Tag Archives: education

How can AI-based analysis help educators support students?

Post Syndicated from Henna Gorsia original https://www.raspberrypi.org/blog/ai-sytems-in-education-learner-support-research-seminar/

We are hosting a series of free research seminars about how to teach artificial intelligence (AI) and data science to young people, in partnership with The Alan Turing Institute.

In the fifth seminar of this series, we heard from Rose Luckin, Professor of Learner Centred Design at the University College London (UCL) Knowledge Lab. Rose is Founder of EDUCATE Ventures Research Ltd., a London consultancy service working with start-ups, researchers, and educators to develop evidence-based educational technology.

Rose Luckin.
Rose Luckin, UCL

Based on her experience at EDUCATE, Rose spoke about how AI-based analysis could help educators gain a deeper understanding of their students, and how educators could work with AI systems to provide better learning resources to their students. This provided us with a different angle to the first four seminars in our current series, where we’ve been thinking about how young people learn to understand AI systems.

Rose Luckin's definition of AI: technology capable of actions and behaviours "requiring intelligence when done by humans".
Rose’s definition of artificial intelligence for this presentation.

Education and AI systems

AI systems have the potential to impact education in a number of different ways, which Rose distilled into three areas: 

  1. Using AI in education to tackle some of the big educational challenges
  2. Educating teachers about AI so that they can use it safely and effectively 
  3. Changing education so that we focus on human intelligence and prepare people for an AI world

It is clear that the three areas are interconnected, meaning developments in one area will affect the others. Rose’s focus during the seminar was the second area: educating people about AI.

Rose Luckin's definition of the three intersections of education and artificial intelligence, see text in list above.

What can AI systems do in education? 

Through giving examples of existing AI-based systems used for education, Rose described what in particular it is about AI systems that can be useful in an education setting. The first point she raised was that AI systems can adapt based on learning from data. Her main example was the AI-based platform ENSKILLS, which detects the user’s level of competency with spoken English through the user’s interactions with a virtual character, and gradually adapts the character to the user’s level. Other examples of adaptive AI systems for education include Carnegie Learning and Century Intelligent Learning.

We know that AI systems can respond to different forms of data. Rose introduced the example of OyaLabs to demonstrate how AI systems can gather and process real-time sensory data. This is an app that parents can use in a young child’s room to monitor the child’s interactions with others. The app analyses the data it gathers and produces advice for parents on how they can support their child’s language development.

AI system creators can also combine adaptivity and real-time sensory data processing  in their systems. One example Rosa gave of this was SimSensei from the University of Southern California. This is a simulated coach, which a student can interact with and which gathers real-time data about how the student is speaking, including their tone, speed of speech, and facial expressions. The system adapts its coaching advice based on these interactions and on what it learns from interactions with other students.

Getting ready for AI systems in education

For the remainder of her presentation, Rose focused on the framework she is involved in developing, as part of the EDUCATE service, to support organisations to prepare for implementing AI systems, including educators within these organisations. The aim of this ETHICAI framework is to enable organisations and educators to understand:

  • What AI systems are capable of doing
  • The strengths and weaknesses of AI systems
  • How data is used by AI systems to learn
The EDUCATE consultancy service's seven-part AI readiness framework, see test below for list.

Rose described the seven steps of the framework as:

  1. Educate, enthuse, excite – about building an AI mindset within your community 
  2. Tailor and Hone – the particular challenges you want to focus on
  3. Identify – identify (wisely), collate and …
  4. Collect – new data relevant to your focus
  5. Apply – AI techniques to the relevant data you have brought together
  6. Learn – understand what the data is telling you about your focus and return to step 5 until you are AI ready
  7. Iterate

She then went on to demonstrate how the framework is applied using the example of online teaching. Online teaching has been a key part of education throughout the coronavirus pandemic; AI systems could be used to analyse datasets generated during online teaching sessions, in order to make decisions for and recommendations to educators.

The first step of the ETHICAI framework is educate, enthuse, excite. In Rose’s example, this step consisted of choosing online teaching as a scenario, because it is very pertinent to a teacher’s practice. The second step is to tailor and hone in on particular challenges that are to be the focus, capitalising on what AI systems can do. In Rose’s example, the challenge is assessing the quality of online lessons in a way that would be useful to educators. The third step of the framework is to identify what data is required to perform this quality assessment.

Examples of data to be fed into an AI system for education, see text.

