Tag Archives: computing education

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.

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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.

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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.

The post AI literacy for teachers and students all over the world appeared first on Raspberry Pi Foundation.

Coding futures: Celebrating our educational partnership in Telangana

Post Syndicated from Mamta Manaktala original https://www.raspberrypi.org/blog/tswreis-coding-academy-computing-education-partnership-telangana/

On September 29 2023, amidst much excitement and enthusiasm, a significant event took place at a unique school in Moinabad, Telangana: the teams of the Raspberry Pi Foundation and Telangana Social Welfare Residential Educational Institutions Society (TSWREIS) gathered to celebrate our partnership on the esteemed Coding Academy of TSWREIS.

The welcoming ceremony at the opening event of the Coding Academy in Telangana.
A celebratory ceremony at the opening event of the Coding Academy in Telangana.

This event marked a special project for us where we are piloting a distinctive, progression-based computing curriculum in a government school and a degree college in India.

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

Partnering with TSWREIS to bring computing education to Telangana

At the Foundation, our goal is to work closely with schools, tailoring our offerings to their contexts. Our objective is to design and evaluate unique learning experiences by integrating content from our diverse range of high-quality educational products. Through these efforts, we aim to drive significant advancements in education and technology, benefiting both students and education systems across the world.

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

TSWREIS manages 268 residential educational institutions in Telangana, with a primary focus on delivering quality education to under-resourced young people, particularly children from scheduled castes and tribes in rural areas. Among these institutions is the Coding Academy school, located in Moinabad, which operates as a fully residential co-ed school for grades 6 to 12, accommodating around 800 students. Additionally, TSWREIS oversees another centre of excellence, the Coding Academy degree college in Shamirpet catering to 600 undergraduate female students.

the Coding Academy in Telangana.
A computing classroom at the Coding Academy in Telangana.

We joined forces with TSWREIS to form a collaborative partnership with their Coding Academy units at both high school and college. We’re committed to sharing our expertise in computing and coding curriculum for students from Grade 6 to intermediate at the school, and across all courses at the college.

Our computing curriculum encompasses computer science, information technology, and digital literacy, and all its materials have been thoroughly researched and tested in the UK. Based on our 12 pedagogical principles, our curriculum ensures a project-based and holistic approach to learning. We also plan to provide national and international avenues for the Coding Academy students to showcase their learnings, for example through Coolest Projects, the world-leading, global technology showcase for young creators that we host every year. 

The exciting model for our partnership with TSWREIS

We took on the challenge of directly delivering a comprehensive curriculum at the Coding Academy school and college through our own educators, exclusively hired and trained for this project. This is an exciting new approach for us, because up to this point, we have never directly delivered a curriculum anywhere in the world. However, we know we have created a world-class computing curriculum for educators in formal (and non-formal) settings, and we have many years’ experience of training teachers, so we are well-prepared to face this project and its potential challenges head-on and make it a success.

A group of people from the Raspberry Pi Foundation at the Coding Academy in Telangana.

To begin the project, our team members based in India conducted a thorough study of the Coding Academy students’ interests and learning levels. Based on this, our Curriculum team in the UK and India customised and localised the content in our curriculum. We will be observing the curriculum’s delivery in classrooms and collecting students’ responses, and based on this data we’ll further refine the localised curriculum. 

Throughout the project’s lifespan, we’ll measure the effectiveness of our curriculum and the impact of learning on the students. To do this, we’ll collect data from classroom observations, periodic assessments, and focused group discussions with students and educators.

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

Starting from the second year of the project, we will build capacity within the system. In collaboration with TSWREIS, we’ll select teachers from within the organisation based on their interest and competence, and initiate their training. Our objective is that by the project’s fifth year, TSWREIS will have achieved self-sufficiency in delivering computing education to students at the Coding Academy as well as other institutions in its purview.

The promise of this project for our work in India

We began delivering lessons at the Coding Academy college and school in July, and it’s worth mentioning that it’s been a rollercoaster ride so far. We’ve been working closely with the TSWREIS team to equip both the academic units with the resources needed for seamless implementation of the project. Our India-based team has been able to ensure continuity in the project’s momentum and plug every gap, and is working tirelessly to make this big, challenging, and exciting project blossom and succeed. When it comes to the students’ energy, enthusiasm, and the sparkle in their eyes for their learning, it’s unmatched, and everyone feels proud of their achievements so far.

Three female students at the Coding Academy in Telangana.

This work with TSWREIS holds immense importance for us, representing our dedication to shaping a brighter educational landscape especially for young people from under-resourced communities. We hope to replicate similar initiatives across various regions in India, enabling widespread access to quality education. We also aspire to take forward our initiatives in much larger dimensions for the entirety of India. 

Students welcome Rachel Bennett at the Coding Academy in Telangana.

In addition to our partnership with TSWREIS, we are actively engaged in several other impactful projects in India, such as our partnership with Mo School Abhiyan in Odisha to serve the government’s schools across Odisha state, and our collaboration with Pratham Foundation, which is helping us reach under-resourced communities and furthering our commitment to enhancing educational experiences.

We look towards the future

In reflection, the voices at the launch event on September 29 echoed the anticipation and optimism that filled the air on that memorable day. Chief guests who graciously attended the event were Shri. E Naveen Nicholas, IAS, Secretary at TSWREIS & TTWREIS, and Rachel Bennett, our Managing Director at the Raspberry Pi Foundation. Heartfelt gratitude to them for their presence and blessings. We also extend our thanks to our funding partner in this work, Ezrah Charitable Trust, and our delivery partners for their invaluable support.

The group of people from the Raspberry Pi Foundation and TSWREIS at the Coding Academy in Telangana.

The energy felt on the event day continues to drive our determination to do the work that lies ahead. As we look forward to the future, our hope and the hope of both the Coding Academy team and students are aligned: hope for a brighter, technologically empowered future, where education becomes a beacon of opportunity for all.

The post Coding futures: Celebrating our educational partnership in Telangana appeared first on Raspberry Pi Foundation.

Hello World #22 out now: Teaching and AI

Post Syndicated from Meg Wang original https://www.raspberrypi.org/blog/hello-world-22-ai-education/

Recent developments in artificial intelligence are changing how the world sees computing and challenging computing educators to rethink their approach to teaching. In the brand-new issue of Hello World, out today for free, we tackle some big questions about AI and computing education. We also get practical with resources for your classroom.

Cover of Hello World issue 22.

Teaching and AI

In their articles for issue 22, educators explore a range of topics related to teaching and AI, including what is AI literacy and how do we teach it; gender bias in AI and what we can do about it; how to speak to young children about AI; and why anthropomorphism hinders learners’ understanding of AI.

Download your free digital copy

Our feature articles also include a research digest on AI ethics for children, and of course hands-on examples of AI lessons for your learners.

A snapshot of AI education

Hello World issue 22 is a comprehensive snapshot of the current landscape of AI education. Ben Garside, Learning Manager for our Experience AI programme and guest editor of this issue, says:

“When I was teaching in the classroom, I used to enjoy getting to grips with new technological advances and finding ways in which I could bring them into school and excite the students I taught. Occasionally, during the busiest of times, I’d also look longingly at other subjects and be jealous that their curriculum appeared to be more static than ours (probably a huge misconception on my behalf).”

It’s inspiring for me to see how the education community is reacting to the opportunities that AI can provide.

Ben Garside

“It’s inspiring for me to see how the education community is reacting to the opportunities that AI can provide. Of course, there are elements of AI where we need to tread carefully and be very cautious in our approach, but what you’ll see in this magazine is educators who are thinking creatively in this space.”

Download Hello World issue 22 for free

AI is a topic we’ve addressed before in Hello World, and we’ll keep covering this rapidly evolving area in future. We hope this issue gives you plenty of ideas to take away and build upon.

Also in issue 22:

  • Vocational training for young people
  • Making the most of online educator training
  • News about BBC micro:bit
  • An insight into the WiPSCE 2023 conference for teachers and educators
  • And much, much more

You can download your free PDF issue now, or purchase a print copy from our store. UK-based subscribers for a free print edition can expect their copies to arrive in the mail this week.

Download issue 22 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.

The post Hello World #22 out now: Teaching and AI appeared first on Raspberry Pi Foundation.

What does AI mean for computing education?

Post Syndicated from Philip Colligan original https://www.raspberrypi.org/blog/what-does-ai-mean-for-computing-education/

It’s been less than a year since ChatGPT catapulted generative artificial intelligence (AI) into mainstream public consciousness, reigniting the debate about the role that these powerful new technologies will play in all of our futures.

