At the heart of our efforts lies a simple yet powerful vision: to ensure every young person develops the knowledge, skills, and confidence to use digital technologies effectively. This includes understanding societal and ethical issues, using technology for creative problem solving, and fostering a mindset of adaptability that will enable them to thrive amid rapid technological change.

A vision for global computing education

To realise this vision, we developed The Computing Curriculum (TCC). Launched in 2018 as part of the UK’s National Centre for Computing Education, TCC is a comprehensive set of free teaching resources tailored for students aged 5–16. Over the years, the curriculum has evolved through rigorous testing and teacher feedback, which has helped to make it one of the most effective and inclusive computing education tools globally.

Contextualising computing education for India

India’s vast diversity — in languages, social and economic contexts, and educational infrastructure — creates unique challenges and opportunities. As a result, we at the Raspberry Pi Foundation have adapted and localised our computing curriculum to meet the needs of Indian students. Collaborations with the Telangana Social Welfare Residential Educational Institutions Society (TGSWREIS) and the Odisha Mo School programme have been pivotal in this endeavour.

In Telangana, we adapted TCC to create a 70+ hour computing curriculum designed for government schools with limited resources. Similarly, in Odisha, elements of this curriculum have been tailored to develop Kaushali, an IT and coding curriculum for over 8,000 state schools. This localised approach ensures that computing education becomes accessible and relevant for students across India.

A curriculum designed for impact

The computing curriculum for India spans Grades 6 to 10 (age group 11-16) and is structured to ensure progressive learning. Students revisit foundational concepts repeatedly, building on prior knowledge as they advance through the grades. The curriculum emphasises forming a strong understanding of concepts over rote learning and integrates research-informed pedagogical approaches.

We tested our localised curriculum resources in Telangana Coding Academy, and there was lots of positive feedback from educators and observers. Overall, the educators were happy with the content format, and the observers noted that students enjoyed learning and completing the activities. This was also evident from the student discussion notes and student survey responses.

“[…] this content is more than what we are expecting for the school years[…] this time they [are] having [a] practical session. So they are very happy to do it and whenever they are free[,] they will come and ask us. ‘[C]an you take [an] extra class for us?’” – Educator

“[…] They are very [appreciative of] the content and [t]hey [are] learning very well, and the response is very good.” – Educator

Key features of the curriculum:

• Tailored content: Materials are customised to align with the proficiency levels and contexts of Indian students, ensuring accessibility
• Localised examples: By incorporating culturally relevant examples, students find the learning experience relatable and engaging
• Simplified language: Designed for students who may lack confidence in English, the curriculum employs clear and concise language for better comprehension
• Hands-on learning: Practical activities, including projects and model creation, solidify understanding and foster creativity
• Ready-to-use resources: Teachers are equipped with lesson plans, presentations, worksheets, and activity sheets, reducing preparation time and enhancing delivery

Learning objectives:
The curriculum focuses on equipping students with:

• An understanding of digital systems and their impact on people and society
• Computational thinking and problem-solving skills for real-world applications
• Confidence and knowledge to become creators and innovators
• Awareness of digital citizenship and responsible technology use

Curriculum structure:
Each academic year includes 30–34 sessions, each lasting 45–60 minutes. Lessons are structured into deliverable units comprising detailed plans, presentations, and worksheets. Both plugged (computer-based) and unplugged (activity-based) learning methods are used, with a 60:40 ratio, ensuring balanced and inclusive learning experiences.

Sample progression across grades:

Curriculum highlights

Grade 6: Building a foundation

Students develop foundational computer skills, learn basic text formatting, and explore introductory programming concepts using Scratch. They also begin to understand how to group and describe objects based on their properties.  

Grade 7: Expanding horizons

Students delve into computer networks, the internet, and the World Wide Web. They learn to use loops in Scratch programming and explore data organisation using flat-file databases and spreadsheets.  

Grade 8: Deepening understanding

Students gain a deeper understanding of how computer systems function and use spreadsheets for data analysis. They continue to build their programming skills in Scratch, focusing on sequences, variables, and selection. They are also introduced to HTML and CSS for basic web development.  