The fourth step is the collection of new data relevant to the focus of the project. The aim is to gain an increased understanding of what happens in online learning across thousands of schools. Walking through the online learning example, Rose suggested we might be able to collect the following types of data:

  • Log data
  • Audio data
  • Performance data
  • Video data, which includes eye-movement data
  • Historical data from tests and interviews
  • Behavioural data from surveying teachers and parents about how they felt about online learning

It is important to consider the ethical implications of gathering all this data about students, something that was a recurrent theme in both Rose’s presentation and the Q&A at the end.

Step five of the ETHICAI framework focuses on applying AI techniques to the relevant data to combine and process it. The figure below shows that in preparation, the various data sets need to be collated, cleaned, organised, and transformed.

Presentation slide showing that data for an AI system needs to be collated, cleaned, organised, and transformed.

From the correctly prepared data, interaction profiles can be produced in order to put characteristics from different lessons into groups/profiles. Rose described how cluster analysis using a combination of both AI and human intelligence could be used to sort lessons into groups based on common features.

The sixth step in Rose’s example focused on what may be learned from analysing collected data linked to the particular challenge of online teaching and learning. Rose said that applying an AI system to students’ behavioural data could, for example, give indications about students’ focus and confidence, and make or recommend interventions to educators accordingly.

Presentation slide showing example graphs of results produced by an AI system in education.

Where might we take applications of AI systems in education in the future?

Rose described that AI systems can possess some types of intelligence humans have or can develop: interdisciplinary academic intelligence, meta-knowing intelligence, and potentially social intelligence. However, there are types such as meta-contextual intelligence and perceived self-efficacy that AI systems are not able to demonstrate in the way humans can.

The seven types of human intelligence as defined by Rose Luckin: interdisciplinary academic knowledge, meta-knowing intelligence, social intelligence, metacognitive intelligence, meta-subjective intelligence, meta-contextual knowledge, perceived self-efficacy.

The use of AI systems in education can cause ethical issues. As an example, Rose pointed out the use of virtual glasses to identify when students need help, even if they do not realise it themselves. A system like this could help educators with assessing who in their class needs more help, and could link this back to student performance. However, using such a system like this has obvious ethical implications, and some of these were the focus of the Q&A that followed Rose’s presentation.

It’s clear that, in the education domain as in all other domains, both positive and negative outcomes of integrating AI are possible. In a recent paper written by Wayne Holmes (also from the UCL Knowledge Lab) and co-authors, ‘Ethics of AI in Education: Towards a Community Wide Framework’ [1], the authors suggest that the interpretation of data, consent and privacy, data management, surveillance, and power relations are all ethical issues that should be taken into consideration. Finding consensus for a practical ethical framework or set of principles, with all stakeholders, at the very start of an AI-related project is the only way to ensure ethics are built into the project and the AI system itself from the ground up.

Two boys at laptops in a classroom.

Ethical issues of AI systems more broadly, and how to involve young people in discussions of AI ethics, were the focus of our seminar with Dr Mhairi Aitken back in September. You can revisit the seminar recording, presentation slides, and summary blog post.

I really enjoyed both the focus and content of Rose’s talk: educators understanding how AI systems may be applied to education in order to help them make more informed decisions about how to best support their students. This is an important factor to consider in the context of the bigger picture of what young people should be learning about AI. The work that Rose and her colleagues are doing also makes an important contribution to translating research into practical models that teachers can use.

Join our next free seminars

You may still have time to sign up for our Tuesday 11 January seminar, today at 17:00–18:30 GMT, where we will welcome Dave Touretzky and Fred Martin, founders of the influential AI4K12 framework, which identifies the five big ideas of AI and how they can be integrated into education.

Next month, on 1 February at 17:00–18:30 GMT, Tara Chklovski (CEO of Technovation) will give a presentation called Teaching youth to use AI to tackle the Sustainable Development Goals at our seminar series.

If you want to join any of our seminars, click the button below to sign up and we will send you information on how to join. We look forward to seeing you there!

You’ll always find our schedule of upcoming seminars on this page. For previous seminars, you can visit our past seminars and recordings page.

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How do we develop AI education in schools? A panel discussion

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/ai-education-schools-panel-uk-policy/

AI is a broad and rapidly developing field of technology. Our goal is to make sure all young people have the skills, knowledge, and confidence to use and create AI systems. So what should AI education in schools look like?

To hear a range of insights into this, we organised a panel discussion as part of our seminar series on AI and data science education, which we co-host with The Alan Turing Institute. Here our panel chair Tabitha Goldstaub, Co-founder of CogX and Chair of the UK government’s AI Council, summarises the event. You can also watch the recording below.