A person in front of a cloudy sky, seen through a refractive glass grid. Parts of the image are overlaid with a diagram of a neural network.
Image: Alan Warburton / © BBC / Better Images of AI / Quantified Human / CC-BY 4.0

‘Will AI save or destroy humanity?’ might seem like an extreme title for a podcast, particularly if you’ve played with these products and enjoyed some of their obvious limitations. The reality is that we are still at the foothills of what AI technology can achieve (think World Wide Web in the 1990s), and lots of credible people are predicting an astonishing pace of progress over the next few years, promising the radical transformation of almost every aspect of our lives. Comparisons with the Industrial Revolution abound.

At the same time, there are those saying it’s all moving too fast; that regulation isn’t keeping pace with innovation. One of the UK’s leading AI entrepreneurs, Mustafa Suleyman, said recently: “If you don’t start from a position of fear, you probably aren’t paying attention.”

In a computing classroom, a girl looks at a computer screen.
What is AI literacy for young people?

What does all this mean for education, and particularly for computing education? Is there any point trying to teach children about AI when it is all changing so fast? Does anyone need to learn to code anymore? Will teachers be replaced by chatbots? Is assessment as we know it broken?

If we’re going to seriously engage with these questions, we need to understand that we’re talking about three different things:

  1. AI literacy: What it is and how we teach it
  2. Rethinking computer science (and possibly some other subjects)
  3. Enhancing teaching and learning through AI-powered technologies

AI literacy: What it is and how we teach it

For young people to thrive in a world that is being transformed by AI systems, they need to understand these technologies and the role they could play in their lives.

In a computing classroom, a smiling girl raises her hand.
Our SEAME model articulates the concepts, knowledge, and skills that are essential ingredients of any AI literacy curriculum.

The first problem is defining what AI literacy actually means. What are the concepts, knowledge, and skills that it would be useful for a young person to learn?

The reality is that — with a few notable exceptions — the vast majority of AI literacy resources available today are probably doing more harm than good.

In the past couple of years there has been a huge explosion in resources that claim to help young people develop AI literacy. Our research team mapped and categorised over 500 resources, and undertaken a systematic literature review to understand what research has been done on K–12 AI classroom interventions (spoiler: not much). 

The reality is that — with a few notable exceptions — the vast majority of AI literacy resources available today are probably doing more harm than good. For example, in an attempt to be accessible and fun, many materials anthropomorphise AI systems, using human terms to describe them and their functions and thereby perpetuating misconceptions about what AI systems are and how they work.

A real banana and an image of a banana shown on the screen of a laptop are both labelled "Banana".
Image: Max Gruber / Better Images of AI / Ceci n’est pas une banane / CC-BY 4.0

What emerged from this work at the Raspberry Pi Foundation is the SEAME model, which articulates the concepts, knowledge, and skills that are essential ingredients of any AI literacy curriculum. It separates out the social and ethical, application, model, and engine levels of AI systems — all of which are important — and gets specific about age-appropriate learning outcomes for each. 

This research has formed the basis of Experience AI (experience-ai.org), a suite of resources, lessons plans, videos, and interactive learning experiences created by the Raspberry Pi Foundation in partnership with Google DeepMind, which is already being used in thousands of classrooms.

If we’re serious about AI literacy for young people, we have to get serious about AI literacy for teachers.

Defining AI literacy and developing resources is part of the challenge, but that doesn’t solve the problem of how we get them into the hands and minds of every young person. This will require policy change. We need governments and education system leaders to grasp that a foundational understanding of AI technologies is essential for creating economic opportunity, ensuring that young people have the mindsets to engage positively with technological change, and avoiding a widening of the digital divide. We’ve messed this up before with digital skills. Let’s not do it again.

Two smiling adults learn about computing at desktop computers.
Teacher professional development is key to AI literacy for young people.

More than anything, we need to invest in teachers and their professional development. While there are some fantastic computing teachers with computer science qualifications, the reality is that most of the computing lessons taught anywhere on the planet are taught by a non-specialist teacher. That is even more so the case for anything related to AI. If we’re serious about AI literacy for young people, we have to get serious about AI literacy for teachers. 

Rethinking computer science 

Alongside introducing AI literacy, we also need to take a hard look at computer science. At the very least, we need to make sure that computer science curricula include machine learning models, explaining how they constitute a new paradigm for computing, and give more emphasis to the role that data will play in the future of computing. Adding anything new to an already packed computer science curriculum means tough choices about what to deprioritise to make space.

Elephants in the Serengeti.
One of our Experience AI Lessons revolves around the us of AI technology to study the Serengeti ecosystem.

And, while we’re reviewing curricula, what about biology, geography, or any of the other subjects that are just as likely to be revolutionised by big data and AI? As part of Experience AI, we are launching some of the first lessons focusing on ecosystems and AI, which we think should be at the heart of any modern biology curriculum. 

Some are saying young people don’t need to learn how to code. It’s an easy political soundbite, but it just doesn’t stand up to serious scrutiny.

There is already a lively debate about the extent to which the new generation of AI technologies will make programming as we know it obsolete. In January, the prestigious ACM journal ran an opinion piece from Matt Welsh, founder of an AI-powered programming start-up, in which he said: “I believe the conventional idea of ‘writing a program’ is headed for extinction, and indeed, for all but very specialised applications, most software, as we know it, will be replaced by AI systems that are trained rather than programmed.”

Computer science students at a desktop computer in a classroom.
Writing computer programs is an essential part of learning how to analyse problems in computational terms.

With GitHub (now part of Microsoft) claiming that their pair programming technology, Copilot, is now writing 46 percent of developers’ code, it’s perhaps not surprising that some are saying young people don’t need to learn how to code. It’s an easy political soundbite, but it just doesn’t stand up to serious scrutiny. 

Even if AI systems can improve to the point where they generate consistently reliable code, it seems to me that it is just as likely that this will increase the demand for more complex software, leading to greater demand for more programmers. There is historical precedent for this: the invention of abstract programming languages such as Python dramatically simplified the act of humans providing instructions to computers, leading to more complex software and a much greater demand for developers. 

A child codes a Spiderman project at a laptop during a Code Club session.
Learning to program will help young people understand how the world around them is being transformed by AI systems.

However these AI-powered tools develop, it will still be essential for young people to learn the fundamentals of programming and to get hands-on experience of writing code as part of any credible computer science course. Practical experience of writing computer programs is an essential part of learning how to analyse problems in computational terms; it brings the subject to life; it will help young people understand how the world around them is being transformed by AI systems; and it will ensure that they are able to shape that future, rather than it being something that is done to them.

Enhancing teaching and learning through AI-powered technologies

Technology has already transformed learning. YouTube is probably the most important educational innovation of the past 20 years, democratising both the creation and consumption of learning resources. Khan Academy, meanwhile, integrated video instruction into a learning experience that gamified formative assessment. Our own edtech platform, Ada Computer Science, combines comprehensive instructional materials, a huge bank of questions designed to help learning, and automated marking and feedback to make computer science easier to teach and learn. Brilliant though these are, none of them have even begun to harness the potential of AI systems like large language models (LLMs).

The challenge for all of us working in education is how we ensure that ethics and privacy are at the centre of the development of [AI-powered edtech].

One area where I think we’ll see huge progress is feedback. It’s well-established that good-quality feedback makes a huge difference to learning, but a teacher’s ability to provide feedback is limited by their time. No one is seriously claiming that chatbots will replace teachers, but — if we can get the quality right — LLM applications could provide every child with unlimited, on-demand feedback. AI-powered feedback — not giving students the answers, but coaching, suggesting, and encouraging in the way that great teachers already do — could be transformational.

Two adults learn about computing at desktop computers.
The challenge for all of us working in education is how we ensure that ethics and privacy are at the centre of the development of AI-powered edtech.

We are already seeing edtech companies racing to bring new products and features to market that leverage LLMs, and my prediction is that the pace of that innovation is going to increase exponentially over the coming years. The challenge for all of us working in education is how we ensure that ethics and privacy are at the centre of the development of these technologies. That’s important for all applications of AI, but especially so in education, where these systems will be unleashed directly on young people. How much data from students will an AI system need to access? Can that data — aggregated from millions of students — be used to train new models? How can we communicate transparently the limitations of the information provided back to students?

