck trying to write code. Solutions used in the generated PPs were derived from past student solutions collected during previous university courses. The study had promising results: participants said the PPs were helpful in completing the write-code problems, and 6 participants stated that the PPs lowered the difficulty of the problem and speeded up the problem-solving process, reducing their debugging time. Additionally, participants said that the PPs prompted them to think more deeply.

A young person codes at a Raspberry Pi computer.

This study provided further evidence that PPs can be useful in supporting students and keeping them engaged when writing code. However, some participants still had difficulty arriving at the correct code solution, even when prompted with a PP as support. The research team thinks that a possible reason for this could be that only one solution was given to the PP, the same one for all participants. Therefore, participants with a different approach in mind would likely have experienced a higher cognitive demand and would not have found that particular PP useful.

An example of a coding interface presenting adaptive Parson's Problems.

Supporting students with varying self-efficacy using PPs

To understand the impact of using PPs with different learners, the team then undertook a follow-up study asking whether PPs could specifically support students with lower computer science self-efficacy. The results show that study participants with low self-efficacy who were scaffolded with PPs support showed significantly higher practice performance and higher problem-solving efficiency compared to participants who had no scaffolding. These findings provide evidence that PPs can create a more supportive environment, particularly for students who have lower self-efficacy or difficulty solving code writing problems. Another finding was that participants with low self-efficacy were more likely to completely solve the PPs, whereas participants with higher self-efficacy only scanned or partly solved the PPs, indicating that scaffolding in the form of PPs may be redundant for some students.

Secondary school age learners in a computing classroom.

These two studies highlighted instances where PPs are more or less relevant depending on a student’s level of expertise or self-efficacy. In addition, the best PP to solve may differ from one student to another, and so having the same PP for all students to solve may be a limitation. This prompted the team to conduct their most recent study to ask how large language models (LLMs) can be leveraged to support students in code-writing practice without hindering their learning.

Generating personalised PPs using AI tools

This recent third study focused on the development of CodeTailor, a tool that uses LLMs to generate and evaluate code solutions before generating personalised PPs to scaffold students writing code. Students are encouraged to engage actively with solving problems as, unlike other AI-assisted coding tools that merely output a correct code correct solution, students must actively construct solutions using personalised PPs. The researchers were interested in whether CodeTailor could better support students to actively engage in code-writing.

An example of the CodeTailor interface presenting adaptive Parson's Problems.

In a study with 18 undergraduate students, they found that CodeTailor could generate correct solutions based on students’ incorrect code. The CodeTailor-generated solutions were more closely aligned with students’ incorrect code than common previous student solutions were. The researchers also found that most participants (88%) preferred CodeTailor to other AI-assisted coding tools when engaging with code-writing tasks. As the correct solution in CodeTailor is generated based on individual students’ existing strategy, this boosted students’ confidence in their current ideas and progress during their practice. However, some students still reported challenges around solution comprehension, potentially due to CodeTailor not providing sufficient explanation for the details in the individual code blocks of the solution to the PP. The researchers argue that text explanations could help students fully understand a program’s components, objectives, and structure. 

In future studies, the team is keen to evaluate a design of CodeTailor that generates multiple levels of natural language explanations, i.e. provides personalised explanations accompanying the PPs. They also aim to investigate the use of LLM-based AI tools to generate a self-reflection question structure that students can fill in to extend their reasoning about the solution to the PP.

Barbara and Xinying’s seminar is available to watch here: 

Find examples of PPs embedded in free interactive ebooks that Barbara and her team have developed over the years, including CSAwesome and Python for Everybody. You can also read more about the CodeTailor platform in Barbara and Xinying’s paper.

Join our next seminar

The focus of our ongoing seminar series is on teaching programming with or without AI. 

For our next seminar on Tuesday 12 March at 17:00–18:30 GMT, we’re joined by Yash Tadimalla and Prof. Mary Lou Maher (University of North Carolina at Charlotte). The two of them will share further insights into the impact of AI tools on the student experience in programming courses. To take part in the seminar, click the button below to sign up, and we will send you information about joining. We hope to see you there.

I want to join the next seminar

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

The post Supporting learners with programming tasks through AI-generated Parson’s Problems appeared first on Raspberry Pi Foundation.

Our T Level resources to support vocational education in England

Post Syndicated from Jan Ander original https://www.raspberrypi.org/blog/t-level-resources-support-vocational-education-england/

You can now access classroom resources created by us for the T Level in Digital Production, Design and Development. T Levels are a type of vocational qualification young people in England can gain after leaving school, and we are pleased to be able to support T Level teachers and students.

A teenager learning computer science.

With our new resources, we aim to empower more young people to develop their digital skills and confidence while studying, meaning they can access more jobs and opportunities for further study once they finish their T Levels.

We worked collaboratively with the Gatsby Charitable Foundation on this pilot project as part of their Technical Education Networks Programme, the first time that we have created classroom resources for post-16 vocational education.

Post-16 vocational training and T Levels

T Levels are Technical Levels, 2-year courses for 16- to 18-year-old school leavers. Launched in England in September 2020, T Levels cover a range of subjects and have been developed in collaboration with employers, education providers, and other organisations. The aim is for T Levels to specifically prepare young people for entry into skilled employment, an apprenticeship, or related technical study in further or higher education.

A group of young people in a lecture hall.

For us, this T Level pilot project follows on from work we did in 2022 to learn more about post-16 vocational training and identify gaps where we could make a difference. 

Something interesting we found was the relatively low number of school-age young people who started apprenticeships in the UK in 2019/20. For example, a 2021 Worldskills UK report stated that only 18% of apprentices were young people aged 19 and under. 39% were aged 19-24, and the remaining 43% were people aged 25 and over.

To hear from young people about their thoughts directly, we spoke to a group of year 10 students (ages 14 to 15) at Gladesmore School in Tottenham. Two thirds of these students said that digital skills were ‘very important’ to them, and that they would consider applying for a digital apprenticeship or T Level. When we asked them why, one of the key reasons they gave was the opportunity to work and earn money, rather than moving into further study in higher education and paying tuition fees. One student’s answer was for example, “It’s a good way to learn new skills while getting paid, and also gives effective work experience.”

T Level curriculum materials and project brief

To support teachers in delivering the Digital Production, Design and Development T Level qualification, we created a new set of resources: curriculum materials as well a project brief with examples to support the Occupational Specialism component of the qualification. 

A girl in a university computing classroom.

The curriculum materials on the topic ‘Digital environments’ cover content related to computer systems including hardware, software, networks, and cloud environments. They are designed for teachers to use in the classroom and consist of a complete unit of work: lesson plans, slide decks, activities, a progression chart, and assessment materials. The materials are designed in line with our computing content framework and pedagogy principles, on which the whole of our Computing Curriculum is based.

