As artificial intelligence continues to shape our world, understanding how to teach about AI has never been more important. Our new research seminar series brings together educators and researchers to explore approaches to AI and data science education. In the first seminar, we welcomed Shuchi Grover, Director of AI and Education Research at Looking Glass Ventures. Shuchi began by exploring the theme of teaching using AI, then moved on to discussing teaching about AI in K–12 (primary and secondary) education. She emphasised that it is crucial to teach about AI before using it in the classroom, and this blog post will focus on her insights in this area.

An AI literacy framework

From her research, Shuchi has developed a framework for teaching about AI that is structured as four interlocking components, each representing a key area of understanding:

• Basic understanding of AI, which refers to foundational knowledge such as what AI is, types of AI systems, and the capabilities of AI technologies
• Ethics and human–AI relationship, which includes the role of humans in regard to AI, ethical considerations, and public perceptions of AI
• Computational thinking/literacy, which relates to how AI works, including building AI applications and training machine learning models
• Data literacy, which addresses the importance of data, including examining data features, data visualisation, and biases

This framework shows the multifaceted nature of AI literacy, which involves an understanding of both technical aspects and ethical and societal considerations. 

Shuchi emphasised the importance of learning about AI ethics, highlighting the topic of bias. There are many ways that bias can be embedded in applications of AI and machine learning, including through the data sets that are used and the design of machine learning models. Shuchi discussed supporting learners to engage with the topic through exploring bias in facial recognition software, sharing activities and resources to use in the classroom that can prompt meaningful discussion, such as this talk by Joy Buolamwini. She also highlighted the Kapor Foundation’s Responsible AI and Tech Justice: A Guide for K–12 Education, which contains questions that educators can use with learners to help them to carefully consider the ethical implications of AI for themselves and for society. 

Computational thinking and AI

In computer science education, computational thinking is generally associated with traditional rule-based programming — it has often been used to describe the problem-solving approaches and processes associated with writing computer programs following rule-based principles in a structured and logical way. However, with the emergence of machine learning, Shuchi described a need for computational thinking frameworks to be expanded to also encompass data-driven, probabilistic approaches, which are foundational for machine learning. This would support learners’ understanding and ability to work with the models that increasingly influence modern technology.

Example activities from research studies

Shuchi shared that a variety of pedagogies have been used in recent research projects on AI education, ranging from hands-on experiences, such as using APIs for classification, to discussions focusing on ethical aspects. You can find out more about these pedagogies in her award-winning paper Teaching AI to K-12 Learners: Lessons, Issues and Guidance. This plurality of approaches ensures that learners can engage with AI and machine learning in ways that are both accessible and meaningful to them.

Shuchi shared examples of activities from two research projects that she has led:

• CS Frontiers engaged high school students in a number of activities involving using NetsBlox and accessing real-world data sets. For example, in one activity, students participated in data science activities such as creating data visualisations to answer questions about climate change. 
• AI & Cybersecurity for Teens explored approaches to teaching AI and machine learning to 13- to 15-year-olds through the use of cybersecurity scenarios. The project aimed to provide learners with insights into how machine learning models are designed, how they work, and how human decisions influence their development. An example activity guided students through building a classification model to analyse social media accounts to determine whether they may be bot accounts or accounts run by a human.

Closing thoughts

At the end of her talk, Shuchi shared some final thoughts addressing teaching about AI to K–12 learners: 

• AI learning requires contextualisation: Think about the data sets, ethical issues, and examples of AI tools and systems you use to ensure that they are relatable to learners in your context.
• AI should not be a solution in search of a problem: Both teachers and learners need to be educated about AI before they start to use it in the classroom, so that they are informed consumers.

Join our next seminar

In our current seminar series, we are exploring teaching about AI and data science. Join us at our next seminar on Tuesday 11 March at 17:00–18:30 GMT to hear Lukas Höper and Carsten Schulte from Paderborn University discuss supporting middle school students to develop their data awareness. 

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

I want to join the next seminarThe schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars and recordings page.

The post Teaching about AI in K–12 education: Thoughts from the USA appeared first on Raspberry Pi Foundation.

This blog post has been written by our Experience AI partners in Romania, Asociatia Techsoup, who piloted our new AI safety resources with Romanian teachers at the end of 2024.

Last year, we had the opportunity to pedagogically test the new three resources on AI safety and see first-hand the transformative effect they have on teachers and students. Here’s what we found.

Romania struggles with the digital skills gap

To say the internet is ubiquitous in Romania is an understatement: Romania has one of the fastest internets in the world (11th place), an impressive mobile internet penetration (86% of the population), and Romania is leading Central and Eastern Europe in terms of percentage of population that is online (89% of the entire population). Unsurprisingly, most of Romania’s internet users are also social media users. 

When you combine that with recent national initiatives, such as

• The introduction of Information Technology and Informatics in the middle-school curriculum in 2017 as a compulsory subject
• A Digital Agenda as a national strategy since 2015 
• Allocation of over 20% of its most recent National Recovery and Resilience Fund for digital transition

one might expect a similar lead in digital skills, both basic and advanced.

But only 28% of the population, well below the 56% EU average, and just 47% of young people between 16 and 24 have basic digital skills — the lowest percentage in the European Union. 