Ultimately, we need to think about how parents, teachers, and education systems (the purchasers of edtech products) will be able to make informed choices about what to put in front of students. Standards will have an important role to play here, and I think we should be exploring ideas such as an AI kitemark for edtech products that communicate whether they meet a set of standards around bias, transparency, and privacy. 

Realising potential in a brave new world

We may very well be entering an era in which AI systems dramatically enhance the creativity and productivity of humanity as a species. Whether the reality lives up to the hype or not, AI systems are undoubtedly going to be a big part of all of our futures, and we urgently need to figure out what that means for education, and what skills, knowledge, and mindsets young people need to develop in order to realise their full potential in that brave new world. 

That’s the work we’re engaged in at the Raspberry Pi Foundation, working in partnership with individuals and organisations from across industry, government, education, and civil society.

If you have ideas and want to get involved in shaping the future of computing education, we’d love to hear from you.

This article will also appear in issue 22 of Hello World magazine, which focuses on teaching and AI. We are publishing this new issue on Monday 23 October. Sign up for a free digital subscription to get the PDF straight to your inbox on the day.

The post What does AI mean for computing education? appeared first on Raspberry Pi Foundation.

Young children’s ScratchJr coding projects: Assessment and support

Post Syndicated from Diana Kirby original https://www.raspberrypi.org/blog/childrens-scratchjr-projects-assessment-support/

Block-based programming applications like Scratch and ScratchJr provide millions of children with an introduction to programming; they are a fun and accessible way for beginners to explore programming concepts and start making with code. ScratchJr, in particular, is designed specifically for children between the ages of 5 and 7, enabling them to create their own interactive stories and games. So it’s no surprise that they are popular tools for primary-level (K–5) computing teachers and learners. But how can teachers assess coding projects built in ScratchJr, where the possibilities are many and children are invited to follow their imagination?

Aim Unahalekhala
Aim Unahalekhala

In the latest seminar of our series on computing education for primary-aged children, attendees heard about two research studies that explore the use of ScratchJr in K–2 education. The speaker, Apittha (Aim) Unahalekhala, is a graduate researcher at the DevTech Research Group at Tufts University. The two studies looked at assessing young children’s ScratchJr coding projects and understanding how they create projects. Both of the studies were part of the Coding as Another Language project, which sees computer science as a new literacy for the 21st century, and is developing a literacy-based coding curriculum for K–2.

How to evaluate children’s ScratchJr projects

ScratchJr offers children 28 blocks to choose from when creating a coding project. Some of these are simple, such as blocks that determine the look of a character or setting, while others are more complex, such as messaging blocks and loops. Children can combine the blocks in many different ways to create projects of different levels of complexity.

A child select blocks for a ScratchJr project on a tablet.
Selecting blocks for a ScratchJr project

At the start of her presentation, Aim described a rubric that she and her colleagues at DevTech have developed to assess three key aspects of a ScratchJr coding project. These aspects are coding concepts, project design, and purposefulness.

  • Coding concepts in ScratchJr are sequencing, repeats, events, parallelism, coordination, and the number parameter
  • Project design includes elaboration (number of settings and characters, use of speech bubbles) and originality (character and background customisation, animated looks, sounds)

The rubric lets educators or researchers:

  • Assess learners’ ability to use their coding knowledge to create purposeful and creative ScratchJr projects
  • Identify the level of mastery of each of the three key aspects demonstrated within the project
  • Identify where learners might need more guidance and support
The elements covered by the ScratchJr project evaluation rubric.
The elements covered by the ScratchJr project evaluation rubric. Click to enlarge.

As part of the study, Aim and her colleagues collected coding projects from two schools at the start, middle, and end of a curriculum unit. They used the rubric to evaluate the coding projects and found that project scores increased over the course of the unit.

They also found that, overall, the scores for the project design elements were higher than those for coding concepts: many learners enjoyed spending lots of time designing their characters and settings, but made less use of other features. However, the two scores were correlated, meaning that learners who devoted a lot of time to the design of their project also got higher scores on coding concepts.

The rubric is a useful tool for any teachers using ScratchJr with their students. If you want to try it in your classroom, the validated rubric is free to download from the DevTech research group’s website.

How do young children create a project?

The rubric assesses the output created by a learner using ScratchJr. But learning is a process, not just an end outcome, and the final project might not always be an accurate reflection of a child’s understanding.

By understanding more about how young children create coding projects, we can improve teaching and curriculum design for early childhood computing education.

In the second study Aim presented, she set out to explore this question. She conducted a qualitative observation of children as they created coding projects at different stages of a curriculum unit, and used Google Analytics data to conduct a quantitative analysis of the steps the children took.

A Scratch project creation process involving iteration.
A project creation process involving iteration

Her findings highlighted the importance of encouraging young learners to explore the full variety of blocks available, both by guiding them in how to find and use different blocks, and by giving them the time and tools they need to explore on their own.

She also found that different teaching strategies are needed at different stages of the curriculum unit to support learners. This helps them to develop their understanding of both basic and advanced blocks, and to explore, customise, and iterate their projects.

Early-unit strategy:

  • Encourage free play to self-discover different functions, especially basic blocks

Mid-unit strategy:

  • Set plans on how long children will need on customising vs coding
  • More guidance on the advanced blocks, then let children explore

End-of-unit strategy:

  • Provide multiple sessions to work
  • Promote iteration by encouraging children to keep improving code and adding details
Teaching strategies for different stages of a ScratchJr curriculum.
Teaching strategies for different stages of the curriculum

You can watch Aim’s full presentation here:

You can also access the seminar slides here.

Join our next seminar on primary computing education

At our next seminar, we welcome Aman Yadav (Michigan State University), who will present research on computational thinking in primary school. The session will take place online on Tuesday 7 November at 17:00 UK time. Don’t miss out and sign up now:

I want to sign up to join

To find out more about connecting research to practice for primary computing education, you can find the rest of our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.

The post Young children’s ScratchJr coding projects: Assessment and support appeared first on Raspberry Pi Foundation.

Apply for a free UK teacher’s place at the WiPSCE conference

Post Syndicated from Bonnie Sheppard original https://www.raspberrypi.org/blog/free-uk-teacher-places-wipsce-conference-2023/

From 27 to 29 September 2023, we and the University of Cambridge are hosting the WiPSCE International Workshop on Primary and Secondary Computing Education Research for educators and researchers. This year, this annual conference will take place at Robinson College in Cambridge. We’re inviting all UK-based teachers of computing subjects to apply for one of five ‘all expenses paid’ places at this well-regarded annual event.

Educators and researchers mingle at a conference.

You could attend WiPSCE with all expenses paid

WiPSCE is where teachers and researchers discuss research that’s relevant to teaching and learning in primary and secondary computing education, to teacher training, and to related topics. You can find more information about the conference, including the preliminary programme, at wipsce.org. 

Educators and researchers listen to a talk at a conference.
Educators and researchers mingle at a conference.

As a teacher at the conference, you will:

  • Engage with high-quality international research in the field where you teach
  • Learn ways to use that research to develop your own classroom practice
  • Find out how to become an advocate in your professional community for research-informed approaches to the teaching of computing.

We are delighted that, thanks to generous funding from a funder, we can offer five free places to UK computing teachers, covering:

  • The registration fee
  • Two nights’ accommodation at Robinson College
  • Up to £500 supply costs paid to your school to cover your teaching
  • Up to £100 travel costs
I want to apply for a free place

The application deadline is Wednesday 19 July.

The application details

To be eligible to apply:

  1. You need to be a currently practising, UK-based teacher of Computing (England), Computing Science (Scotland), ICT or Digital Technologies (N. Ireland), or Computer Science (Wales)
  2. Your headteacher needs to be able to provide written confirmation that they are happy for you to attend WiPSCE
  3. You need to be available to attend the whole conference from Wednesday lunchtime to Friday afternoon
  4. You need to be willing to share what you learn from the conference with your colleagues at school and with your broader teaching community, including through writing an article about your experience and its relevance to your teaching for this blog or Hello World magazine

The application form will ask your for:

  • Your name and contact details
  • Demographic and school information
  • Your teaching experience
  • A statement of up to 500 words on why you’re applying and how you think your teaching practice, your school and your colleagues will benefit from your attendance at WiPSCE (500 words is the maximum, feel free to be concise)

After the 19 July deadline, we’re aiming to inform you of the outcome of your application on Friday 21 July. 

Apply today
Information materials at a conference.
Participants at the Clubs Conference.