As part of the Raspberry Pi Foundation’s monthly AI education seminar series, I was delighted to chair a special panel session to broaden the range of perspectives on the subject. The members of the panel were:

  • Chris Philp, UK Minister for Tech and the Digital Economy
  • Philip Colligan, CEO of the Raspberry Pi Foundation 
  • Danielle Belgrave, Research Scientist, DeepMind
  • Caitlin Glover, A level student, Sandon School, Chelmsford
  • Alice Ashby, student, University of Brighton

The session explored the UK government’s commitment in the recently published UK National AI Strategy stating that “the [UK] government will continue to ensure programmes that engage children with AI concepts are accessible and reach the widest demographic.” We discussed what it will take to make this a reality, and how we will ensure young people have a seat at the table.

Two teenage girls do coding during a computer science lesson.

Why AI education for young people?

It was clear that the Minister felt it is very important for young people to understand AI. He said, “The government takes the view that AI is going to be one of the foundation stones of our future prosperity and our future growth. It’s an enabling technology that’s going to have almost universal applicability across our entire economy, and that is why it’s so important that the United Kingdom leads the world in this area. Young people are the country’s future, so nothing is complete without them being at the heart of it.”

A teacher watches two female learners code in Code Club session in the classroom.

Our panelist Caitlin Glover, an A level student at Sandon School, reiterated this from her perspective as a young person. She told us that her passion for AI started initially because she wanted to help neurodiverse young people like herself. Her idea was to start a company that would build AI-powered products to help neurodiverse students.

What careers will AI education lead to?

A theme of the Foundation’s seminar series so far has been how learning about AI early may impact young people’s career choices. Our panelist Alice Ashby, who studies Computer Science and AI at Brighton University, told us about her own process of deciding on her course of study. She pointed to the fact that terms such as machine learning, natural language processing, self-driving cars, chatbots, and many others are currently all under the umbrella of artificial intelligence, but they’re all very different. Alice thinks it’s hard for young people to know whether it’s the right decision to study something that’s still so ambiguous.

A young person codes at a Raspberry Pi computer.

When I asked Alice what gave her the courage to take a leap of faith with her university course, she said, “I didn’t know it was the right move for me, honestly. I took a gamble, I knew I wanted to be in computer science, but I wanted to spice it up.” The AI ecosystem is very lucky that people like Alice choose to enter the field even without being taught what precisely it comprises.

We also heard from Danielle Belgrave, a Research Scientist at DeepMind with a remarkable career in AI for healthcare. Danielle explained that she was lucky to have had a Mathematics teacher who encouraged her to work in statistics for healthcare. She said she wanted to ensure she could use her technical skills and her love for math to make an impact on society, and to really help make the world a better place. Danielle works with biologists, mathematicians, philosophers, and ethicists as well as with data scientists and AI researchers at DeepMind. One possibility she suggested for improving young people’s understanding of what roles are available was industry mentorship. Linking people who work in the field of AI with school students was an idea that Caitlin was eager to confirm as very useful for young people her age.

We need investment in AI education in school

The AI Council’s Roadmap stresses how important it is to not only teach the skills needed to foster a pool of people who are able to research and build AI, but also to ensure that every child leaves school with the necessary AI and data literacy to be able to become engaged, informed, and empowered users of the technology. During the panel, the Minister, Chris Philp, spoke about the fact that people don’t have to be technical experts to come up with brilliant ideas, and that we need more people to be able to think creatively and have the confidence to adopt AI, and that this starts in schools. 

A class of primary school students do coding at laptops.

Caitlin is a perfect example of a young person who has been inspired about AI while in school. But sadly, among young people and especially girls, she’s in the minority by choosing to take computer science, which meant she had the chance to hear about AI in the classroom. But even for young people who choose computer science in school, at the moment AI isn’t in the national Computing curriculum or part of GCSE computer science, so much of their learning currently takes place outside of the classroom. Caitlin added that she had had to go out of her way to find information about AI; the majority of her peers are not even aware of opportunities that may be out there. She suggested that we ensure AI is taught across all subjects, so that every learner sees how it can make their favourite subject even more magical and thinks “AI’s cool!”.

A primary school boy codes at a laptop with the help of an educator.

Philip Colligan, the CEO here at the Foundation, also described how AI could be integrated into existing subjects including maths, geography, biology, and citizenship classes. Danielle thoroughly agreed and made the very good point that teaching this way across the school would help prepare young people for the world of work in AI, where cross-disciplinary science is so important. She reminded us that AI is not one single discipline. Instead, many different skill sets are needed, including engineering new AI systems, integrating AI systems into products, researching problems to be addressed through AI, or investigating AI’s societal impacts and how humans interact with AI systems.