The project brief is a real-world scenario related to our work and gives students the opportunity to problem-solve as though they are working in an industry job.

Access the T Level resources

The T Level project brief materials are available for download now, with the T Level classroom materials coming in the next few weeks.

We hope T Level teachers and students find the resources useful and interesting — if you’re using them, please let us know your thoughts and feedback.

Our thanks to the Gatsby Foundation for collaborating with us on this work to empower more young people to fulfil their potential through the power of computing and digital technologies.

The post Our T Level resources to support vocational education in England appeared first on Raspberry Pi Foundation.

Grounded cognition: physical activities and learning computing

Post Syndicated from Bonnie Sheppard original https://www.raspberrypi.org/blog/grounded-cognition/

Everyone who has taught children before will know the excited gleam in their eyes when the lessons include something to interact with physically. Whether it’s printed and painstakingly laminated flashcards, laser-cut models, or robots, learners’ motivation to engage with the topic will increase along with the noise levels in the classroom.

Two learners do physical computing in the primary school classroom.

However, these hands-on activities are often seen as merely a technique to raise interest, or a nice extra project for children to do before the ‘actual learning’ can begin. But what if this is the wrong way to think about this type of activity? 

How do children learn?

In our 2023 online research seminar series, focused on computing education for primary-aged (K–5) learners, we delved into the most recent research aimed at enhancing learning experiences for students in the earliest stages of education. From a deep dive into teaching variables to exploring the integration of computational thinking, our series has looked at the most effective ways to engage young minds in the subject of computing.

An adult on a plain background.

It’s only fitting that in our final seminar in the series, Anaclara Gerosa from the University of Glasgow tackled one of the most fundamental questions in education: how do children actually learn? Beyond the conventional methods, emerging research has been shedding light on a fascinating approach — the concept of grounded cognition. This theory suggests that children don’t merely passively absorb knowledge; they physically interact with it, quite literally ‘grasping’ concepts in the process.

Grounded cognition, also known in variations as embodied and situated cognition, offers a new perspective on how we absorb and process information. At its core, this theory suggests that all cognitive processes, including language and thought, are rooted in the body’s dynamic interactions with the environment. This notion challenges the conventional view of learning as a purely cognitive activity and highlights the impact of action and simulation.

A group of learners do physical computing in the primary school classroom.

There is evidence from many studies in psychology and pedagogy that using hands-on activities can enhance comprehension and abstraction. For instance, finger counting has been found to be essential in understanding numerical systems and mathematical concepts. A recent study in this field has shown that children who are taught basic computing concepts with unplugged methods can grasp abstract ideas from as young as 3. There is therefore an urgent need to understand exactly how we could use grounded cognition methods to teach children computing — which is arguably one of the most abstract subjects in formal education.

A recent study in this field has shown that children who are taught basic computing concepts with unplugged methods can grasp abstract ideas from as young as 3.

A new framework for teaching computing

Anaclara is part of a group of researchers at the University of Glasgow who are currently developing a new approach to structuring computing education. Their EIFFEL (Enacted Instrumented Formal Framework for Early Learning in Computing) model suggests a progression from enacted to formal activities.

Following this model, in the early years of computing education, learners would primarily engage with activities that allow them to work with tangible 3D objects or manipulate intangible objects, for instance in Scratch. Increasingly, students will be able to perform actions in an instrumented or virtual environment which will require the knowledge of abstract symbols but will not yet require the knowledge of programming languages. Eventually, students will have developed the knowledge and skills to engage in fully formal environments, such as writing advanced code.

A graph illustrating the EIFFEL model for early computing.

In a recent literature review, Anaclara and her colleagues looked at existing research into using grounded cognition theory in computing education. Although several studies report the use of grounded approaches, for instance by using block-based programming, robots, toys, or construction kits, the focus is generally on looking at how concrete objects can be used in unplugged activities due to specific contexts, such as a limited availability of computing devices.

The next steps in this area are looking at how activities that specifically follow the EIFFEL framework can enhance children’s learning. 

You can watch Anaclara’s seminar here: 

You can also access the presentation slides here.

Try grounded activities in your classroom

Research into grounded cognition activities in computer science is ongoing, but we encourage you to try incorporating more hands-on activities when teaching younger learners and observing the effects yourself. Here are a few ideas on how to get started:

Join us at our next seminar

In 2024, we are exploring different ways to teach and learn programming, with and without AI tools. In our next seminar, on 13 February at 17:00 GMT, Majeed Kazemi from the University of Toronto will be joining us to discuss whether AI-powered code generators can help K–12 students learn to program in Python. All of our online seminars are free and open to everyone. Sign up and we’ll send you the link to join on the day.

I want to sign up to join

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Integrating computational thinking into primary teaching

Post Syndicated from Veronica Cucuiat original https://www.raspberrypi.org/blog/integrating-computational-thinking-into-primary-teaching/

“Computational thinking is really about thinking, and sometimes about computing.” – Aman Yadav, Michigan State University

Young people in a coding lesson.

Computational thinking is a vital skill if you want to use a computer to solve problems that matter to you. That’s why we consider computational thinking (CT) carefully when creating learning resources here at the Raspberry Pi Foundation. However, educators are increasingly realising that CT skills don’t just apply to writing computer programs, and that CT is a fundamental approach to problem-solving that can be extended into other subject areas. To discuss how CT can be integrated beyond the computing classroom and help introduce the fundamentals of computing to primary school learners, we invited Dr Aman Yadav from Michigan State University to deliver the penultimate presentation in our seminar series on computing education for primary-aged children. 

In his presentation, Aman gave a concise tour of CT practices for teachers, and shared his findings from recent projects around how teachers perceive and integrate CT into their lessons.

Research in context

Aman began his talk by placing his team’s work within the wider context of computing education in the US. The computing education landscape Aman described is dominated by the National Science Foundation’s ambitious goal, set in 2008, to train 10,000 computer science teachers. This objective has led to various initiatives designed to support computer science education at the K–12 level. However, despite some progress, only 57% of US high schools offer foundational computer science courses, only 5.8% of students enrol in these courses, and just 31% of the enrolled students are female. As a result, Aman and his team have worked in close partnership with teachers to address questions that explore ways to more meaningfully integrate CT ideas and practices into formal education, such as:

  • What kinds of experiences do students need to learn computing concepts, to be confident to pursue computing?
  • What kinds of knowledge do teachers need to have to facilitate these learning experiences?
  • What kinds of experiences do teachers need to develop these kinds of knowledge? 

The CT4EDU project

At the primary education level, the CT4EDU project posed the question “What does computational thinking actually look like in elementary classrooms, especially in the context of maths and science classes?” This project involved collaboration with teachers, curriculum designers, and coaches to help them conceptualise and implement CT in their core instruction.