Grade 9: Exploring advanced concepts

Students learn about data representation, including binary and character coding schemes. They design and create websites using HTML and CSS, incorporating accessibility and good web design principles. They also explore the layers of computing systems, including hardware, operating systems, and logic circuits.  

Grade 10: Applying knowledge and skills

Students explore advanced data representation, including image and sound representation. They are introduced to cybersecurity concepts and delve deeper into Python programming, focusing on selection and iteration. They also learn about data science and how to create a blog to support a cause.

Assessment framework:
To measure student progress effectively, the curriculum incorporates both formative and summative assessments:

• Formative assessments: Embedded in lessons to monitor progress and identify misconceptions early.
• Summative assessments: Provide a holistic overview of learning outcomes through tools like multiple-choice quizzes and rubrics. These assessments focus on understanding concepts and skills, moving beyond mere code writing.

Bridging the digital divide

Our localised computing curriculum is more than a technical education initiative — it is helping to bridge the digital divide. By empowering students with essential digital skills, it fosters innovation, enhances employability, and enables young people to participate actively in the global digital economy.

The road ahead

As technology continues to evolve, so does the need for adaptive and inclusive computing education. We remain committed to supporting governments, educators, and students in this journey. By fostering a generation of digitally literate and empowered individuals, we can create a future where technology serves as a force for good in society.

Through collaborations and localised efforts, the dream of making computing education accessible to every corner of India is steadily becoming a reality. Together, we can equip students with the skills and mindset needed to navigate the complexities of the digital age and shape a brighter, more inclusive future.

The post Computing Curriculum Framework: Adapting to India’s diverse landscapes appeared first on Raspberry Pi Foundation.

Aim of the partnership 

The aim of our partnership is to enable students in the school and undergraduate college to learn about coding and computing by providing the best possible curriculum, resources, and training for teachers. 

As both institutions are government institutions, education is provided for free, with approximately 800 high-performing students from disadvantaged backgrounds currently benefiting. The school is co-educational up to grade 10 and the college is for female undergraduate students only. 

The partnership is strategically important for us at the Raspberry Pi Foundation because it helps us to test curriculum content in an Indian context, and specifically with learners from historically marginalised communities with limited resources.

Adapting our curriculum content for use in Telangana

Since our partnership began, we’ve developed curriculum content for students in grades 6–12 in the school, which is in line with India’s national education policy requiring coding to be introduced from grade 6. We’ve also developed curriculum content for the undergraduate students at the college. 

In both cases, the content was developed based on an initial needs assessment — we used the assessment to adapt content from our previous work on The Computing Curriculum. Local examples were integrated to make the content relatable and culturally relevant for students in Telangana. Additionally, we tailored the content for different lesson durations and to allow a higher frequency of lessons. We captured impact and learning data through assessments, lesson observations, educator interviews, student surveys, and student focus groups.

Curriculum well received by educators and students

We have found that the partnership is succeeding in meeting many of its objectives. The curriculum resources have received lots of positive feedback from students, educators, and observers.

In our recent survey, 96% of school students and 85% of college students reported that they’ve learned new things in their computing classes. This was backed up by assessment marks, with students scoring an average of 70% in the school and 69% in the college for each assessment, compared to a pass mark of 40%. Students were also positive about their experiences of the computing and coding classes, and particularly enjoyed the practical components.

“My favourite thing in this computing classes [sic] is doing practical projects. By doing [things] practically we learnt a lot.” – Third year undergraduate student, Coding Academy College

“Since their last SA [summative assessment] exam, students have learnt spreadsheet [concepts] and have enjoyed applying them in activities. Their favourite part has been example codes, programming, and web-designing activities.” – Student focus group facilitator, grade 9 students, Coding Academy School

However, we also found some variation in outcomes for different groups of students and identified some improvements that are needed to ensure the content is appropriate for all. For example, educators and students felt improvements were needed to the content for undergraduates specialising in data science — there was a wish for the content to be more challenging and to more effectively prepare students for the workplace. Some amendments have been made to this content and we will continue to keep this under review. 