On hearing about this multitude of different skills, our discussion turned to the teachers who are responsible for imparting this knowledge, and to the challenges they face. 

The challenge of AI education for teachers

When we shifted the focus of the discussion to teachers, Philip said: “If we really want to equip every young person with the knowledge and skills to thrive in a world that shaped by these technologies, then we have to find ways to evolve the curriculum and support teachers to develop the skills and confidence to teach that curriculum.”

Teenage students and a teacher do coding during a computer science lesson.

I asked the Minister what he thought needed to happen to ensure we achieved data and AI literacy for all young people. He said, “We need to work across government, but also across business and society more widely as well.” He went on to explain how important it was that the Department for Education (DfE) gets the support to make the changes needed, and that he and the Office for AI were ready to help.

Philip explained that the Raspberry Pi Foundation is one of the organisations in the consortium running the National Centre for Computing Education (NCCE), which is funded by the DfE in England. Through the NCCE, the Foundation has already supported thousands of teachers to develop their subject knowledge and pedagogy around computer science.

A recent study recognises that the investment made by the DfE in England is the most comprehensive effort globally to implement the computing curriculum, so we are starting from a good base. But Philip made it clear that now we need to expand this investment to cover AI.

Young people engaging with AI out of school

Philip described how brilliant it is to witness young people who choose to get creative with new technologies. As an example, he shared that the Foundation is seeing more and more young people employ machine learning in the European Astro Pi Challenge, where participants run experiments using Raspberry Pi computers on board the International Space Station. 

Three teenage boys do coding at a shared computer during a computer science lesson.

Philip also explained that, in the Foundation’s non-formal CoderDojo club network and its Coolest Projects tech showcase events, young people build their dream AI products supported by volunteers and mentors. Among these have been autonomous recycling robots and AI anti-collision alarms for bicycles. Like Caitlin with her company idea, this shows that young people are ready and eager to engage and create with AI.

We closed out the panel by going back to a point raised by Mhairi Aitken, who presented at the Foundation’s research seminar in September. Mhairi, an Alan Turing Institute ethics fellow, argues that children don’t just need to learn about AI, but that they should actually shape the direction of AI. All our panelists agreed on this point, and we discussed what it would take for young people to have a seat at the table.

A Black boy uses a Raspberry Pi computer at school.

Alice advised that we start by looking at our existing systems for engaging young people, such as Youth Parliament, student unions, and school groups. She also suggested adding young people to the AI Council, which I’m going to look into right away! Caitlin agreed and added that it would be great to make these forums virtual, so that young people from all over the country could participate.

The panel session was full of insight and felt very positive. Although the challenge of ensuring we have a data- and AI-literate generation of young people is tough, it’s clear that if we include them in finding the solution, we are in for a bright future. 

What’s next for AI education at the Raspberry Pi Foundation?

In the coming months, our goal at the Foundation is to increase our understanding of the concepts underlying AI education and how to teach them in an age-appropriate way. To that end, we will start to conduct a series of small AI education research projects, which will involve gathering the perspectives of a variety of stakeholders, including young people. We’ll make more information available on our research pages soon.

In the meantime, you can sign up for our upcoming research seminars on AI and data science education, and peruse the collection of related resources we’ve put together.

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The machine learning effect: Magic boxes and computational thinking 2.0

Post Syndicated from Jane Waite original https://www.raspberrypi.org/blog/machine-learning-education-school-computational-thinking-2-0-research-seminar/

How does teaching children and young people about machine learning (ML) differ from teaching them about other aspects of computing? Professor Matti Tedre and Dr Henriikka Vartiainen from the University of Eastern Finland shared some answers at our latest research seminar.

Three smiling young learners in a computing classroom.
We need to determine how to teach young people about machine learning, and what teachers need to know to help their learners form correct mental models.

Their presentation, titled ‘ML education for K-12: emerging trajectories’, had a profound impact on my thinking about how we teach computational thinking and programming. For this blog post, I have simplified some of the complexity associated with machine learning for the benefit of readers who are new to the topic.

a 3D-rendered grey box.
Machine learning is not magic — what needs to change in computing education to make sure learners don’t see ML systems as magic boxes?

Our seminars on teaching AI, ML, and data science

We’re currently partnering with The Alan Turing Institute to host a series of free research seminars about how to teach artificial intelligence (AI) and data science to young people.