A child at a laptop

During professional development workshops using both plugged and unplugged tasks, the researchers supported educators to connect their day-to-day teaching practice to four foundational CT constructs:

  1. Debugging
  2. Abstraction
  3. Decomposition
  4. Patterns

An emerging aspect of the research team’s work has been the important relationship between vocabulary, belonging, and identity-building, with implications for equity. Actively incorporating CT vocabulary in lesson planning and classroom implementation helps students familiarise themselves with CT ideas: “If young people are using the language, they see themselves belonging in computing spaces”. 

A main finding from the study is that teachers used CT ideas to explicitly engage students in metacognitive thinking processes, and to help them be aware of their thinking as they solve problems. Rather than teachers using CT solely to introduce their students to computing, they used CT as a way to support their students in whatever they were learning. This constituted a fundamental shift in the research team’s thinking and future work, which is detailed further in a conceptual article. 

The Smithsonian Science for Computational Thinking project

The work conducted for the CT4EDU project guided the approach taken in the Smithsonian Science for Computational Thinking project. This project entailed the development of a curriculum for grades 3 and 5 that integrates CT into science lessons.

Teacher and young student at a laptop.

Part of the project included surveying teachers about the value they place on CT, both before and after participating in professional development workshops focused on CT. The researchers found that even before the workshops, teachers make connections between CT and the rest of the curriculum. After the workshops, an overwhelming majority agreed that CT has value (see image below). From this survey, it seems that CT ties things together for teachers in ways not possible or not achieved with other methods they’ve tried previously.  

A graph from Aman's seminar.

Despite teachers valuing the CT approach, asking them to integrate coding into their practices from the start remains a big ask (see image below). Many teachers lack knowledge or experience of coding, and they may not be curriculum designers, which means that we need to develop resources that allow teachers to integrate CT and coding in natural ways. Aman proposes that this requires a longitudinal approach, working with teachers over several years, using plugged and unplugged activities, and working closely with schools’ STEAM or specialist technology teachers where applicable to facilitate more computationally rich learning experiences in classrooms.

A graph from Aman's seminar.

Integrated computational thinking

Aman’s team is also engaged in a research project to integrate CT at middle school level for students aged 11 to 14. This project focuses on the question “What does CT look like in the context of social studies, English language, and art classrooms?”

For this project, the team conducted three Delphi studies, and consequently created learning pathways for each subject, which teachers can use to bring CT into their classrooms. The pathways specify practices and sub-practices to engage students with CT, and are available on the project website. The image below exemplifies the CT integration pathways developed for the arts subject, where the relationship between art and data is explored from both directions: by using CT and data to understand and create art, and using art and artistic principles to represent and communicate data. 

Computational thinking in the primary classroom

Aman’s work highlights the broad value of CT in education. However, to meaningfully integrate CT into the classroom, Aman suggests that we have to take a longitudinal view of the time and methods required to build teachers’ understanding and confidence with the fundamentals of CT, in a way that is aligned with their values and objectives. Aman argues that CT is really about thinking, and sometimes about computing, to support disciplinary learning in primary classrooms. Therefore, rather than focusing on integrating coding into the classroom, he proposes that we should instead talk about using CT practices as the building blocks that provide the foundation for incorporating computationally rich experiences in the classroom. 

Watch the recording of Aman’s presentation:

You can access Aman’s seminar slides as well.

You can find out more about connecting research to practice for primary computing education by watching the recordings of the other seminars in our series on primary (K–5) teaching and learning. In particular, Bobby Whyte discusses similar concepts to Aman in his talk on integrating primary computing and literacy through multimodal storytelling. 

Sign up for our seminars

Our 2024 seminar series is on the theme of teaching programming, with or without AI. In this series, we explore the latest research on how teachers can best support school-age learners to develop their programming skills.

On 13 February, we’ll hear from Majeed Kazemi (University of Toronto) about his work investigating whether AI code generator tools can support K-12 students to learn Python programming.

Sign up now to join the seminar:

I want to sign up

The post Integrating computational thinking into primary teaching appeared first on Raspberry Pi Foundation.

Teaching about AI explainability

Post Syndicated from Mac Bowley original https://www.raspberrypi.org/blog/teaching-ai-explainability/

In the rapidly evolving digital landscape, students are increasingly interacting with AI-powered applications when listening to music, writing assignments, and shopping online. As educators, it’s our responsibility to equip them with the skills to critically evaluate these technologies.

A woman teacher helps a young person with a coding project.

A key aspect of this is understanding ‘explainability’ in AI and machine learning (ML) systems. The explainability of a model is how easy it is to ‘explain’ how a particular output was generated. Imagine having a job application rejected by an AI model, or facial recognition technology failing to recognise you — you would want to know why.

Two teenage girls do coding activities at their laptops in a classroom.

Establishing standards for explainability is crucial. Otherwise we risk creating a world where decisions impacting our lives are made by opaque systems we don’t understand. Learning about explainability is key for students to develop digital literacy, enabling them to navigate the digital world with informed awareness and critical thinking.

Why AI explainability is important

AI models can have a significant impact on people’s lives in various ways. For instance, if a model determines a child’s exam results, parents and teachers would want to understand the reasoning behind it.

Two learners sharing a laptop in a coding session.

Artists might want to know if their creative works have been used to train a model and could be at risk of plagiarism. Likewise, coders will want to know if their code is being generated and used by others without their knowledge or consent. If you came across an AI-generated artwork that features a face resembling yours, it’s natural to want to understand how a photo of you was incorporated into the training data. 

Explainability is about accountability, transparency, and fairness, which are vital lessons for children as they grow up in an increasingly digital world.

There will also be instances where a model seems to be working for some people but is inaccurate for a certain demographic of users. This happened with Twitter’s (now X’s) face detection model in photos; the model didn’t work as well for people with darker skin tones, who found that it could not detect their faces as effectively as their lighter-skinned friends and family. Explainability allows us not only to understand but also to challenge the outputs of a model if they are found to be unfair.

In essence, explainability is about accountability, transparency, and fairness, which are vital lessons for children as they grow up in an increasingly digital world.

Routes to AI explainability

Some models, like decision trees, regression curves, and clustering, have an in-built level of explainability. There is a visual way to represent these models, so we can pretty accurately follow the logic implemented by the model to arrive at a particular output.

By teaching students about AI explainability, we are not only educating them about the workings of these technologies, but also teaching them to expect transparency as they grow to be future consumers or even developers of AI technology.

A decision tree works like a flowchart, and you can follow the conditions used to arrive at a prediction. Regression curves can be shown on a graph to understand why a particular piece of data was treated the way it was, although this wouldn’t give us insight into exactly why the curve was placed at that point. Clustering is a way of collecting similar pieces of data together to create groups (or clusters) with which we can interrogate the model to determine which characteristics were used to create the groupings.