Your application will be reviewed by the 2023 WiPSCE Chairs:

Sue and Mareen will:

  • Use the information you share in your form, particularly in your statement
  • Select applicants from a mix of primary and secondary schools, with a mix of years of computing teaching experience, and from a mix of geographic areas

Join us in strengthening research-informed computing classroom practice

We’d be delighted to receive your application. Being able to facilitate teachers’ attendance at the conference is very much aligned with our approach to research. Both at the Foundation and the Raspberry Pi Computing Education Research Centre, we’re committed to conducting research that’s directly relevant to schools and teachers, and to working in close collaboration with teachers.

We hope you are interested in attending WiPSCE and becoming an advocate for research-informed computing education practice. If your application is unsuccessful, we hope you consider coming along anyway. We’re looking forward to meeting you there. In the meantime, you can keep up with WiPSCE news on Twitter.

The post Apply for a free UK teacher’s place at the WiPSCE conference appeared first on Raspberry Pi Foundation.

Running a workshop with teachers to create culturally relevant Computing lessons

Post Syndicated from Katharine Childs original https://www.raspberrypi.org/blog/research-teacher-workshop-culturally-relevant-computing-lessons/

Who chooses to study Computing? In England, data from GCSE and A level Computer Science entries in 2019 shows that the answer is complex. Black Caribbean students were one of the most underrepresented groups in the subject, while pupils from other ethnic backgrounds, such as White British, Chinese, and Asian Indian, were well-represented. This picture is reflected in the STEM workforce in England, where Black people are also underrepresented.

Two young girls, one of them with a hijab, do a Scratch coding activity together at a desktop computer.

That’s why one of our areas of academic research aims to support Computing teachers to use culturally relevant pedagogy to design and deliver equitable learning experiences that enable all learners to enjoy and succeed in Computing and Computer Science at school. Our previous research projects within this area have involved developing guidelines for culturally relevant and responsive teaching, and exploring how a small group of primary and secondary Computing teachers used these guidelines in their teaching.

A tree symbolising culturally relevant pedagogy,with the roots labeled 'curriculum, the trunk labeled 'teaching approaches', and the crown labeled 'learning materials'.
Learning materials, teaching approaches, and the curriculum as a whole are three areas where culturally relevance is important.

In our latest research study, funded by Cognizant, we worked with 13 primary school teachers in England on adapting computing lessons to incorporate culturally relevant and responsive principles and practices. Here’s an insight into the workshop we ran with them, and what the teachers and we have taken away from it.

Adapting lesson materials based on culturally relevant pedagogy

In the group of 13 England-based primary school Computing teachers we worked with for this study:

  • One third were specialist primary Computing teachers, and the other two thirds were class teachers who taught a range of subjects
  • Some acted as Computing subject lead or coordinator at their school
  • Most had taught Computing for between three and five years 
  • The majority worked in urban areas of England, at schools with culturally diverse catchment areas 

In November 2022, we held a one-day workshop with the teachers to introduce culturally relevant pedagogy and explore how to adapt two six-week units of computing resources.

An example of a collaborative activity from a teacher-focused workshop around culturally relevant pedagogy.
An example of a collaborative activity from the workshop

The first part of the workshop was a collaborative, discussion-based professional development session exploring what culturally relevant pedagogy is. This type of pedagogy uses equitable teaching practices to:

  • Draw on the breadth of learners’ experiences and cultural knowledge
  • Facilitate projects that have personal meaning for learners
  • Develop learners’ critical consciousness

The rest of the workshop day was spent putting this learning into practice while planning how to adapt two units of computing lessons to make them culturally relevant for the teachers’ particular settings. We used a design-based approach for this part of the workshop, meaning researchers and teachers worked collaboratively as equal stakeholders to decide on plans for how to alter the units.

We worked in four groups, each with three or four teachers and one or two researchers, focusing on one of two units of work from The Computing Curriculum for teaching digital skills: a unit on photo editing for Year 4 (ages 8–9), and a unit about vector graphics for Year 5 (ages 9–10).

Descriptions of a classroom unit of teaching materials about photo editing for Year 4 (ages 8–9), and a unit about vector graphics for Year 5 (ages 9–10).
We based the workshop around two Computing Curriculum units that cover digital literacy skills.

In order to plan how the resources in these units of work could be made culturally relevant for the participating teachers’ contexts, the groups used a checklist of ten areas of opportunity. This checklist is a result of one of our previous research projects on culturally relevant pedagogy. Each group used the list to identify a variety of ways in which the units’ learning objectives, activities, learning materials, and slides could be adapted. Teachers noted down their ideas and then discussed them with their group to jointly agree a plan for adapting the unit.

By the end of the day, the groups had designed four really creative plans for:

  • A Year 4 unit on photo editing that included creating an animal to represent cultural identity
  • A Year 4 unit on photo editing that included creating a collage all about yourself 
  • A Year 5 unit on vector graphics that guided learners to create their own metaverse and then add it to the class multiverse
  • A Year 5 unit on vector graphics that contextualised the digital skills by using them in online activities and in video games

Outcomes from the workshop

Before and after the workshop, we asked the teachers to fill in a survey about themselves, their experiences of creating computing resources, and their views about culturally relevant resources. We then compared the two sets of data to see whether anything had changed over the course of the workshop.

A teacher attending a training workshop laughs as she works through an activity.
The workshop was a positive experience for the teachers.

After teachers had attended the workshop, they reported a statistically significant increase in their confidence levels to adapt resources to be culturally relevant for both themselves and others. 

Teachers explained that the workshop had increased their understanding of culturally relevant pedagogy and of how it could impact on learners. For example, one teacher said:

“The workshop has developed my understanding of how culturally adapted resources can support pupil progress and engagement. It has also highlighted how contextual appropriateness of resources can help children to access resources.” – Participating teacher

Some teachers also highlighted how important it had been to talk to teachers from other schools during the workshop, and how they could put their new knowledge into practice in the classroom:

“The dedicated time and value added from peer discourse helped make this authentic and not just token activities to check a box.” – Participating teacher

“I can’t wait to take some of the work back and apply it to other areas and subjects I teach.” – Participating teacher

What you can expect to see next from this project

After our research team made the adaptations to the units set out in the four plans made during the workshop, the adapted units were delivered by the teachers to more than 500 Year 4 and 5 pupils. We visited some of the teachers’ schools to see the units being taught, and we have interviewed all the teachers about their experience of delivering the adapted materials. This observational and interview data, together with additional survey responses, will be analysed by us, and we’ll share the results over the coming months.

A computing classroom filled with learners
As part of the project, we observed teachers delivering the adapted units to their learners.

In our next blog post about this work, we will delve into the fascinating realm of parental attitudes to culturally relevant computing, and we’ll explore how embracing diversity in the digital landscape is shaping the future for both children and their families. 

We’ve also written about this professional development activity in more detail in a paper to be published at the UKICER conference in September, and we’ll share the paper once it’s available.

Finally, we are grateful to Cognizant for funding this academic research, and to our cohort of primary computing teachers for their enthusiasm, energy, and creativity, and their commitment to this project.

The post Running a workshop with teachers to create culturally relevant Computing lessons appeared first on Raspberry Pi Foundation.

Celebrating the community: Spencer

Post Syndicated from Sophie Ashford original https://www.raspberrypi.org/blog/celebrating-the-community-spencer/

We love hearing from members of the community and how they use their passion for computing and digital making to inspire others. Our community stories series takes you on a tour of the globe to meet educators and young tech creators from the USA, Iraq, Romania, and more.

A smiling computer science teacher stands in front of a school building.

For our latest story, we are in the UK with Spencer, a Computer Science teacher at King Edward VI Sheldon Heath Academy (KESH), Birmingham. After 24 years as a science teacher, Spencer decided to turn his personal passion for digital making into a career and transitioned to teaching Computer Science.

Meet Spencer

From the moment he printed his name on the screen of an Acorn Electron computer at age ten, Spencer was hooked on digital making. He’s remained a member of the digital making community throughout his life, continuing to push himself with his creations and learn new skills whenever possible. Wanting to spread his knowledge and make sure the students at his school had access to computer science, he began running a weekly Code Club in his science lab:

“Code Club was a really nice vehicle for me to get students into programming and digital making, before computer science was an option at the school. So Code Club originally ran in my science lab around the Bunsen burners and all the science equipment, and we do some programming on a Friday afternoon making LEDs flash and a little bit of Minecraft. And from that, the students really got an exciting sense of what programming and digital making could be.”