The seminar with Matti and Henriikka, the third one of the series, was very well attended. Over 100 participants from San Francisco to Rajasthan, including teachers, researchers, and industry professionals, contributed to a lively and thought-provoking discussion.

Representing a large interdisciplinary team of researchers, Matti and Henriikka have been working on how to teach AI and machine learning for more than three years, which in this new area of study is a long time. So far, the Finnish team has written over a dozen academic papers based on their pilot studies with kindergarten-, primary-, and secondary-aged learners.

Current teaching in schools: classical rule-driven programming

Matti and Henriikka started by giving an overview of classical programming and how it is currently taught in schools. Classical programming can be described as rule-driven. Example features of classical computer programs and programming languages are:

  • A classical language has a strict syntax, and a limited set of commands that can only be used in a predetermined way
  • A classical language is deterministic, meaning we can guarantee what will happen when each line of code is run
  • A classical program is executed in a strict, step-wise order following a known set of rules

When we teach this type of programming, we show learners how to use a deductive problem solving approach or workflow: defining the task, designing a possible solution, and implementing the solution by writing a stepwise program that is then run on a computer. We encourage learners to avoid using trial and error to write programs. Instead, as they develop and test a program, we ask them to trace it line by line in order to predict what will happen when each line is run (glass-box testing).

A list of features of rule-driven computer programming, also included in the text.
The features of classical (rule-driven) programming approaches as taught in computer science education (CSE) (Tedre & Vartiainen, 2021).

Classical programming underpins the current view of computational thinking (CT). Our speakers called this version of CT ‘CT 1.0’. So what’s the alternative Matti and Henriikka presented, and how does it affect what computational thinking is or may become?

Machine learning (data-driven) models and new computational thinking (CT 2.0) 

Rule-based programming languages are not being eradicated. Instead, software systems are being augmented through the addition of machine learning (data-driven) elements. Many of today’s successful software products, such as search engines, image classifiers, and speech recognition programs, combine rule-driven software and data-driven models. However, the workflows for these two approaches to solving problems through computing are very different.

A table comparing problem solving workflows using computational thinking 1.0 versus computational thinking 2.0, info also included in the text.
Problem solving is very different depending on whether a rule-driven computational thinking (CT 1.0) approach or a data-driven computational thinking (CT 2.0) approach is used (Tedre & Vartiainen,2021).

Significantly, while in rule-based programming (and CT 1.0), the focus is on solving problems by creating algorithms, in data-driven approaches, the problem solving workflow is all about the data. To highlight the profound impact this shift in focus has on teaching and learning computing, Matti introduced us to a new version of computational thinking for machine learning, CT 2.0, which is detailed in a forthcoming research paper.

Because of the focus on data rather than algorithms, developing a machine learning model is not at all like developing a classical rule-driven program. In classical programming, programs can be traced, and we can predict what will happen when they run. But in data-driven development, there is no flow of rules, and no absolutely right or wrong answer.

A table comparing conceptual differences between computational thinking 1.0 versus computational thinking 2.0, info also included in the text.
There are major differences between rule-driven computational thinking (CT 1.0) and data-driven computational thinking (CT 2.0), which impact what computing education needs to take into account (Tedre & Vartiainen,2021).

Machine learning models are created iteratively using training data and must be cross-validated with test data. A tiny change in the data provided can make a model useless. We rarely know exactly why the output of an ML model is as it is, and we cannot explain each individual decision that the model might have made. When evaluating a machine learning system, we can only say how well it works based on statistical confidence and efficiency. 

Machine learning education must cover ethical and societal implications 

The ethical and societal implications of computer science have always been important for students to understand. But machine learning models open up a whole new set of topics for teachers and students to consider, because of these models’ reliance on large datasets, the difficulty of explaining their decisions, and their usefulness for automating very complex processes. This includes privacy, surveillance, diversity, bias, job losses, misinformation, accountability, democracy, and veracity, to name but a few.

I see the shift in problem solving approach as a chance to strengthen the teaching of computing in general, because it opens up opportunities to teach about systems, uncertainty, data, and society.

Jane Waite

Teaching machine learning: the challenges of magic boxes and new mental models

For teaching classical rule-driven programming, much time and effort has been put into researching learners’ understanding of what a program will do when it is run. This kind of understanding is called a learner’s mental model or notional machine. An approach teachers often use to help students develop a useful mental model of a program is to hide the detail of how the program works and only gradually reveal its complexity. This approach is described with the metaphor of hiding the detail of elements of the program in a box. 