A decision tree that classifies animals based on their characteristics; you can follow these models like a flowchart

However, the more powerful the model, the less explainable it tends to be. Neural networks, for instance, are notoriously hard to understand — even for their developers. The networks used to generate images or text can contain millions of nodes spread across thousands of layers. Trying to work out what any individual node or layer is doing to the data is extremely difficult.

Learners in a computing classroom.

Regardless of the complexity, it is still vital that developers find a way of providing essential information to anyone looking to use their models in an application or to a consumer who might be negatively impacted by the use of their model.

Model cards for AI models

One suggested strategy to add transparency to these models is using model cards. When you buy an item of food in a supermarket, you can look at the packaging and find all sorts of nutritional information, such as the ingredients, macronutrients, allergens they may contain, and recommended serving sizes. This information is there to help inform consumers about the choices they are making.

Model cards attempt to do the same thing for ML models, providing essential information to developers and users of a model so they can make informed choices about whether or not they want to use it.

A model card mock-up from the Experience AI Lessons

Model cards include details such as the developer of the model, the training data used, the accuracy across diverse groups of people, and any limitations the developers uncovered in testing.

Model cards should be accessible to as many people as possible.

A real-world example of a model card is Google’s Face Detection model card. This details the model’s purpose, architecture, performance across various demographics, and any known limitations of their model. This information helps developers who might want to use the model to assess whether it is fit for their purpose.

Transparency and accountability in AI

As the world settles into the new reality of having the amazing power of AI models at our disposal for almost any task, we must teach young people about the importance of transparency and responsibility. 

An educator points to an image on a student's computer screen.

As a society, we need to have hard discussions about where and when we are comfortable implementing models and the consequences they might have for different groups of people. By teaching students about explainability, we are not only educating them about the workings of these technologies, but also teaching them to expect transparency as they grow to be future consumers or even developers of AI technology.

Most importantly, model cards should be accessible to as many people as possible — taking this information and presenting it in a clear and understandable way. Model cards are a great way for you to show your students what information is important for people to know about an AI model and why they might want to know it. Model cards can help students understand the importance of transparency and accountability in AI.  

This article also appears in issue 22 of Hello World, which is all about teaching and AI. Download your free PDF copy now.

If you’re an educator, you can use our free Experience AI Lessons to teach your learners the basics of how AI works, whatever your subject area.

The post Teaching about AI explainability appeared first on Raspberry Pi Foundation.

Culturally relevant Computing: Experiences of primary learners

Post Syndicated from Alex Hadwen-Bennett original https://www.raspberrypi.org/blog/culturally-relevant-pedagogy-experiences-primary-computing/

Today’s blog is written by Dr Alex Hadwen-Bennett, who we worked with to find out primary school learners’ experiences of engaging with culturally relevant Computing lessons. Alex is a Lecturer in Computing Education at King’s College London, where he undertakes research focusing on inclusive computing education and the pedagogy of making.

Despite many efforts to make a career in Computing more accessible, many groups of people are still underrepresented in the field. For instance, a 2022 report revealed that only 22% of people currently working in the IT industry in the UK are women. Additionally, among learners who study Computing at schools in England, Black Caribbean students are currently one of the most underrepresented groups. One approach that has been suggested to address this underrepresentation at school is culturally relevant pedagogy.

In a computing classroom, a girl laughs at what she sees on the screen.

For this reason, a particular focus of the Raspberry Pi Foundation’s academic research programme is to support Computing teachers in the use of culturally relevant pedagogy. This pedagogy involves developing learning experiences that deliberately aim to enable all learners to engage with and succeed in Computing, including by bringing their culture and interests into the classroom.

The Foundation’s work in this area started with the development of guidelines for culturally relevant and responsive teaching together with a group of teachers and external researchers. The Foundation’s researchers then explored how a group of Computing teachers employed the guidelines in their own teaching. In a follow-on study funded by Cognizant, the team worked with 13 primary school teachers in England to adapt Computing lessons to make them culturally relevant for their learners. In this process, the teachers adapted a unit on photo editing for Year 4 (ages 8–9), and a unit about vector graphics for Year 5 (ages 9–10). As part of the project, I worked with the Foundation team to analyse and report on data gathered from focus groups of primary learners who had engaged with the adapted units.

At the beginning of this study, teachers adapted two units of work that cover digital literacy skills

Conducting the focus groups

For the focus groups, the Foundation team asked teachers from three schools to each choose four learners to take part. All children in the three focus groups had taken part in all the lessons involving the culturally adapted resources. The children were both boys and girls, and came from diverse cultural backgrounds where possible.

The questions for the focus groups were prepared in advance and covered:

  • Perceptions of Computing as a subject
  • Reflections of their experiences of the engaging with culturally adapted resources
  • Perceptions of who does Computing

Outcomes from the focus groups

“I feel happy that I see myself represented in some way.”

“It was nice to do something that actually represented you in many different ways, like your culture and your background.”

– Statements of learners who participated in the focus groups

When the learners were asked about what they did in their Computing lessons, most of them made references to working with and manipulating graphics; fewer made references to programming and algorithms. This emphasis on graphics is likely related to this being the most recent topic the learners engaged with. The learners were also asked about their reflections on the culturally adapted graphics unit that they had recently completed. Many of them felt that the unit gave them the freedom to incorporate things that related to their interests or culture. The learners’ responses also suggested that they felt represented in the work they completed during the unit. Most of them indicated that their interests were acknowledged, whereas fewer mentioned that they felt their cultural backgrounds were highlighted.

“Anyone can be good at computing if they have the passion to do it.”

– Statement by a learner who participated in a focus group

When considering who does computing, the learners made multiple references to people who keep trying or do not give up. Whereas only a couple of learners said that computer scientists need to be clever or intelligent to do computing. A couple of learners suggested that they believed that anyone can do computing. It is encouraging that the learners seemed to associate being good at computing with effort rather than with ability. However, it is unclear whether this is associated with the learners engaging with the culturally adapted resources.

Reflections and next steps

While this was a small-scale study, the focus groups findings do suggest that engaging with culturally adapted resources can make primary learners feel more represented in their Computing lessons. In particular, engaging with an adapted unit led learners to feel that their interests were recognised as well as, to a lesser extent, their cultural backgrounds. This suggests that primary-aged learners may identify their practical interests as the most important part of their background, and want to share this in class.

Two children code on laptops while an adult supports them.

Finally, the responses of the learners suggest that they feel that perseverance is a more important quality than intelligence for success in computing and that anyone can do it. While it is not possible to say whether this is directly related to their engagement with a culturally adapted unit, it would be an interesting area for further research.

More information and resources

You can find out more about culturally relevant pedagogy and the Foundation’s research on it, for example by:

The Foundation would like to extend thanks to Cognizant for funding this research, and to the primary computing teachers and learners who participated in the project. 