– Spencer

While running his Code Club, Spencer really embedded himself in the Raspberry Pi community, attending Raspberry Jams, engaging with like-minded people on Twitter, and continuing to rely on our free training to upskill.

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

When leadership at KESH began to explore introducing Computer Science to the curriculum, Spencer knew he was the right person for the job, and just where to look to make sure he had the right support:

“So when I decided to change from being a science teacher to a computer science teacher, there were loads of course options you could find online, and a lot of them required some really specific prior knowledge and skills. The Foundation’s resources take you from a complete novice, complete beginner — my very first LED flashing on and off — to being able to teach computational thinking and algorithms. So it was a really clear progression from using the Foundation resources that helped take me from a Physics teacher, who could use electricity to light and LED on, to a programmer who could teach how to use this in our digital making for our students.”

– Spencer

Thanks to the support from KESH and Spencer’s compelling can-do attitude, he was soon heading up a brand-new Computer Science department. This was met with great enthusiasm from the learners at KESH, with a willing cohort eagerly signing up for the new subject.

Two smiling computer science students at a desktop computer in a classroom.

“It’s really exciting to see how students have embraced Computer Science as a brand-new subject at school. The take-up for our first year at GCSE was fantastic with 25 students, and this year I’ve really got students asking about, ‘Is there an option for next year, and how can I get on to it?’ Students are almost blown away by the resources now.”

– Spencer

Supporting all students

Spencer has a mission to make sure all of KESH’s learners can learn about computing, and making his lessons accessible to all means he’s become a firm favourite amongst the students for his collaborative teaching approach.

“Mr Organ teaches you, and then he just puts you in. If you do need help, you can ask people around you, or him, but he lets you make your own mistakes and learn from there. He will then give you help so you don’t make those mistakes the next time.”

– Muntaha, 16, GCSE Computer Science student, KESH

Computer science students at a desktop computer in a classroom.

Spencer’s work is shaped by his awareness that many of the learners at KESH come from under-resourced areas of Birmingham and backgrounds that are underrepresented in computing. He knows that many of them have previously had limited opportunities to use digital tools. This is something he is driven to change.

“I want my young students here, regardless of their background, regardless of their area they’ve been brought up in, to have the same experiences as all other students in the country. And the work I do with Raspberry Pi, and the work I do with Code Club, is a way of opening those doors for our young people.”

– Spencer

Share Spencer’s story and inspire other educators

As a passionate member of the Raspberry Pi Foundation community, Spencer has been counted on as a friendly face for many years, sharing his enthusiasm on training courses, at Foundation events, and as a part of discussions on Twitter. With the goal to introduce Computer Science at A level shortly, and an ever-growing collection of digital makes housed in his makerspace, Spencer shows no signs of slowing down.

If you are interested in changing your teaching path to focus on Computer Science, take a look at the free resources we have available to support you on your journey.

Help us celebrate Spencer and his dedication to opening doors for his learners by sharing his story on Twitter, LinkedIn, and Facebook.

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How we’re learning to explain AI terms for young people and educators

Post Syndicated from Veronica Cucuiat original https://www.raspberrypi.org/blog/explaining-ai-terms-young-people-educators/

What do we talk about when we talk about artificial intelligence (AI)? It’s becoming a cliche to point out that, because the term “AI” is used to describe so many different things nowadays, it’s difficult to know straight away what anyone means when they say “AI”. However, it’s true that without a shared understanding of what AI and related terms mean, we can’t talk about them, or educate young people about the field.

A group of young people demonstrate a project at Coolest Projects.

So when we started designing materials for the Experience AI learning programme in partnership with leading AI unit Google DeepMind, we decided to create short explanations of key AI and machine learning (ML) terms. The explanations are doubly useful:

  1. They ensure that we give learners and teachers a consistent and clear understanding of the key terms across all our Experience AI resources. Within the Experience AI Lessons for Key Stage 3 (age 11–14), these key terms are also correlated to the target concepts and learning objectives presented in the learning graph. 
  2. They help us talk about AI and AI education in our team. Thanks to sharing an understanding of what terms such as “AI”, “ML”, “model”, or “training” actually mean and how to best talk about AI, our conversations are much more productive.

As an example, here is our explanation of the term “artificial intelligence” for learners aged 11–14:

Artificial intelligence (AI) is the design and study of systems that appear to mimic intelligent behaviour. Some AI applications are based on rules. More often now, AI applications are built using machine learning that is said to ‘learn’ from examples in the form of data. For example, some AI applications are built to answer questions or help diagnose illnesses. Other AI applications could be built for harmful purposes, such as spreading fake news. AI applications do not think. AI applications are built to carry out tasks in a way that appears to be intelligent.

You can find 32 explanations in the glossary that is part of the Experience AI Lessons. Here’s an insight into how we arrived at the explanations.

Reliable sources

In order to ensure the explanations are as precise as possible, we first identified reliable sources. These included among many others:

Explaining AI terms to Key Stage 3 learners: Some principles

Vocabulary is an important part of teaching and learning. When we use vocabulary correctly, we can support learners to develop their understanding. If we use it inconsistently, this can lead to alternate conceptions (misconceptions) that can interfere with learners’ understanding. You can read more about this in our Pedagogy Quick Read on alternate conceptions.

Some of our principles for writing explanations of AI terms were that the explanations need to: 

  • Be accurate
  • Be grounded in education research best practice
  • Be suitable for our target audience (Key Stage 3 learners, i.e. 11- to 14-year-olds)
  • Be free of terms that have alternative meanings in computer science, such as “algorithm”

We engaged in an iterative process of writing explanations, gathering feedback from our team and our Experience AI project partners at Google DeepMind, and adapting the explanations. Then we went through the feedback and adaptation cycle until we all agreed that the explanations met our principles.

A real banana and an image of a banana shown on the screen of a laptop are both labelled "Banana".
Image: Max Gruber / Better Images of AI / Ceci n’est pas une banane / CC-BY 4.0

An important part of what emerged as a result, aside from the explanations of AI terms themselves, was a blueprint for how not to talk about AI. One aspect of this is avoiding anthropomorphism, detailed by Ben Garside from our team here.

As part of designing the the Experience AI Lessons, creating the explanations helped us to:

  • Decide which technical details we needed to include when introducing AI concepts in the lessons
  • Figure out how to best present these technical details
  • Settle debates about where it would be appropriate, given our understanding and our learners’ age group, to abstract or leave out details

Using education research to explain AI terms

One of the ways education research informed the explanations was that we used semantic waves to structure each term’s explanation in three parts: 

  1. Top of the wave: The first one or two sentences are a high-level abstract explanation of the term, kept as short as possible, while introducing key words and concepts.
  2. Bottom of the wave: The middle part of the explanation unpacks the meaning of the term using a common example, in a context that’s familiar to a young audience. 
  3. Top of the wave: The final one or two sentences repack what was explained in the example in a more abstract way again to reconnect with the term. The end part should be a repeat of the top of the wave at the beginning of the explanation. It should also add further information to lead to another concept. 

Most explanations also contain ‘middle of the wave’ sentences, which add additional abstract content, bridging the ‘bottom of the wave’ concrete example to the ‘top of the wave’ abstract content.

Here’s the “artificial intelligence” explanation broken up into the parts of the semantic wave:

  • Artificial intelligence (AI) is the design and study of systems that appear to mimic intelligent behaviour. (top of the wave)
  • Some AI applications are based on rules. More often now, AI applications are built using machine learning that is said to ‘learn’ from examples in the form of data. (middle of the wave)
  • For example, some AI applications are built to answer questions or help diagnose illnesses. Other AI applications could be built for harmful purposes, such as spreading fake news (bottom of the wave)
  • AI applications do not think. (middle of the wave)
  • AI applications are built to carry out tasks in a way that appears to be intelligent. (top of the wave)
Our "artificial intelligence" explanation broken up into the parts of the semantic wave.
Our “artificial intelligence” explanation broken up into the parts of the semantic wave. Red = top of the wave; yellow = middle of the wave; green = bottom of the wave

Was it worth our time?

Some of the explanations went through 10 or more iterations before we agreed they were suitable for publication. After months of thinking about, writing, correcting, discussing, and justifying the explanations, it’s tempting to wonder whether I should have just prompted an AI chatbot to generate the explanations for me.