Findings from the latest International Computer and Information Literacy Study (ICILS, 2023)  underscore the urgent need to improve young people’s digital skills. Just 4% of students in Romania were scored at level 3 of 4, meaning they can demonstrate the capacity to work independently when using computers as information gathering and management tools, and are able, for example, to recognise that the credibility of web‐based information can be influenced by the identity, expertise, and motives of the people who create, publish, and share it.

Furthermore, 33% of students were assessed as level 1, while a further 40% of students did not even reach the minimum level set out in the ICILS, which means that they are unable to demonstrate even basic operational skills with computers or an understanding of computers as tools for completing simple tasks. For example, they can’t use computers to perform routine research and communication tasks under explicit instruction, and can’t manage simple content creation, such as entering text or images into pre‐existing templates.

Why we wanted to pilot the Experience AI safety resources

Add AI — and particularly generative AI — to this mix, and it spells huge trouble for educational systems unprepared for the fast rate of AI adoption by their students. Teachers need to be given the right pedagogical tools and support to address these new disruptions and the AI-related challenges that are adding to the existing post-pandemic ones.

This is why we at Asociația Techsoup have been enthusiastically supporting Romanian teachers to deliver the Experience AI curriculum created by the Raspberry Pi Foundation and Google DeepMind. We have found it to be the best pedagogical support that prepares students to fully understand AI and to learn how to use machine learning to solve real-world problems.

Testing the resources

Last year, we had the opportunity to pedagogically test the new three resources on AI Safety and see first-hand the transformative effect they have on teachers and students.

We worked closely with 8 computer science teachers in 8 Romanian schools from rural and small urban areas, reaching approximately 340 students between the ages of 13 and 18.

Before the teachers used the resources in the classroom, we worked with them in online community meetings and one-to-one phone conversations to help them review the available lesson plans, videos, and activity guides, to familiarise themselves with the structure, and to plan how to adapt the sessions to their classroom context. 

In December 2024, the teachers delivered the resources to their students. They guided students through key topics in AI safety, including understanding how to protect their data, critically evaluating data to spot fake news, and how to use AI tools responsibly. Each session incorporated a dynamic mix of teaching methods, including short videos and presentations delivering core messages, unplugged activities to reinforce understanding, and structured discussions to encourage critical thinking and reflection. 

Gathering feedback from users

We then interviewed all the teachers to understand their challenges in delivering such a new curriculum and we also observed two of the lessons. We took time to discuss with students and gather in-depth feedback on their learning experiences, perspectives on AI safety, and their overall engagement with the activities, in focus groups and surveys.

Feedback gathered in this pilot was then incorporated into the resources and recommendations given to teachers as part of the AI safety materials.

Teachers’ perspectives on the resources

It became obvious quite fast for both us and our teachers that the AI safety resources cover a growing and unaddressed need: to prepare our students for the ubiquitous presence of AI tools, which are on the road to becoming as ubiquitous as the internet itself.

Teachers evaluated the resources as very effective, giving them the opportunity to have authentic and meaningful conversations with their students about the world we live in. The format of the lessons was engaging — one of the teachers was so enthusiastic that she actually managed to keep students away from their phones for the whole lesson. 

They also appreciated the pedagogical quality of the resources, especially the fact that everything is ready to use in class and that they could access them for free. In interviews, they also appreciated that they themselves also learnt a lot from the lessons:

“For me it was a wake-up call. I was living in my bubble, in which I don’t really use these tools that much. But the world we live in is no longer the world I knew. … So such a lesson also helps us to learn and to discover the children in another context, – Carmen Melinte, a computer science teacher at the Colegiul Național Grigore Moisil in the small city of Onești, in north-east Romania, one of the EU regions with the greatest poverty risk.

What our students think about the resources

Students enjoyed discussing real-world scenarios and admitted that they don’t really have adults around whom they can talk to about the AI tools they use. They appreciated the interactive activities where they worked in pairs or groups and the games where they pretended to be creators of AI apps, thinking about safety features they could implement:

“I had never questioned AI, as long as it did my homework,” said one student in our focus groups, where the majority of students admitted that they are already using large language models (LLMs) for most of their homework.

“I really liked that I found out what is behind that ‘Accept all’ and now I think twice before giving my data,” – Student at the end of the ‘Your data and AI’ activities.

“Activities put me in a situation where I had to think from the other person’s shoes and think twice before sharing my personal data,” commented another student.

Good starting point

This is a good first step: there is an acute need for conversations between young people and adults around AI tools, how to think about them critically, and how to use them safely. School is the right place to start these conversations and activities, as teachers are still trusted by most Romanian students to help them understand the world.

But to be able to do that, we need to be serious about equipping teachers with pedagogically sound resources that they can use in class, as well as training them, supporting them, and making sure that most of their time is dedicated to teaching, and not administration. It might seem a slow process, but it is the best way to help our students become responsible, ethical and accountable digital citizens.

We are deeply grateful to the brave, passionate teachers in our community who gave the AI safety resources a try and of course to our partners at the Raspberry Pi Foundation for giving us the opportunity to lead this pilot.

If you are a teacher anywhere in the world, give them a try today to celebrate Safer Internet Day: rpf.io/aisafetyromania

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