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Engaging primary Computing teachers in culturally relevant pedagogy through professional development

Post Syndicated from Claire Johnson original https://www.raspberrypi.org/blog/culturally-relevant-pedagogy-areas-opportunity-adapting-lessons/

Underrepresentation in computing is a widely known issue, in industry and in education. To cite some statistics from the UK: a Black British Voices report from August 2023 noted that 95% of respondents believe the UK curriculum neglects black lives and experiences; fewer students from working class backgrounds study GCSE Computer Science; when they leave formal education, fewer female, BAME, and white working class people are employed in the field of computer science (Kemp 2021); only 21% of GCSE Computer Science students, 15% at A level, and 22% at undergraduate level are female (JCQ 2020, Ofqual 2020, UCAS 2020); students with additional needs are also underrepresented.

In a computing classroom, two girls concentrate on their programming task.

Such statistics have been the status quo for too long. Many Computing teachers already endeavour to bring about positive change where they can and engage learners by including their interests in the lessons they deliver, so how can we support them to do this more effectively? Extending the reach of computing so that it is accessible to all also means that we need to consider what formal and informal values predominate in the field of computing. What is the ‘hidden’ curriculum in computing that might be excluding some learners? Who is and who isn’t represented?

Katharine Childs.
Katharine Childs (Raspberry Pi Foundation)

In a recent research seminar, Katharine Childs from our team outlined a research project we conducted, which included a professional development workshop to increase primary teachers’ awareness of and confidence in culturally relevant pedagogy. In the workshop, teachers considered how to effectively adapt curriculum materials to make them culturally relevant and engaging for the learners in their classrooms. Katharine described the practical steps teachers took to adapt two graphics-related units, and invited seminar participants to apply their learning to a graphics activity themselves.

What is culturally relevant pedagogy?

Culturally relevant pedagogy is a teaching framework which values students’ identities, backgrounds, knowledge, and ways of learning. By drawing on students’ own interests, experiences and cultural knowledge educators can increase the likelihood that the curriculum they deliver is more relevant, engaging and accessible to all.

The idea of culturally relevant pedagogy was first introduced in the US in the 1990s by African-American academic Gloria Ladson-Billings (Ladson-Billings 1995). Its aim was threefold: to raise students’ academic achievement, to develop students’ cultural competence and to promote students’ critical consciousness. The idea of culturally responsive teaching was later advanced by Geneva Gay (2000) and more recently  brought into focus in US computer science education by Kimberly Scott and colleagues (2015). The approach has been localised for England by Hayley Leonard and Sue Sentance (2021) in work they undertook here at the Foundation.

Ten areas of opportunity

Katharine began her presentation by explaining that the professional development workshop in the Primary culturally adapted resources for computing project built on two of our previous research projects to develop guidelines for culturally relevant and responsive computing and understand how teachers used them in practice. This third project ran as a pilot study funded by Cognizant, starting in Autumn 2022 with a one-day, in-person workshop for 13 primary computing teachers

The research structure was a workshop followed by research adaption, then delivery of resources, and evaluation through a parent survey, teacher interviews, and student focus groups.

Katharine then introduced us to the 10 areas of opportunity (AO) our research at the Raspberry Pi Computing Education Research Centre had identified for culturally relevant pedagogy. These 10 areas were used as practical prompts to frame the workshop discussions:

  1. Find out about learners
  2. Find out about ourselves as teachers
  3. Review the content
  4. Review the context
  5. Make the learning accessible to all
  6. Provide opportunities for open-ended and problem solving activities
  7. Promote collaboration and structured group discussion
  8. Promote student agency through choice
  9. Review the learning environment
  10. Review related policies, processes, and training in your school and department

At first glance it is easy to think that you do most of those things already, or to disregard some items as irrelevant to the computing curriculum. What would your own cultural identity (see AO2) have to do with computing, you might wonder. But taking a less complacent perspective might lead you to consider all the different facets that make up your identity and then to think about the same for the students you teach. You may discover that there are many areas which you have left untapped in your lesson planning.

Two young people learning together at a laptop.

Katharine explained how this is where the professional development workshop showed itself as beneficial for the participants. It gave teachers the opportunity to reflect on how their cultural identity impacted on their teaching practices — as a starting point to learning more about other aspects of the culturally relevant pedagogy approach.

Our researchers were interested in how they could work alongside teachers to adapt two computing units to make them more culturally relevant for teachers’ specific contexts. They used the Computing Curriculum units on Photo Editing (Year 4) and Vector Graphics (Year 5).

A slide about adapting an emoji teaching activity to make it culturally relevant.

Katharine illustrated some of the adaptations teachers and researchers working together had made to the emoji activity above, and which areas of opportunity (AO) had been addressed; this aspect of the research will be reported in later publications.

Results after the workshop

Although the numbers of participants in this pilot study was small, the findings show that the professional development workshop significantly increased teachers’ awareness of culturally relevant pedagogy and their confidence in adapting resources to take account of local contexts:

  • After the workshop, 10/13 teachers felt more confident to adapt resources to be culturally relevant for their own contexts, and 8/13 felt more confident in adapting resources for others.
  • Before the workshop, 5/13 teachers strongly agreed that it was an important part of being a computing teacher to examine one’s own attitudes and beliefs about race, gender, disabilities, sexual orientation. After the workshop, the number in agreement rose to 12/13.
  • After the workshop, 13/13 strongly agreed that part of a computing teacher’s responsibility is to challenge teaching practices which maintain social inequities (compared to 7/13 previously).
  • Before the workshop, 4/13 teachers strongly agreed that it is important to allow student choice when designing computing activities; this increased to 9/13 after the workshop.

These quantitative shifts in perspective indicate a positive effect of the professional development pilot. 

Katharine described that in our qualitative interviews with the participating teachers, they expressed feeling that their understanding of culturally relevant pedagogy had increased and they recognized the many benefits to learners of the approach. They valued the opportunity to discuss their contexts and to adapt materials they currently used with other teachers, because it made it a more ‘authentic’ and practical professional development experience.

The seminar ended with breakout sessions inviting viewers to consider possible adaptations that could be made to the graphics activities which had been the focus of the workshop.

In the breakout sessions, attendees also discussed specific examples of culturally relevant teaching practices that had been successful in their own classrooms, and they considered how schools and computing educational initiatives could support teachers in their efforts to integrate culturally relevant pedagogy into their practice. Some attendees observed that it was not always possible to change schemes of work without a ‘whole-school’ approach, senior leadership team support, and commitment to a research-based professional development programme.

Where do you see opportunities for your teaching?

The seminar reminds us that the education system is not culture neutral and that teachers generally transmit the dominant culture (which may be very different from their students’) in their settings (Vrieler et al, 2022). Culturally relevant pedagogy is an attempt to address the inequities and biases that exist, which result in many students feeling marginalised, disenfranchised, or underachieving. It urges us to incorporate learners’ cultures and experiences in our endeavours  to create a more inclusive computing curriculum; to adopt an intersectional lens so that all can thrive.