In addition, we faced some challenges with the equipment and infrastructure available. For example, there were instances of power cuts and unstable internet connections. These issues have been addressed as far as possible with Wi-Fi dongles and educators adapting their delivery to work with the equipment available.

Our ambition for India

Our team has already made some improvements to our curriculum content in preparation for the new academic year. We will also make further improvements based on the feedback received. 

The long-term vision for our work in India is to enable any school in India to teach students about computing and creating with digital technologies. Over our five-year partnership, we plan to work with TGSWREIS to roll out a computing curriculum to other government schools within the state. 

Through our work in Telangana and Odisha, we are learning about the unique challenges faced by government schools. We’re designing our curriculum to address these challenges and ensure that every student in India has the opportunity to thrive in the 21st century. If you would like to know more about our work and impact in India, please reach out to us at india@raspberrypi.org.

We take the evaluation of our work seriously and are always looking to understand how we can improve and increase the impact we have on the lives of young people. To find out more about our approach to impact, you can read about our recently updated theory of change, which supports how we evaluate what we do.

The post Implementing a computing curriculum in Telangana appeared first on Raspberry Pi Foundation.

Supporting students through personalised learning, new resources, and new questions

We made significant improvements throughout the year to support students with exam preparation and personalised learning. We introduced over 145 new self-marking questions and updated 50 existing ones, bringing the total to more than 1000. A new type of question was also launched to help students practise writing longer responses: they label parts of a sample answer and apply a mark scheme, simulating a peer review process. You can read more about this work in the AI section below.

We updated the question finder tool with an intuitive new design. Instead of seeing ten questions at random, students can now see all the questions we have on any given topic, and can use the filters to refine their searches by qualification and difficulty level. This enables students to better personalise their revision and progress tracking

“Ada Computer Science has been very effective for my revision. I like how it provides hints and pointers if you answer a question incorrectly.” 

– Ada Computer Science student

The ‘Representation of sound’ topic received a major update, with clearer explanations, new diagrams, and improved feedback to support students as they tackle common misconceptions in sound physics. We also refreshed the ‘Representation of numbers’ topic, adding new content and interactive quizzes to support teachers in assessing students’ understanding more effectively. 

We introduced a new database scenario titled ‘Repair & Reform’, offering an entity relationship diagram, a data dictionary, and a new SQL editor and question set to help students prepare for project-based assessments. We’ve further expanded this scenario into a full project covering all stages of development, including requirements analysis and evaluation. 

April was dedicated to gearing up for the exam season, with the introduction of revision flashcards and ready-made quizzes on key topics like bitmapped graphics and sorting algorithms. We also launched a student revision challenge, which ran from April to June and attracted over 600 participants.

“Ada Computer Science is an excellent resource to help support teachers and students. The explanations are clear and relevant, and the questions help students test their knowledge and understanding in a structured way, providing links to help them reconcile any discrepancies or misunderstandings.” 

– Patrick Kennedy, Computer Science teacher

Supporting teachers  

We expanded our efforts to support new computer science teachers with the launch of a teacher mentoring programme that offers free online drop-in sessions. We also hosted a teacher training event at the Raspberry Pi Foundation office in Cambridge (as seen in the picture below), where educators saw previews of upcoming content on AI and machine learning and contributed their own questions to the platform.

AI content and AI features

We continued our focus on AI and machine learning, releasing new learning resources that explore the ethical and social implications of AI alongside the practical applications of AI and machine learning models. 

To expand the Ada platform’s features, we also made considerable progress in integrating a large language model (LLM) to mark free-text responses. Our research showed that, as of June, LLM marks matched real teachers’ marks 82% of the time. In July, we received ethics approval from the University of Cambridge to add LLM-marked questions to the Ada platform. 