A window of three images. On the right is a photo of a big tree in a green field in a field of grass and a bright blue sky. The two on the left are simplifications created based on a decision tree algorithm. The work illustrates a popular type of machine learning model: the decision tree. Decision trees work by splitting the population into ever smaller segments. I try to give people an intuitive understanding of the algorithm. I also want to show that models are simplifications of reality, but can still be useful, or in this case visually pleasing. To create this I trained a model to predict pixel colour values, based on an original photograph of a tree.
Rens Dimmendaal & Johann Siemens / Better Images of AI / Decision Tree reversed / CC-BY 4.0

I tested this idea by getting a chatbot to generate an explanation of “artificial intelligence” using the prompt “Explain what artificial intelligence is, using vocabulary suitable for KS3 students, avoiding anthropomorphism”. The result included quite a few inconsistencies with our principles, as well as a couple of technical inaccuracies. Perhaps I could have tweaked the prompt for the chatbot in order to get a better result. However, relying on a chatbot’s output would mean missing out on some of the value of doing the work of writing the explanations in collaboration with my team and our partners.

The visible result of that work is the explanations themselves. The invisible result is the knowledge we all gained, and the coherence we reached as a team, both of which enabled us to create high-quality resources for Experience AI. We wouldn’t have gotten to know what resources we wanted to write without writing the explanations ourselves and improving them over and over. So yes, it was worth our time.

What do you think about the explanations?

The process of creating and iterating the AI explanations highlights how opaque the field of AI still is, and how little we yet know about how best to teach and learn about it. At the Raspberry Pi Foundation, we now know just a bit more about that and are excited to share the results with teachers and young people.

You can access the Experience AI Lessons and the glossary with all our explanations at experience-ai.org. The glossary of AI explanations is just in its first published version: we will continue to improve it as we find out more about how to best support young people to learn about this field.

Let us know what you think about the explanations and whether they’re useful in your teaching. Onwards with the exciting work of establishing how to successfully engage young people in learning about and creating with AI technologies.

The post How we’re learning to explain AI terms for young people and educators appeared first on Raspberry Pi Foundation.

Introducing the Hello World newsletter

Post Syndicated from Gemma Coleman original https://www.raspberrypi.org/blog/hello-world-newsletter/

Launched six years ago, Hello World magazine is the education magazine about computing and digital making. It’s made for educators by educators, and a community of teachers around the world reads and contributes to every issue. We’re now starting a monthly Hello World newsletter to bring you more great content for computing educators while you await each new magazine issue.

Cover of Hello World issue 21.
Cover of The Big Book of Computing Content.
Cover of The Big Book of Computing Pedagogy.

A monthly newsletter for Hello World readers

The Hello World community is an amazing group of people, and we love hearing your ideas about what could make Hello World even better at supporting your classroom practice. That’s why we host a fun and informative Hello World podcast to chat with educators around the globe about all things computing and digital making, and why we regularly share some of our favourite past magazine articles online to keep the conversation on important topics going.

Now we’re starting a monthly newsletter to offer you another way to get regular computing education ideas and insights you can use in your teaching. Every month, we’ll be curating a couple of interesting Hello World articles, plus news about the free education resources, research, community stories, and events from the Foundation. You can expect bite-size summaries of all items, plus links for you to explore more in your own time.

Sign up today

Keep up with all of the education news from the Raspberry Pi Foundation and Hello World by signing up for the Hello World newsletter today.

I want to sign up

If you’re already signed up to the Raspberry Pi LEARN newsletter, then you don’t need to do anything: this newsletter replaces LEARN and you will be automatically subscribed.

We hope you’ll enjoy the first Hello World newsletter, which we will send out this Wednesday. As always, let us know what you think of it on Twitter or Facebook, or here in the comments.

PS Remember that if you work or volunteer as an educator in the UK, you can subscribe to receive free Hello World print copies to your home or workplace.

The post Introducing the Hello World newsletter appeared first on Raspberry Pi Foundation.

Hello World #21 out now: Focus on primary computing education

Post Syndicated from Gemma Coleman original https://www.raspberrypi.org/blog/hello-world-21-primary-computing-education/

How do we best prepare young children for a world filled with digital technology? This is the question the writers in our newest issue of Hello World respond to with inspiration and ideas for computing education in primary school.

Cover of Hello World issue 21.

It is vital that young children gain good digital literacy skills and understanding of computing concepts, which they can then build on as they grow up. Digital technology is here to stay, and as Sethi De Clercq points out in his article, we need to prepare our youngest learners for circumstances and jobs that don’t yet exist.

In a computing classroom, a boy looks down at a keyboard.
A group of young people work together at a computer.

Primary computing education: Inspiration and ideas

Issue 21 of Hello World covers a big range of topics in the theme of primary computing education, including:

  • Cross-curricular project ideas to keep young learners engaged
  • Perfecting typing skills in the primary school classroom
  • Using picture books to introduce programming concepts to children
  • Toolkits for new and experienced computing primary teachers, by Neil Rickus and Catherine Archer
  • Explorations of different approaches to improving diversity in computing and instilling a sense of belonging from the very start of a child’s educational journey, by Chris Lovell and Peter Marshman

The issue also has useful news and updates about our work: we share insights from our primary-specialist learning managers, tell you a bit about the research presented at our ongoing primary education seminar series, and include some relevant lesson plans from The Computing Curriculum.

A child at a laptop in a classroom in rural Kenya.

As always, you’ll find many other articles to support and inspire you in your computing teaching in this new issue. Topics include programming with dyslexia, exploring filter bubbles with your learners to teach them about data science, and using metaphors, similes, and analogies to help your learners understand abstract concepts.

I want to download Hello World 21

What do you think?

This issue of Hello World focusses on primary computing education because readers like you told us in the annual readers’ survey that they’d like more articles for primary teachers.

We love to hear your ideas about what we can do to continue making Hello World interesting and relevant for you. So please get in touch on Twitter with your thoughts and suggestions.

The post Hello World #21 out now: Focus on primary computing education appeared first on Raspberry Pi Foundation.

Preparing young children for a digital world | Hello World #21

Post Syndicated from Sway Grantham original https://www.raspberrypi.org/blog/preparing-young-children-digital-world-hello-world-21/

How do we teach our youngest learners digital and computing skills? Hello World‘s issue 21 will focus on this question and all things primary school computing education. We’re excited to share this new issue with you on Tuesday 30 May. Today we’re giving you a taste by sharing an article from it, written by our own Sway Grantham.

Cover of Hello World issue 21.

How are you preparing young children for a world filled with digital technology? Technology use of our youngest learners is a hotly debated topic. From governments to parents and from learning outcomes to screen-time rules, everyone has an opinion on the ‘right’ approach. Meanwhile, many young children encounter digital technology as a part of their world at home. For example in the UK, 87 percent of 3- to 4-year-olds and 93 percent of 5- to 7-year-olds went online at home in 2023. Schools should be no different.

A girl doing digital making on a tablet

As educators, we have a responsibility to prepare learners for life in a digital world. We want them to understand its uses, to be aware of its risks, and to have access to the wide range of experiences unavailable without it. And we especially need to consider the children who do not encounter technology at home. Education should be a great equaliser, so we need to ensure all our youngest learners have access to the skills they need to realise their full potential.

Exploring technology and the world

A major aspect of early-years or kindergarten education is about learners sharing their world with each other and discovering that everyone has different experiences and does things in their own way. Using digital technology is no different.

Allowing learners to share their experiences of using digital technology both accepts the central role of technology in our lives today and also introduces them to its broader uses in helping people to learn, talk to others, have fun, and do work. At home, many young learners may use technology to do just one of these things. Expanding their use of technology can encourage them to explore a wider range of skills and to see technology differently.

A girl shows off a robot she has built.

In their classroom environment, these explorations can first take place as part of the roleplay area of a classroom, where learners can use toys to show how they have seen people use technology. It may seem counterintuitive that play-based use of non-digital toys can contribute to reducing the digital divide, but if you don’t know what technology can do, how can you go about learning to use it? There is also a range of digital roleplay apps (such as the Toca Boca apps) that allow learners to recreate their experiences of real-world situations, such as visiting the hospital, a hair salon, or an office. Such apps are great tools for extending roleplay areas beyond the resources you already have.

Another aspect of a child’s learning that technology can facilitate is their understanding of the world beyond their local community. Technology allows learners to explore the wider world and follow their interests in ways that are otherwise largely inaccessible. For example:

  • Using virtual reality apps, such as Expeditions Pro, which lets learners explore Antarctica or even the bottom of the ocean
  • Using augmented reality apps, such as Octagon Studio’s 4D+ cards, which make sea creatures and other animals pop out of learners’ screens
  • Doing a joint project with a class of children in another country, where learners blog or share ‘email’ with each other

Each of these opportunities gives children a richer understanding of the world while they use technology in meaningful ways.