Secondary school age learners in a computing classroom.

As a pilot study, the workshop was offered to a small cohort of 13, yet the findings show that the intervention significantly increased participants’ awareness of culturally relevant pedagogy and their confidence in adapting resources to take account of local contexts.

Of course there are many ways in which teachers already adapt resources to make them interesting and accessible to their pupils. Further examples of the sort of adaptations you might make using these areas of opportunity include:

  • AO1: You could find out to what extent learners feel like they ‘belong’ or are included in a particular computing-related career. This is sure to yield valuable insights into learners’ knowledge and/or preconceptions of computing-related careers. 
  • AO3: You could introduce topics such as the ethics of AI, data bias, investigations of accessibility and user interface design. 
  • AO4: You might change the context of a unit of work on the use of conditional statements in programming, from creating a quiz about ‘Vikings’ to focus on, for example, aspects of youth culture which are more engaging to some learners such as football or computer games, or to focus on religious celebrations, which may be more meaningful to others.
  • AO5: You could experiment with a particular pedagogical approach to maximise the accessibility of a unit of work. For example, you could structure a programming unit by using the PRIMM model, or follow the Universal Design for Learning framework to differentiate for diversity.
  • AO6/7: You could offer more open-ended and collaborative activities once in a while, to promote engagement and to allow learners to express themselves autonomously.
  • AO8: By allowing learners to choose topics which are relevant or familiar to their individual contexts and identities, you can increase their feeling of agency. 
  • AO9: You could review both your learning materials and your classroom to ensure that all your students are fully represented.
  • AO10: You can bring colleagues on board too; the whole enterprise of embedding culturally relevant pedagogy will be more successful when school- as well as department-level policies are reviewed and prioritised.

Can you see an opportunity for integrating culturally relevant pedagogy in your classroom? We would love to hear about examples of culturally relevant teaching practices that you have found successful. Let us know your thoughts or questions in the comments below.

You can watch Katharine’s seminar here:

You can download her presentation slides on our ‘previous seminars’ page, and you can read her research paper.

To get a practical overview of culturally relevant pedagogy, read our 2-page Quick Read on the topic and download the guidelines we created with a group of teachers and academic specialists.

Tomorrow we’ll be sharing a blog about how the learners who engaged with the culturally adapted units found the experience, and how it affected their views of computing. Follow us on social media to not miss it!

Join our upcoming seminars live

On 12 December we’ll host the last seminar session in our series on primary (K-5) computing. Anaclara Gerosa will share her work on how to design and structure early computing activities that promote and scaffold students’ conceptual understanding. As always, the seminar is free and takes place online at 17:00–18:30 GMT / 12:00–13:30 ET / 9:00–10:30 PT / 18:00–19:30 CET. Sign up and we’ll send you the link to join on the day.

I want to sign up

In 2024, our new seminar series will be about teaching and learning programming, with and without AI tools. If you’re signed up to our seminars, you’ll receive the link to join every monthly seminar.

The post Engaging primary Computing teachers in culturally relevant pedagogy through professional development appeared first on Raspberry Pi Foundation.

Spotlight on teaching programming with and without AI in our 2024 seminar series

Post Syndicated from Bonnie Sheppard original https://www.raspberrypi.org/blog/teaching-programming-ai-seminar-series-2024/

How do you best teach programming in school? It’s one of the core questions for primary and secondary computing teachers. That’s why we’re making it the focus of our free online seminars in 2024. You’re invited to attend and hear about the newest research about the teaching and learning of programming, with or without AI tools.

Two smiling adults learn about computing at desktop computers.

Building on the success and the friendly, accessible session format of our previous seminars, this coming year we will delve into the latest trends and innovative approaches to programming education in school.

Secondary school age learners in a computing classroom.

Our online seminars are for everyone interested in computing education

Our monthly online seminars are not only for computing educators but also for everyone else who is passionate about teaching young people to program computers. The seminar participants are a diverse community of teachers, technology enthusiasts, industry professionals, coding club volunteers, and researchers.

Two adults learn about computing at desktop computers.

With the seminars we aim to bridge the gap between the newest research and practical teaching. Whether you are an educator in a traditional classroom setting or a mentor guiding learners in a CoderDojo or Code Club, you will gain insights from leading researchers about how school-age learners engage with programming. 

What to expect from the seminars

Each online seminar begins with an expert presenter delivering their latest research findings in an accessible way. We then move into small groups to encourage discussion and idea exchange. Finally, we come back together for a Q&A session with the presenter.

Here’s what attendees had to say about our previous seminars:

“As a first-time attendee of your seminars, I was impressed by the welcoming atmosphere.”

“[…] several seminars (including this one) provided valuable insights into different approaches to teaching computing and technology.”

“I plan to use what I have learned in the creation of curriculum […] and will pass on what I learned to my team.”

“I enjoyed the fact that there were people from different countries and we had a chance to see what happens elsewhere and how that may be similar and different to what we do here.”

January seminar: AI-generated Parson’s Problems

Computing teachers know that, for some students, learning about the syntax of programming languages is very challenging. Working through Parson’s Problem activities can be a way for students to learn to make sense of the order of lines of code and how syntax is organised. But for teachers it can be hard to precisely diagnose their students’ misunderstandings, which in turn makes it hard to create activities that address these misunderstandings.

A group of students and a teacher at the Coding Academy in Telangana.

At our first 2024 seminar on 9 January, Dr Barbara Ericson and Xinying Hou (University of Michigan) will present a promising new approach to helping teachers solve this difficulty. In one of their studies, they combined Parsons Problems and generative AI to create targeted activities for students based on the errors students had made in previous tasks. Thus they were able to provide personalised activities that directly addressed gaps in the students’ learning.

Sign up now to join our seminars

All our seminars start at 17:00 UK time (18:00 CET / 12:00 noon ET / 9:00 PT) and are held online on Zoom. To ensure you don’t miss out, sign up now to receive calendar invitations, and access links for each seminar on the day.

I want to sign up

If you sign up today, we’ll also invite you to our 12 December seminar with Anaclara Gerosa (University of Glasgow) about how to design and structure of computing activities for young learners, the final session in our 2023 series about primary (K-5) computing education.

The post Spotlight on teaching programming with and without AI in our 2024 seminar series appeared first on Raspberry Pi Foundation.

Evolving our online courses to help more people be computing educators

Post Syndicated from Sway Grantham original https://www.raspberrypi.org/blog/free-online-courses-computing-education-updates-2023/

Since launching our free online courses about computing on the edX platform back in August, we’ve been training course facilitators and analysing the needs of educators around the world. We want every course participant to have a great experience learning with us — read on to find out what we’re doing right now and into 2024 to ensure this.

Workshop attendees at a table.