Data-driven models in machine learning systems are highly complex and make little sense to humans. Therefore, they may appear like magic boxes to students. This view needs to be banished. Machine learning is not magic. We have just not figured out yet how to explain the detail of data-driven models in a way that allows learners to form useful mental models.

An example of a representation of a machine learning model in TensorFlow, an online machine learning tool (Tedre & Vartiainen,2021).

Some existing ML tools aim to help learners form mental models of ML, for example through visual representations of how a neural network works (see Figure 2). But these explanations are still very complex. Clearly, we need to find new ways to help learners of all ages form useful mental models of machine learning, so that teachers can explain to them how machine learning systems work and banish the view that machine learning is magic.

Some tools and teaching approaches for ML education

Matti and Henriikka’s team piloted different tools and pedagogical approaches with different age groups of learners. In terms of tools, since large amounts of data are needed for machine learning projects, our presenters suggested that tools that enable lots of data to be easily collected are ideal for teaching activities. Media-rich education tools provide an opportunity to capture still images, movements, sounds, or sense other inputs and then use these as data in machine learning teaching activities. For example, to create a machine learning–based rock-paper-scissors game, students can take photographs of their hands to train a machine learning model using Google Teachable Machine.

Photos of hands are used to train a machine learning model as part of a project to create a rock-paper-scissors game.
Photos of hands are used to train a Teachable Machine machine learning model as part of a project to create a rock-paper-scissors game (Tedre & Vartiainen, 2021).

Similar to tools that teach classic programming to novice students (e.g. Scratch), some of the new classroom tools for teaching machine learning have a drag-and-drop interface (e.g. Cognimates). Using such tools means that in lessons, there can be less focus on one of the more complex aspects of learning to program, learning programming language syntax. However, not all machine learning education products include drag-and-drop interaction, some instead have their own complex languages (e.g. Wolfram Programming Lab), which are less attractive to teachers and learners. In their pilot studies, the Finnish team found that drag-and-drop machine learning tools appeared to work well with students of all ages.

The different pedagogical approaches the Finnish research team used in their pilot studies included an exploratory approach with preschool children, who investigated machine learning recognition of happy or sad faces; and a project-based approach with older students, who co-created machine learning apps with web-based tools such as Teachable Machine and Learn Machine Learning (built by the research team), supported by machine learning experts.

Example of a middle school (age 8 to 11) student’s pen and paper design for a machine learning app that recognises different instruments and chords.
Example of a middle school (age 8 to 11) student’s design for a machine learning app that recognises different instruments and chords (Tedre & Vartiainen, 2021).

What impact these pedagogies have on students’ long-term mental models about machine learning has yet to be researched. If you want to find out more about the classroom pilot studies, the academic paper is a very accessible read.

My take-aways: new opportunities, new research questions

We all learned a tremendous amount from Matti and Henriikka and their perspectives on this important topic. Our seminar participants asked them many questions about the pedagogies and practicalities of teaching machine learning in class, and raised concerns about squeezing more into an already packed computing curriculum.

For me, the most significant take-away from the seminar was the need to shift focus from algorithms to data and from CT 1.0 to CT 2.0. Learning how to best teach classical rule-driven programming has been a long journey that we have not yet completed. We are forming an understanding of what concepts learners need to be taught, the progression of learning, key mental models, pedagogical options, and assessment approaches. For teaching data-driven development, we need to do the same.  

The question of how we make sure teachers have the necessary understanding is key.

Jane Waite

I see the shift in problem solving approach as a chance to strengthen the teaching of computing in general, because it opens up opportunities to teach about systems, uncertainty, data, and society. I think it will help us raise awareness about design, context, creativity, and student agency. But I worry about how we will introduce this shift. In my view, there is a considerable risk that we will be sucked into open-ended, project-based learning, with busy and fun but shallow learning experiences that result in restricted conceptual development for students.

I also worry about how we can best help teachers build up the knowledge and experience to support their students. In the Q&A after the seminar, I asked Matti and Henriikka about the role of their team’s machine learning experts in their pilot studies. It seemed to me that without them, the pilot lessons would not have worked, as the participating teachers and students would not have had the vocabulary to talk about the process and would not have known what was doable given the available time, tools, and student knowledge.

The question of how we make sure teachers have the necessary understanding is key. Many existing professional development resources for teachers wanting to learn about ML seem to imply that teachers will all need a PhD in statistics and neural network optimisation to engage with machine learning education. This is misleading. But teachers do need to understand the machine learning concepts that their students need to learn about, and I think we don’t yet know exactly what these concepts are. 