Technology as a learning tool

Beyond helping children to better understand our world, technology offers opportunities to be expressive and imaginative. For example, alongside your classroom art activities, how about using an app like Draw & Tell, which helps learners draw pictures and then record themselves explaining what they are drawing? Or what about using filters on photographs to create artistic portraits of themselves or their favourite toys? Digital technology should be part of the range of tools learners can access for creative play and expression, particularly where it offers opportunities that analogue tools don’t.

Young learners at computers in a classroom.

Using technology is also invaluable for learners who struggle with communication and language skills. When speaking is something you find challenging, it can often be intimidating to talk to others who speak much more confidently. But speaking to a tablet? A tablet only speaks as well as you do. Apps to record sounds and listen back to them are a helpful way for young children to learn about how clear their speech is and practise speech exercises. ChatterPix Kids is a great tool for this. It lets learners take a photo of an object, e.g. their favourite soft toy, and record themselves talking about it. When they play back the recording, the app makes it look like the toy is saying their words. This is a very engaging way for young learners to practise communicating.

Technology is part of young people’s world

No matter how we feel about the role of technology in the lives of young people, it is a part of their world. We need to ensure we are giving all learners opportunities to develop digital skills and understand the role of technology, including how people can use it for social good.

A woman and child follow instructions to build a digital making project at South London Raspberry Jam.

This is not just about preparing them for their computing education (although that’s definitely a bonus!) or about online safety (although this is vital — see my articles in Hello World issue 15 and issue 19 for more about the topic). It’s about their right to be active citizens in the digital world.

So I ask again: how are you preparing young children for a digital world?

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The first experiences children have with learning about computing and digital technologies are formative. That’s why primary computing education should be of interest to all educators, no matter what the age of your learners is. This issue covers for example:

And there’s much more besides. So don’t miss out on this upcoming issue of Hello World — subscribe for free today to receive every PDF edition in your inbox on the day of publication.

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The post Preparing young children for a digital world | Hello World #21 appeared first on Raspberry Pi Foundation.

Introducing data science concepts and skills to primary school learners

Post Syndicated from Katharine Childs original https://www.raspberrypi.org/blog/data-science-data-literacy-primary-school-scotland/

Every day, most of us both consume and create data. For example, we interpret data from weather forecasts to predict our chances of a good weather for a special occasion, and we create data as our carbon footprint leaves a trail of energy consumption information behind us. Data is important in our lives, and countries around the world are expanding their school curricula to teach the knowledge and skills required to work with data, including at primary (K–5) level.

Kate Farrell
Kate Farrell
Prof. Judy Robertson

In our most recent research seminar, attendees heard about a research-based initiative called Data Education in Schools. The speakers, Kate Farrell and Professor Judy Robertson from the University of Edinburgh, Scotland, shared how this project aims to empower learners to develop data literacy skills and succeed in a data-driven world.

“Data literacy is the ability to ask questions, collect, analyse, interpret and communicate stories about data.”

– Kate Farrell & Prof. Judy Robertson

Being a data citizen

Scotland’s national curriculum does not explicitly mention data literacy, but the topic is embedded in many subjects such as Maths, English, Technologies, and Social Studies. Teachers in Scotland, particularly in primary schools, have the flexibility to deliver learning in an interdisciplinary way through project-based learning. Therefore, the team behind Data Education in Schools developed a set of cross-curricular data literacy projects. Educators and education policy makers in other countries who are looking to integrate computing topics with other subjects may also be interested in this approach.

Becoming a data citizen involves finding meaning in data, controlling your personal data trail, being a critical consumer of data, and taking action based on data.
Data citizens have skills they need to thrive in a world shaped by digital technology.

The Data Education in Schools projects are aimed not just at giving learners skills they may need for future jobs, but also at equipping them as data citizens in today’s world. A data citizen can think critically, interpret data, and share insights with others to effect change.

Kate and Judy shared an example of data citizenship from a project they had worked on with a primary school. The learners gathered data about how much plastic waste was being generated in their canteen. They created a data visualisation in the form of a giant graph of types of rubbish on the canteen floor and presented this to their local council.

A child arranges objects to visualise data.
Sorting food waste from lunch by type of material

As a result, the council made changes that reduced the amount of plastic used in the canteen. This shows how data citizens are able to communicate insights from data to influence decisions.

A cycle for data literacy projects

Across its projects, the Data Education in Schools initiative uses a problem-solving cycle called the PPDAC cycle. This cycle is a useful tool for creating educational resources and for teaching, as you can use it to structure resources, and to concentrate on areas to develop learner skills.

The PPDAC project cycle.
The PPDAC data problem-solving cycle

The five stages of the cycle are: 

  1. Problem: Identifying the problem or question to be answered
  2. Plan: Deciding what data to collect or use to answer the question
  3. Data: Collecting the data and storing it securely
  4. Analysis: Preparing, modelling, and visualising the data, e.g. in a graph or pictogram
  5. Conclusion: Reviewing what has been learned about the problem and communicating this with others 

Smaller data literacy projects may focus on one or two stages within the cycle so learners can develop specific skills or build on previous learning. A large project usually includes all five stages, and sometimes involves moving backwards — for example, to refine the problem — as well as forwards.

Data literacy for primary school learners

At primary school, the aim of data literacy projects is to give learners an intuitive grasp of what data looks like and how to make sense of graphs and tables. Our speakers gave some great examples of playful approaches to data. This can be helpful because younger learners may benefit from working with tangible objects, e.g. LEGO bricks, which can be sorted by their characteristics. Kate and Judy told us about one learner who collected data about their clothes and drew the results in the form of clothes on a washing line — a great example of how tangible objects also inspire young people’s creativity.

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

As learners get older, they can begin to work with digital data, including data they collect themselves using physical computing devices such as BBC micro:bit microcontrollers or Raspberry Pi computers.

Free resources for primary (and secondary) schools

For many attendees, one of the highlights of the seminar was seeing the range of high-quality teaching resources for learners aged 3–18 that are part of the Data Education in Schools project. These include: 

  • Data 101 videos: A set of 11 videos to help primary and secondary teachers understand data literacy better.
  • Data literacy live lessons: Data-related activities presented through live video.
  • Lesson resources: Lots of projects to develop learners’ data literacy skills. These are mapped to the Scottish primary and secondary curriculum, but can be adapted for use in other countries too.

More resources are due to be published later in 2023, including a set of prompt cards to guide learners through the PPDAC cycle, a handbook for teachers to support the teaching of data literacy, and a set of virtual data-themed escape rooms.  

You may also be interested in the units of work on data literacy skills that are part of The Computing Curriculum, our complete set of classroom resources to teach computing to 5- to 16-year-olds.

Join our next seminar on primary computing education

At our next seminar we welcome Aim Unahalekhaka from Tufts University, USA, who will share research about a rubric to evaluate young learners’ ScratchJr projects. If you have a tablet with ScratchJr installed, make sure to have it available to try out some activities. The seminar will take place online on Tuesday 6 June at 17.00 UK time, sign up now to not miss out.

I want to sign up for the next seminar

To find out more about connecting research to practice for primary computing education, you can see a list of our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.

The post Introducing data science concepts and skills to primary school learners appeared first on Raspberry Pi Foundation.

Integrating primary computing and literacy through multimodal storytelling

Post Syndicated from Veronica Cucuiat original https://www.raspberrypi.org/blog/primary-computing-programming-literacy-storytelling/

Broadening participation and finding new entry points for young people to engage with computing is part of how we pursue our mission here at the Raspberry Pi Foundation. It was also the focus of our March online seminar, led by our own Dr Bobby Whyte. In this third seminar of our series on computing education for primary-aged children, Bobby presented his work on ‘designing multimodal composition activities for integrated K-5 programming and storytelling’. In this research he explored the integration of computing and literacy education, and the implications and limitations for classroom practice.

Young learners at computers in a classroom.

Motivated by challenges Bobby experienced first-hand as a primary school teacher, his two studies on the topic contribute to the body of research aiming to make computing less narrow and difficult. In this work, Bobby integrated programming and storytelling as a way of making the computing curriculum more applicable, relevant, and contextualised.

Critically for computing educators and researchers in the area, Bobby explored how theories related to ‘programming as writing’ translate into practice, and what the implications of designing and delivering integrated lessons in classrooms are. While the two studies described here took place in the context of UK schooling, we can learn universal lessons from this work.