Computer science education in Scotland

We made significant strides towards supporting Scottish teachers and students with resources tailored to the SQA Computing Science curriculum. From September to November last year, we piloted a new set of materials specifically designed for Scottish teachers, receiving valuable feedback that we’ve used in 2024 to develop new content. More than half of the theory content for the National 5 and Higher specifications is now available on the platform. 

Our ‘Reform & Repair’ database scenario and project align with both SQA Higher and A level standards, providing a comprehensive resource for students preparing for project-based assessments.

Looking ahead: New resources for September and beyond

We have big plans for Ada for the next 12 months. Our focus will remain on continuously improving our resources and supporting the needs of both educators and students. 

After the positive response to our ‘Repair & Reform’ database project, our content experts are planning additional practical projects to support students and teachers. The next one will be a web project that covers HTML, CSS, JavaScript, and PHP, supporting students taking SQA qualifications in Scotland or undertaking the non-examined assessment (NEA) at A level.

We’ll be working on a number of teacher-focused improvements to the platform, which you’ll also see on Ada’s sibling site, Isaac Physics. These will include an overhaul of the markbook to make it more user-friendly, and updates to the ‘Assignments’ tool so assignments better meet the needs of teachers in schools.

We’ll be welcoming the next cohort of computer science students to the STEM SMART programme in January 2025 where, in partnership with the University of Cambridge, we’ll offer free, complementary teaching and support to UK students at state schools. Applications are now open.

Thank you to every teacher and student who has given their time in the last year to share feedback about Ada Computer Science — your insights are invaluable as we work to make high-quality computer science materials easily accessible. Here’s to another fantastic year of learning and growth!

The post Ada Computer Science: A year in review appeared first on Raspberry Pi Foundation.

Supporting government schools in Odisha to teach computing

Previously we shared an insight into how we established Code Clubs in Odisha to bring computing education to young people. Now we are partnering with two Indian civil society organisations to develop high school curriculum resources for computing and support teachers to deliver this content.

With our two partners, we trained 311 master teachers during July and August 2023. The master teachers, most often mathematics or science teachers, were in turn tasked with training teachers from around 8000 government schools. The aim of the training was to enable the 8000 teachers to deliver the curriculum to grades 9 and 10 in the June 2023 – April 2024 academic year.

At the Foundation, we have been responsible for providing ongoing support to 1898 teachers from 10 districts throughout the academic year, including through webinars and other online and in-person support.

To evaluate the impact our work in Odisha is having, we gathered data using a mixed-methods approach that included gathering feedback from teachers via surveys and interviews, visiting schools, capturing reflections from our trainers, and reviewing a sample of students’ projects.

Positive impact on teachers and students

In our teacher survey, respondents were generally positive about the curriculum resources:

• 87% of the 385 respondents agreed that the curriculum resources were both high quality and useful for their teaching
• 91% agreed that they felt more confident to teach students IT & Coding as a result of the curriculum resources

Teachers also tended to agree that the initial training had helped improve their understanding and confidence, and they appreciated our ongoing support webinars.

“The curriculum resources are very useful for students.” – Teacher in Odisha

“The webinar is very useful to acquire practical knowledge regarding the specific topics.”  – Teacher in Odisha

Teachers who responded to our survey observed a positive impact on students:

• 93% agreed their students’ digital literacy skills had improved
• 90% agreed that their students’ coding knowledge had improved

Students’ skills were also demonstrated by the Scratch projects we reviewed. And students from Odisha shared 314 projects in Coolest Projects — our online technology showcase for young people — including the project ‘We’ll build a new Odisha’ and an apple catching game.

Feedback and observations about teacher training

On school visits, our team observed that the teachers adopted and implemented the practical elements of the initial training quite well. However, survey responses and interviews showed that often teachers were not yet using all the elements of the curriculum as intended.

In their feedback, many teachers expressed a need for further regular training and support, and some reported additional challenges, such as other demands on their time and access to equipment.