In summary, clearly more research is needed. There are fundamental questions still to be answered about what, when, and how we teach data-driven approaches to software systems development and how this impacts what we teach about classical, rule-based programming. But to me, that is exciting, and I am very much looking forward to the journey ahead.

Join our next free seminar

To find out what others recommend about teaching AI and ML, catch up on last month’s seminar with Professor Carsten Schulte and colleagues on centring data instead of code in the teaching of AI.

We have another four seminars in our monthly series on AI, machine learning, and data science education. Find out more about them on this page, and catch up on past seminar blogs and recordings here.

At our next seminar on Tuesday 7 December at 17:00–18:30 GMT, we will welcome Professor Rose Luckin from University College London. She will be presenting on what it is about AI that makes it useful for teachers and learners.

We look forward to meeting you there!

PS You can build your understanding of machine learning by joining our latest free online course, where you’ll learn foundational concepts and train your own ML model!

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Introducing Code Club World: a new way for young people to learn to code at home

Post Syndicated from Laura Kirsop original https://www.raspberrypi.org/blog/code-club-world-free-online-platform-young-people-children-learn-to-code-at-home/

Today we are introducing you to Code Club World — a free online platform where young people aged 9 to 13 can learn to make stuff with code.

Images from Code Club World, a free online platform for children who want to learn to code

In Code Club World, young people can:

  • Start out by creating their personal robot avatar
  • Make music, design a t-shirt, and teach their robot avatar to dance!
  • Learn to code on islands with structured activities
  • Discover block-based and text-based coding in Scratch and Python
  • Earn badges for their progress 
  • Share their coding creations with family, friends, and the Code Club World community

Learning to code at home with Code Club World: meaningful, fun, flexible

When we spoke to parents and children about learning at home during the pandemic, it became clear to us that they were looking for educational tools that the children can enjoy and master independently, and that are as fun and social as the computer games and other apps the children love.

A girl has fun learning to code at home, sitting with a laptop on a sofa, with a dog sleeping next to her and her father writing code too.
Code Club World is educational, and as fun as the games and apps young people love.

What’s more, a free tool for learning to code at home is particularly important for young people who are unable to attend coding clubs in person. We believe every child should have access to a high-quality coding and digital making education. And with this in mind, we set out to create Code Club World, an online environment as rich and engaging as a face-to-face extracurricular learning experience, where all young people can learn to code.

The Code Club World activities are mapped to our research-informed Digital Making Framework — a coding and digital making curriculum for non-formal settings. That means when children are in the Code Club World environment, they are learning to code and use digital making to independently create their ideas and address challenges that matter to them.

Islands in the Code Club World online platform for children who want to learn to code for free.
Welcome to Code Club World — so many islands to explore!

By providing a structured pathway through the coding activities, a reward system of badges to engage and motivate learners, and a broad range of projects covering different topics, Code Club World supports learners at every stage, while making the activities meaningful, fun, and flexible.

A girl has fun learning to code at home on a tablet sitting on a sofa.
Code Club World’s home island works as well on mobile phones and tablets as on computers.

We’ve also designed Code Club World to be mobile-friendly, so if a young person uses a phone or tablet to visit the platform, they can still code cool things they will be proud of.

Created with the community

Since we started developing Code Club World, we have been working with a community of more than 1000 parents, educators, and children who are giving us valuable input to shape the direction of the platform. We’ve had some fantastic feedback from them:

“I’ve not coded before, but found this really fun! … I LOVED making the dance. It was so much fun and made me laugh!”

Learner, aged 11

“I love the concept of having islands to explore in making the journey through learning coding, it is fabulous and eye-catching.”

Parent

The platform is still in beta status — this means we’d love you to share it with young people in your family, school, or community so they can give their feedback and help make Code Club World even better.

Together, we will ensure every child has an equal opportunity to learn to code and make things that change their world.

The post Introducing Code Club World: a new way for young people to learn to code at home appeared first on Raspberry Pi.

Cat Lamin on building a global educator family | Hello World #17

Post Syndicated from Gemma Coleman original https://www.raspberrypi.org/blog/global-staffroom-mental-health-hello-world-17/

Cat Lamin.