What is multimodal composition?

In the seminar Bobby made a distinction between applying computing to literacy (or vice versa) and true integration of programming and storytelling. To achieve true integration in the two studies he conducted, Bobby used the idea of ‘multimodal composition’ (MMC). A multimodal composition is defined as “a composition that employs a variety of modes, including sound, writing, image, and gesture/movement [… with] a communicative function”.

Storytelling comes together with programming in a multimodal composition as learners create a program to tell a story where they:

  • Decide on content and representation (the characters, the setting, the backdrop)
  • Structure text they’ve written
  • Use technical aspects (i.e. motion blocks, tension) to achieve effects for narrative purposes
A screenshot showing a Scratch project.
Defining multimodal composition (MMC) for a visual programming context

Multimodality for programming and storytelling in the classroom

To investigate the use of MMC in the classroom, Bobby started by designing a curriculum unit of lessons. He mapped the unit’s MMC activities to specific storytelling and programming learning objectives. The MMC activities were designed using design-based research, an approach in which something is designed and tested iteratively in real-world contexts. In practice that means Bobby collaborated with teachers and students to analyse, evaluate, and adapt the unit’s activities.

A list of learning objectives that could be covered by a multimodal composition activity.
Mapping of the MMC activities to storytelling and programming learning objectives

The first of two studies to explore the design and implementation of MMC activities was conducted with 10 K-5 students (age 9 to 11) and showed promising results. All students approached the composition task multimodally, using multiple representations for specific purposes. In other words, they conveyed different parts of their stories using either text, sound, or images.

Bobby found that broadcast messages and loops were the least used blocks among the group. As a consequence, he modified the curriculum unit to include additional scaffolding and instructional support on how and why the students might embed these elements.

A list of modifications to the MMC curriculum unit based on testing in a classroom.
Bobby modified the classroom unit based on findings from his first study

In the second study, the MMC activities were evaluated in a classroom of 28 K-5 students led by one teacher over two weeks. Findings indicated that students appreciated the longer multi-session project. The teacher reported being satisfied with the project work the learners completed and the skills they practised. The teacher also further integrated and adapted the unit into their classroom practice after the research project had been completed.

How might you use these research findings?

Factors that impacted the integration of storytelling and programming included the teacher’s confidence to teach programming as well as the teacher’s ability to differentiate between students and what kind of support they needed depending on their previous programming experience.

In addition, there are considerations regarding the curriculum. The school where the second study took place considered the activities in the unit to be literacy-light, as the English literacy curriculum is ‘text-heavy’ and the addition of multimodal elements ‘wastes’ opportunities to produce stories that are more text-based.

Woman teacher and female student at a laptop.

Bobby’s research indicates that MMC provides useful opportunities for learners to simultaneously pursue storytelling and programming goals, and the curriculum unit designed in the research proved adaptable for the teacher to integrate into their classroom practice. However, Bobby cautioned that there’s a need to carefully consider both the benefits and trade-offs when designing cross-curricular integration projects in order to ensure a fair representation of both subjects.

Can you see an opportunity for integrating programming and storytelling in your classroom? Let us know your thoughts or questions in the comments below.

You can watch Bobby’s full presentation:

And you can read his research paper Designing for Integrated K-5 Computing and Literacy through Story-making Activities (open access version).

You may also be interested in our pilot study on using storytelling to teach computing in primary school, which we conducted as part of our Gender Balance in Computing programme.

Join our next seminar on primary computing education

At our next seminar, we welcome Kate Farrell and Professor Judy Robertson (University of Edinburgh). This session will introduce you to how data literacy can be taught in primary and early-years education across different curricular areas. It will take place online on Tuesday 9 May at 17.00 UK time, don’t miss out and sign up now.

I want to sign up to join the seminar

Yo find out more about connecting research to practice for primary computing education, you can find other our upcoming monthly seminars on primary (K–5) teaching and learning and watch the recordings of previous seminars in this series.

The post Integrating primary computing and literacy through multimodal storytelling appeared first on Raspberry Pi Foundation.

Experience AI: The excitement of AI in your classroom

Post Syndicated from Duncan Maidens original https://www.raspberrypi.org/blog/experience-ai-launch-lessons/

We are delighted to announce that we’ve launched Experience AI, our new learning programme to help educators to teach, inspire, and engage young people in the subject of artificial intelligence (AI) and machine learning (ML).

Experience AI is a new educational programme that offers cutting-edge secondary school resources on AI and machine learning for teachers and their students. Developed in partnership by the Raspberry Pi Foundation and DeepMind, the programme aims to support teachers in the exciting and fast-moving area of AI, and get young people passionate about the subject.

The importance of AI and machine learning education

Artificial intelligence and machine learning applications are already changing many aspects of our lives. From search engines, social media content recommenders, self-driving cars, and facial recognition software, to AI chatbots and image generation, these technologies are increasingly common in our everyday world.

Young people who understand how AI works will be better equipped to engage with the changes AI applications bring to the world, to make informed decisions about using and creating AI applications, and to choose what role AI should play in their futures. They will also gain critical thinking skills and awareness of how they might use AI to come up with new, creative solutions to problems they care about.

The AI applications people are building today are predicted to affect many career paths. In 2020, the World Economic Forum estimated that AI would replace some 85 million jobs by 2025 and create 97 million new ones. Many of these future jobs will require some knowledge of AI and ML, so it’s important that young people develop a strong understanding from an early age.

A group of young people investigate computer hardware together.
 Develop a strong understanding of the concepts of AI and machine learning with your learners.

Experience AI Lessons

Something we get asked a lot is: “How do I teach AI and machine learning with my class?”. To answer this question, we have developed a set of free lessons for secondary school students (age 11 to 14) that give you everything you need including lesson plans, slide decks, worksheets, and videos.

The lessons focus on relatable applications of AI and are carefully designed so that teachers in a wide range of subjects can use them. You can find out more about how we used research to shape the lessons and how we aim to avoid misconceptions about AI.

The lessons are also for you if you’re an educator or volunteer outside of a school setting, such as in a coding club.

The six lessons

  1. What is AI?: Learners explore the current context of artificial intelligence (AI) and how it is used in the world around them. Looking at the differences between rule-based and data-driven approaches to programming, they consider the benefits and challenges that AI could bring to society. 
  2. How computers learn: Learners focus on the role of data-driven models in AI systems. They are introduced to machine learning and find out about three common approaches to creating ML models. Finally the learners explore classification, a specific application of ML.
  3. Bias in, bias out: Learners create their own machine learning model to classify images of apples and tomatoes. They discover that a limited dataset is likely to lead to a flawed ML model. Then they explore how bias can appear in a dataset, resulting in biased predictions produced by a ML model.
  4. Decision trees: Learners take their first in-depth look at a specific type of machine learning model: decision trees. They see how different training datasets result in the creation of different ML models, experiencing first-hand what the term ‘data-driven’ means. 
  5. Solving problems with ML models: Learners are introduced to the AI project lifecycle and use it to create a machine learning model. They apply a human-focused approach to working on their project, train a ML model, and finally test their model to find out its accuracy.
  6. Model cards and careers: Learners finish the AI project lifecycle by creating a model card to explain their machine learning model. To finish off the unit, they explore a range of AI-related careers, hear from people working in AI research at DeepMind, and explore how they might apply AI and ML to their interests.

As part of this exciting first phase, we’re inviting teachers to participate in research to help us further develop the resources. All you need to do is sign up through our website, download the lessons, use them in your classroom, and give us your valuable feedback.

I want to access the Experience AI lessons
An educator points to an image on a student's computer screen.
 Ben Garside, one of our lead educators working on Experience AI, takes a group of students through one of the new lessons.

Support for teachers

We’ve designed the Experience AI lessons with teacher support in mind, and so that you can deliver them to your learners aged 11 to 14 no matter what your subject area is. Each of the lesson plans includes a section that explains new concepts, and the slide decks feature embedded videos in which DeepMind’s AI researchers describe and bring these concepts to life for your learners.

We will also be offering you a range of new teacher training opportunities later this year, including a free online CPD course — Introduction to AI and Machine Learning — and a series of AI-themed webinars.

Tell us your feedback

We will be inviting schools across the UK to test and improve the Experience AI lessons through feedback. We are really looking forward to working with you to shape the future of AI and machine learning education.

Visit the Experience AI website today to get started.

The post Experience AI: The excitement of AI in your classroom appeared first on Raspberry Pi Foundation.