When we observed training sessions master teachers delivered to teachers, we saw that, in some cases, information was lost within the training cascade (from our trainers, to master teachers, to teachers), including details about the intended pedagogical approach. It can be difficult to introduce experienced teachers to new pedagogical methods within a short training session, and teachers’ lack of computing knowledge also presents a challenge.

We will use all this data to shape how we support teachers going forward. Some teachers didn’t share feedback, and so in our further evaluation work, we will focus on making sure we hear a broad and representative range of teachers’ views and experiences.

What’s new this year?

In the current academic year, we are rolling out more advanced curriculum content for grade 10 students, including AI literacy resources developed at the Foundation. We’re currently training master teachers on this content, and they will pass on their knowledge to other teachers in the coming months. Based on teachers’ feedback, the grade 10 curriculum and the training also include a recap of some key points from the grade 9 curriculum.

A State Resource Group (SRG) has also been set up, consisting of 30 teachers who will support us with planning and providing ongoing support to master teachers and other teachers in Odisha. We have already trained the SRG members on the new curriculum content to enable them to best support teachers across the state. In addition to this, our local team in Odisha plans to conduct more visits and reach out directly to teachers more often. 

Our plans for the future

The long-term vision for our work in India is to enable any school in India to teach students about computing and creating with digital technologies. A critical part of achieving this vision is the development of a comprehensive computing curriculum for grade 6 to 12, specifically tailored for government schools in India. Thanks to our work in Odisha, we are in a better position to understand the unique challenges and limitations of government schools. We’re designing our curriculum to address these challenges and ensure that every Indian student has the opportunity to thrive in the 21st century. If you would like to know more about our work and impact in India, please reach out to us via india@raspberrypi.org.

We take evaluation of our work seriously and are always looking to understand how we can improve and increase the impact we have on the lives of young people. To find out more about our approach to impact, you can read about our recently updated theory of change, which supports how we evaluate what we do.

The post Introducing a computing curriculum in Odisha appeared first on Raspberry Pi Foundation.

I recently delivered Experience AI lessons to three Year 9 (ages 13–14) classes of about 20 students each with a ratio of approximately 2:3 girls to boys. They are groups of keen pupils who have elected to study computing as an option. The Experience AI lessons are an excellent set of resources.

Everything you need

Part of the Experience AI resources is a series of six lessons that introduce the concepts behind machine learning and artificial intelligence (AI). There are full lesson plans with timings, clear PowerPoint presentations, and activity sheets. There is also an end-of-topic multiple choice assessment provided.

Accompanying these are interesting, well-produced videos that underpin the concepts, all explained by real people who work in the AI industry. Plus, there are helpful videos for the educators, which explain certain parts of the scheme of work — particularly useful for parts that might have been seen as difficult for non-specialist teachers, for example, setting up a project using the Machine Learning for Kids website.

Confidence delivering lessons

The clear and detailed resources meant I felt mostly confident in delivering lessons. The suggested timings were a good guideline, although in some lessons, this did not always go to plan. For example, when the pupils were enjoying investigating websites that produce images generated by a text prompt, they were keen to spend more time on this than was allocated in the lesson plan. In this case, I modified the timings on the fly and set the final task of this lesson as a homework task.

Learning about AI sparked the students’ curiosity, and it triggered a few questions that I could not answer immediately. However, I admitted this was a new area for me, and with some investigation, found answers to many of their extra questions. This shows that the topic of AI is such an inspiring and important one for the next generation, and how important it is to add this to the curriculum now before students make their own, potentially biased, opinions about it.

“I’ve enjoyed actually learning about what AI is and how it works because before I thought it was just a scary computer that thinks like a human.” – Student, King Edward’s School, UK 

Impact on learners

The pupils’ feedback from the series of lessons was unerringly positive. I felt the lessons on bias in data were particularly important. The lesson where they trained their own algorithm recognising tomatoes and apples was a key one as it gave students an immediate sense of how a flawed training data set created bias and can impact the answers from a supposedly intelligent AI tool. I hope this has changed their outlook on AI-generated results and reinforced their critical thinking skills.

Many students are now seeing the influence of AI appearing in more and more tools around them and have mentioned that a career in AI is now something they are interested in.