Online courses for all adults who support young people

Educators of all kinds are key for supporting children and young people to engage with computing technology and develop digital skills. You might be a professional teacher, or a parent, volunteer, youth worker, librarian… there are so many roles in which people share knowledge with young learners.

Young people and an adult mentor at a computer at Coolest Projects Ireland 2023.

That’s why our online courses are designed to support any kind of educator to:

  • Understand the full breadth of topics within computing
  • Discover how to introduce computing to young people in clear and exciting ways that are grounded in the latest research

We are constantly improving our online courses based on your feedback, the latest education research, and the insights our team members gain through supporting you on your course learning journeys. Three principles guide these improvements: accessibility, scalability, and sustainability. 

Making our courses more relevant and accessible

Our online courses are used by people who live around the world and bring various knowledge and experiences. Some participants are classroom teachers, others have computing experience from their job and want to volunteer at a kids’ coding club, and some may be parents who want to support their children. It’s important to us that our courses are relevant and accessible to all kinds of adult learners. 

A parent and child work together at a Raspberry Pi computer.

We’re currently working to: 

  • Simplify the English in the courses for participants who speak it as a second language
  • Adapt the course activities for specific settings where participants help young people learn so that e.g. teachers see how the activities work in the classroom, and volunteers who run coding clubs see how they work in club sessions
  • Ensure our course facilitators have experience in a range of different settings including coding clubs, and in a variety of different contexts around the world

Making our courses useful for more groups of people

When we think about the scalability of our courses, we think about how to best support as many educators around the world as possible. If we can make the jobs of all educators easier, whatever their setting is like, then we are making the right choices.

An educator helps two young people at a computer.

We’re currently working to: 

  • Talk with the global network of educators we’re a part of to better understand what works for them so we can reflect that in the courses
  • Include a wider range of examples for settings beyond the classroom in the courses
  • Adapt our courses so they are relevant to participants with various needs while sustaining the high quality of the overall learning experience

Making the learning from our courses sustainable

The educators who take our courses work to achieve amazing things, and this means they are often busy. That they take the time to complete one of our courses to learn new things is a commitment we want to make sure is rewarded. The learning you get from participating in our online courses should continue to benefit you far beyond the time you spend completing it. This is what we mean by sustainability.

Kenyan educators work on a physical computing project.

We’re currently working to: 

  • Lay out clear learning pathways so you can build on the knowledge you gain in one course in the next course
  • Offer course resources that are easy to access after you’ve completed the course
  • Explore ways to build communities around our courses where you can share successes and learning outcomes with your fellow participants

Learn with us, and help us design better courses for you

Our work to improve the accessibility, scalability, and sustainability of our courses will continue into 2024, and these three principles will likely be part of our online training strategy for the following year too. 

If you’d like to support young people in your life to learn about computing and digital technologies, take one of our free courses now and learn something new. We have twenty courses available right now and they are totally free.

We are also looking for adult testers for new course content. So if you’re any kind of educator and would like to test upcoming online course content and share your feedback and experiences, please send us a message with the subject ‘Educator training’. 

The post Evolving our online courses to help more people be computing educators appeared first on Raspberry Pi Foundation.

Support for new computing teachers: A tool to find Scratch programming errors

Post Syndicated from Bonnie Sheppard original https://www.raspberrypi.org/blog/support-new-computing-teachers-debugging-scratch-litterbox/

We all know that learning to program, and specifically learning how to debug or fix code, can be frustrating and leave beginners overwhelmed and disheartened. In a recent blog article, our PhD student Lauria at the Raspberry Pi Computing Education Research Centre highlighted the pivotal role that teachers play in shaping students’ attitudes towards debugging. But what about teachers who are coding novices themselves?

Two adults learn about computing at desktop computers.

In many countries, primary school teachers are holistic educators and often find themselves teaching computing despite having little or no experience in the field. In a recent seminar of our series on computing education for primary-aged children, Luisa Greifenstein told attendees that struggling with debugging and negative attitudes towards programming were among the top ten challenges mentioned by teachers.

Luisa Greifenstein.

Luisa is a researcher at the University of Passau, Germany, and has been working closely with both teacher trainees and experienced primary school teachers in Germany. She’s found that giving feedback to students can be difficult for primary school teachers, and especially for teacher trainees, as programming is still new to them. Luisa’s seminar introduced a tool to help.

A unique approach: Visualising debugging with LitterBox

To address this issue, the University of Passau has initiated the primary::programming project. One of its flagship tools, LitterBox, offers a unique solution to debugging and is specifically designed for Scratch, a beginners’ programming language widely used in primary schools.

A screenshot from the LitterBox tool.
You can upload Scratch program files to LitterBox to analyse them. Click to enlarge.

LitterBox serves as a static code debugging tool that transforms code examination into an engaging experience. With a nod to the Scratch cat, the tool visualises the debugging of Scratch code as checking the ‘litterbox’, categorising issues into ‘bugs’ and ‘smells’:

  • Bugs represent code patterns that have gone wrong, such as missing loops or specific blocks
  • Smells indicate that the code couldn’t be processed correctly because of duplications or unnecessary elements
A screenshot from the LitterBox tool.
The code patterns LitterBox recognises. Click to enlarge.

What sets LitterBox apart is that it also rewards correct code by displaying ‘perfumes’. For instance, it will praise correct broadcasting or the use of custom blocks. For every identified problem or achievement, the tool provides short and direct feedback.

A screenshot from the LitterBox tool.
LitterBox also identifies good programming practice. Click to enlarge.

Luisa and her team conducted a study to gauge the effectiveness of LitterBox. In the study, teachers were given fictitious student code with bugs and were asked to first debug the code themselves and then explain in a manner appropriate to a student how to do the debugging.

The results were promising: teachers using LitterBox outperformed a control group with no access to the tool. However, the team also found that not all hints proved equally helpful. When hints lacked direct relevance to the code at hand, teachers found them confusing, which highlighted the importance of refining the tool’s feedback mechanisms.

A bar chart showing that LitterBox helps computing teachers.

Despite its limitations, LitterBox proved helpful in another important aspect of the teachers’ work: coding task creation. Novice students require structured tasks and help sheets when learning to code, and teachers often invest substantial time in developing these resources. While LitterBox does not guide educators in generating new tasks or adapting them to their students’ needs, in a second study conducted by Luisa’s team, teachers who had access to LitterBox not only received support in debugging their own code but also provided more scaffolding in task instructions they created for their students compared to teachers without LitterBox.