“I have enjoyed learning about how AI is actually programmed rather than just hearing about how impactful and great it could be.” – Student, King Edward’s School, UK 

Tips for other teachers

Clearly this topic is incredibly important, and the Experience AI series of lessons is an excellent introduction to this for key stage 3 students (ages 11–14). My tips for other educators would be:

• I delivered these to bright Year 9s and added a few more coding activities from the Machine Learning for Kids website. As these lessons stand, they could be delivered to Year 8s (ages 12–13), but perhaps Year 7s (ages 11–12) might struggle with some of the more esoteric concepts.

• Before each lesson, ensure you read the content and familiarise yourself with the lesson resources and tools used. The Machine Learning for Kids website can take a little getting used to, but it is a powerful tool that brings to life how machine learning works, and many pupils said this was their favourite part of the lessons.

• Before the lesson, ensure that the websites that you need to access are unblocked by your school’s firewall!

• I tried to add a hands-on activity each lesson, e.g. for Lesson 1, I showed the students Google’s Quick, Draw! game, which they enjoyed and has a good section on the training data used to train the AI tool to recognise the drawings.

• We also spent an extra lesson using the brilliant Machine Learning for Kids website and followed the ‘Shoot the bug’ worksheet, which allowed pupils to train an algorithm to learn how to play a simple video game.

• I also needed to have a weekly homework task, so I would either use part of the activity from the lesson or quickly devise something (e.g. research another use for AI we haven’t discussed/what ethical issues might occur with a certain use of AI). Next year, our department will formalise these to help other teachers who might deliver these lessons to set these tasks more easily.

• Equally, I needed to have a summative assessment at the end of the topic. I used some of the multiple choice questions that were provided but added some longer-answer questions and made an online assessment to allow me to mark students’ answers more efficiently.

“I have always been fascinated by AI applications and finally finding out how they work and make the decisions they do has been a really cool experience.” – Student, King Edward’s School, UK 

From comments I have had from the students, they really engaged with the lessons and appreciated the opportunity to discuss and explore the topic, which is often associated with ‘deception’ within school. It allowed them to understand the benefits and the risks of AI and, most importantly, to begin to understand how it works ‘under the hood’, rather than see AI as a magical, anthropomorphised entity that is guessing their next move.

“The best part about learning about AI was knowing the dangers and benefits associated and how we can safely use it in our day-to-day life.” – Student, King Edward’s School, UK 

As for my perspective, I really enjoyed teaching this topic, and it has earned its place in the Year 9 scheme of work for next year. 

If you’re interested in teaching the Experience AI Lessons to your students, download the resources for free today at experience-ai.org.

The post A teacher’s guide to teaching Experience AI lessons appeared first on Raspberry Pi Foundation.

Artificial intelligence (AI) is transforming the world at an incredible pace, and at Penang Science Cluster, we are determined to be at the forefront of this fast-changing landscape.

The Malaysian government is actively promoting AI literacy among citizens, demonstrating a commitment to the nation’s technological advancement. This dedication is further demonstrated by the Ministry of Education’s recent announcement to introduce AI basics into the primary school curriculum, starting in 2027. 

Why we chose Experience AI

At Penang Science Cluster, we firmly believe that AI is already an essential part of everybody’s future, especially for young people, for whom technologies such as search engines, AI chatbots, image generation, and facial recognition are already deeply ingrained in their daily experiences. It is vital that we equip young people with the knowledge to understand, harness, and even create AI solutions, rather than view AI with trepidation.

With this in mind, we’re excited to be one of the first of many organisations to join the Experience AI global partner network. Experience AI is a free educational programme  offering cutting-edge resources on artificial intelligence and machine learning for teachers and students. Developed in collaboration between the Raspberry Pi Foundation and Google DeepMind, as a global partner we hope the programme will bring AI literacy to thousands of students across Malaysia.

Our goal is to demystify AI and highlight its potential for positive change. The Experience AI programme resonated with our mission to provide accessible and engaging resources tailored for our beneficiaries, making it a natural fit for our efforts.

Experience AI pilot: Results and student voices

At the start of this year, we ran an Experience AI pilot with 56 students to discover how the programme resonated with young people. The positive feedback we received was incredibly encouraging! Students expressed excitement and a genuine shift in their understanding of AI. 

Their comments, such as discovering the fun of learning about AI and seeing how AI can lead to diverse career paths, validated the effectiveness of the programme’s approach.  

One student’s changed perspective — from fearing AI to recognising its potential — underscores the importance of addressing misconceptions. Providing accessible AI education empowers students to develop a balanced and informed outlook.

“I learnt new things and it changed my mindset that AI is not going to take over the world.” – Student who took part in the Experience AI pilot

Launching Experience AI in Malaysia

The successful pilot paved the way for our official Experience AI launch in early April. Students who participated in the pilot were proud to be a part of the launch event, sharing their AI knowledge and experience with esteemed guests, including the Chief Minister of Penang, the Deputy Finance Minister of Malaysia, and the Director of the Penang State Education Department. The presence of these leaders highlights the growing recognition of the significance of AI education.

Building a vibrant AI education community

Following the launch, our immediate focus has shifted to empowering teachers. With the help of the Raspberry Pi Foundation, we’ll conduct teacher workshops to equip them with the knowledge and tools to bring Experience AI into their classrooms. Collaborating with education departments in Penang, Kedah, Perlis, Perak, and Selangor will be vital in teacher recruitment and building a vibrant AI education community.

Inspiring the next generation of AI creators

Experience AI marks an exciting start to integrating AI education within Malaysia, for both students and teachers. Our hope is to inspire a generation of young people empowered to shape the future of AI — not merely as consumers of the technology, but as active creators and innovators.

We envision a future where AI education is as fundamental as mathematics education, providing students with the tools they need to thrive in an AI-driven world. The journey of AI exploration in Malaysia has only just begun, and we’re thrilled to play a part in shaping its trajectory.

If you’re interested in partnering with us to bring Experience AI to students and teachers in your country, you can register your interest here.

The post Teaching a generation of AI innovators in Malaysia with Experience AI appeared first on Raspberry Pi Foundation.

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

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

Why is culturally relevant pedagogy necessary?

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

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

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

Applying the areas of opportunity in your classroom

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

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

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

How we’re using the AOs

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

Case study 1: Teachers in UK primary school adapt resources

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

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

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

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

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

Applying research to practice with the AOs

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

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

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

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

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

The post New resource to help teachers make Computing culturally relevant appeared first on Raspberry Pi Foundation.

What’s new on Ada?

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

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

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

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

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

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

Who is using Ada?

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

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

How are people using Ada?

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

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

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

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

What feedback are people giving about Ada?

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

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

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

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

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

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

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

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

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

We’d love to hear from you

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

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

The post How we’re creating more impact with Ada Computer Science appeared first on Raspberry Pi Foundation.

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

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

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

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

Supporting students with varying self-efficacy using PPs

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

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

Generating personalised PPs using AI tools

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

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

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

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

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

Join our next seminar

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

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

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

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

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

How do children learn?

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

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

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

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

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

A new framework for teaching computing

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

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

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

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

You can watch Anaclara’s seminar here: 

You can also access the presentation slides here.

Try grounded activities in your classroom

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

• Try out one of our hands-on lessons and learning activities for young learners from The Computing Curriculum. For example, in this Programming unit for Year 1 learners (aged 5–6), students learn how to program with the help of reenactments and classroom robots.
• Explore the ‘Teach Data Literacy’ guide, developed by the Data Education in Schools team, which offers some practical activities to support young learners to develop their data literacy skills. You can find out more about the Data Education in Schools initiative in Kate Farrell and Judy Robertson’s seminar on teaching primary learners how to be data citizens from May 2023.
• Check out Barefoot Computing, which offers a range of resources for early years education that involve physical manipulation and simulation.

Join us at our next seminar

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

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