How to maximise the impact of new tools: use existing frameworks and materials

One important realisation that we had in the Q&A phase of Luisa’s seminar was that many different research teams are working on solutions for similar challenges, and that the impact of this research can be maximised by integrating new findings and resources. For instance, what the LitterBox tool cannot offer could be filled by:

  • Pedagogical frameworks to enhance teachers’ lessons and feedback structures. Frameworks such as PRIMM (Predict, Run, Investigate, Modify, and Make) or TIPP&SEE for Scratch projects (Title, Instructions, Purpose, Play & Sprites, Events, Explore) can serve as valuable resources. These frameworks provide a structured approach to lesson design and teaching methodologies, making it easier for teachers to create engaging and effective programming tasks. Additionally, by adopting semantic waves in the feedback for teachers and students, a deeper understanding of programming concepts can be fostered. 
  • Existing courses and materials to aid task creation and adaptation. Our expert educators at the Raspberry Pi Foundation have not only created free lesson plans and courses for teachers and educators, but also dedicated non-formal learning paths for Scratch, Python, Unity, web design, and physical computing that can serve as a starting point for classroom tasks.

Exploring innovative ideas in computing education

As we navigate the evolving landscape of programming education, it’s clear that innovative tools like LitterBox can make a significant difference in the journey of both educators and students. By equipping educators with effective debugging and task creation solutions, we can create a more positive and engaging learning experience for students.

If you’re an educator, consider exploring how such tools can enhance your teaching and empower your students in their coding endeavours.

You can watch the recording of Luisa’s seminar here:

Sign up now to join our next seminar

If you’re interested in the latest developments in computing education, join us at one of our free, monthly seminars. In these sessions, researchers from all over the world share their innovative ideas and are eager to discuss them with educators and students. In our December seminar, Anaclara Gerosa (University of Edinburgh) will share her findings about how to design and structure early-years computing activities.

I want to sign up

This will be the final seminar in our series about primary computing education. Look out for news about the theme of our 2024 seminar series, which are coming soon.

The post Support for new computing teachers: A tool to find Scratch programming errors appeared first on Raspberry Pi Foundation.

AI literacy for teachers and students all over the world

Post Syndicated from Philip Colligan original https://www.raspberrypi.org/blog/experience-ai-canada-kenya-romania/

I am delighted to announce that the Raspberry Pi Foundation and Google DeepMind are building a global network of educational organisations to bring AI literacy to teachers and students all over the world, starting with Canada, Kenya, and Romania.

Learners in a classroom in Kenya.
Learners around the world will gain AI literacy skills through Experience AI.

Experience AI 

We launched Experience AI in September 2022 to help teachers and students learn about AI technologies and how they are changing the world. 

Developed by the Raspberry Pi Foundation and Google DeepMind, Experience AI provides everything that teachers need to confidently deliver engaging lessons that will inspire and educate young people about AI and the role that it could play in their lives.

A group of young people investigate computer hardware together.
Experience AI is designed to inspire learners about AI through real-world contexts.

We provide lesson plans, classroom resources, worksheets, hands-on activities, and videos that introduce a wide range of AI applications and the underlying technologies that make them work. The materials are designed to be relatable to young people and can be taught by any teacher, whether or not they have a technical background. Alongside the classroom resources, we provide teacher professional development, including an online course that provides an introduction to machine learning and AI. 

Part of Experience AI are video interviews with AI developers at Google DeepMind.

The materials are grounded in real-world contexts and emphasise the potential for young people to positively change the world through a mastery of AI technologies. 

Since launching the first resources, we have seen significant demand from teachers and students all over the world, with over 200,000 students already learning with Experience AI. 

Experience AI network

Building on that initial success and in response to huge demand, we are now building a global network of educational organisations to expand the reach and impact of Experience AI by translating and localising the materials, promoting them to schools, and supporting teacher professional development.

Obum Ekeke OBE, Head of Education Partnerships at Google DeepMind, says:

“We have been blown away by the interest we have seen in Experience AI since its launch and are thrilled to be working with the Raspberry Pi Foundation and local partners to expand the reach of the programme. AI literacy is a critical skill in today’s world, but not every young person currently has access to relevant education and resources. By making AI education more inclusive, we can help young people make more informed decisions about using AI applications in their daily lives, and encourage safe and responsible use of the technology.”

Learner in a computing classroom.
Experience AI helps learners understand how they might use AI to positively change the world.

Today we are announcing the first three organisations that we are working with, each of which is already doing fantastic work to democratise digital skills in their part of the world. All three are already working in partnership with the Raspberry Pi Foundation and we are excited to be deepening and expanding our collaboration to include AI literacy.

Digital Moment, Canada

Digital Moment is a Montreal-based nonprofit focused on empowering young changemakers through digital skills. Founded in 2013, Digital Moment has a track record of supporting teachers and students across Canada to learn about computing, coding, and AI literacy, including through supporting one of the world’s largest networks of Code Clubs. 

Digital Moment logo.

“We’re excited to be working with the Raspberry Pi Foundation and Google DeepMind to bring Experience AI to teachers across Canada. Since 2018, Digital Moment has been introducing rich training experiences and educational resources to make sure that Canadian teachers have the support to navigate the impacts of AI in education for their students. Through this partnership, we will be able to reach more teachers and with more resources, to keep up with the incredible pace and disruption of AI.”

Indra Kubicek, President, Digital Moment

Tech Kidz Africa, Kenya

Tech Kidz Africa is a Mobasa-based social enterprise that nurtures creativity in young people across Kenya through digital skills including coding, robotics, app and web development, and creative design thinking.

Tech Kidz Africa logo.

“With the retooling of teachers as a key objective of Tech Kidz Africa, working with Google DeepMind and the Raspberry Pi Foundation will enable us to build the capacity of educators to empower the 21st century learner, enhancing the teaching and learning experience to encourage innovation and  prepare the next generation for the future of work.”

Grace Irungu, CEO, Tech Kidz Africa

Asociația Techsoup, Romania

Asociația Techsoup works with teachers and students across Romania and Moldova, training Computer Science, ICT, and primary school teachers to build their competencies around coding and technology. A longstanding partner of the Raspberry Pi Foundation, they foster a vibrant community of CoderDojos and support young people to participate in Coolest Projects and the European Astro Pi Challenge. 

Asociata Techsoup logo.

“We are enthusiastic about participating in this global partnership to bring high-quality AI education to all students, regardless of their background. Given the current exponential growth of AI tools and instruments in our daily lives, it is crucial to ensure that students and teachers everywhere comprehend and effectively utilise these tools to enhance their human, civic, and professional potential. Experience AI is the best available method for AI education for middle school students. We couldn’t be more thrilled to work with the Raspberry Pi Foundation and Google DeepMind to make it accessible in Romanian for teachers in Romania and the Republic of Moldova, and to assist teachers in fully integrating it into their classes.”

Elena Coman, Director of Development, Asociația Techsoup

Get involved

These are the first of what will become a global network of organisations supporting tens of thousands of teachers to equip millions of students with a foundational understanding of AI technologies through Experience AI. If you want to get involved in inspiring the next generation of AI leaders, we would love to hear from you.

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