In Hello World issue 17, Raspberry Pi Certified Educator Cat Lamin talks about how building connections and sharing the burden can help make us better educators, even in times of great stress:

“I felt like I needed to play my part”

In March 2020, the world suddenly changed. For educators, we jumped from face-to-face teaching to a stark new landscape, with no idea of how the future would look. As generous teachers pushed out free resources, I felt like I needed to play my part. Suddenly, an idea struck me. In September 2017, I had decided to be brave and submit a talk to PyConUK to discuss my mental health. Afterwards, several people in the audience shared their own stories with me or let me know that it helped them just to hear that someone else struggled too. I realised that in times of pressure, we need a chance to talk and we had lost these outlets. In school, we would pop to the staffroom or a friend’s classroom for a quick vent, but that wasn’t an option anymore. People were feeling isolated, scared, stressed and didn’t have anyone to turn to.

I realised that in times of pressure, we need a chance to talk, and we had lost these outlets.

Cat Lamin

Thus, the first Global Google Educator Group Staffroom: Mental Health Matters was launched on 14 March 2020, which coincided with the US government announcing school closures and UK teachers still waiting anxiously to hear when doors would close. The aim of Staffroom was to give teachers a safe space to talk about how they’re feeling under the overwhelming weight of school closures. To say it was a success would be an understatement, with teachers joining the calls from Australia, Malaysia, the USA, Colombia, Mexico, Brazil, Europe and more!

Pily Perfil.

Staffroom for me is a place and time to connect with other teachers from around the world. I remember seeing the calendar invites by mail and I kept thinking I should join but was afraid to do it. The first time I did it, I listened first and it made me realize that my struggles during pandemic online teaching were the same struggles as everywhere else.” – Pily Hernandez, Monterrey, Mexico

Which William are you today?

In those early days, we just gave teachers a chance to talk. The format of our meetings was simple: what’s your name, where are you from, and then an ice breaker question like ‘What colour do you feel like?’ or ‘What song represents your current mood?’ It wasn’t long before we hit upon a winning formula by making our own ‘Which image are you today?’ picture scale (see the ‘Which William’ image below!). Using the picture scales allowed people to really express how they felt. Often someone who had been happily chatting would explain that they were actually struggling to keep their head above water because a silly image allowed them to be honest.

A grid of photos of the same toddler expressing different emotions.
Which William are you today?

One of the most important messages from Staffroom was that many people involved with technology in schools were feeling alone. After years of suggesting teachers use technology, suddenly they were blamed for schools not being properly prepared. They were struggling with not necessarily knowing what to suggest to teachers with technology difficulties, as they were grappling with their own personal lockdown situations. Hearing that other people, all around the world, were experiencing something similar was hugely eye-opening and took a great amount of weight off their shoulders.

Abid Patel.

“As someone who thrived from having in person connections and networking opportunities, lockdown hit me hard. Staffroom really helped to keep those connections going and has developed into such a lovely safe space to talk and connect with others.” – Abid Patel, London, UK

We varied the tone of the sessions depending on the needs of the attendees. In the first few months, we shared our lockdown situations and our different experiences across the world. We could share advice and tips, as well as best practice for delivering content and things that had gone terribly wrong since switching to remote teaching. Or we’d discuss food in different countries around the world (did you know that in Australia, fish and chips is made from shark?) or joke about whether Vegemite was actually an edible product (it’s ok, I tried it live on camera during one Staffroom). Other days, we would discuss how difficult we were finding teaching, isolation or life in general during a pandemic.

An honest environment

One of the things that people continuously mentioned was that Staffroom was a safe place where they felt they could share, be listened to, and be understood. We made it clear that no one had to speak unless they wanted to. I made a point of always being completely honest about my own mental health. As a person who had suffered from depression and anxiety in the past, it was no surprise to me when I was diagnosed with both near the end of 2020, and I was fortunate enough to get virtual therapy. I shared my story with the group, which allowed attendees to feel more comfortable being open and talking about their own struggles, in some cases leading to their own diagnosis and getting much-needed support.

Frederick Ballew.

Staffroom has been the best ‘out of my comfort zone’ leap that I have ever taken. I have met educators from all over the world and learned that there are more things that unite us than divide us in this world of education.” – Frederick Ballew, Minnesota, USA

People would join Staffroom to share new jobs, engagements, even cross-country moves, but equally they would join after losing a loved one or hearing of a pupil sick in hospital. Staffroom became a safe haven for teachers, coaches, IT directors, and pretty much anyone involved in technology within education. It is a place where we could bond over shared experience, share a joke, ask questions, get ideas, and even plan our futures.

Do not underestimate the power of connections, and of sharing your story.

Cat Lamin

Alongside Staffroom, I also built a website to allow teachers to share their mental health stories and to feel a little less alone (mentalhealthineducation.com). I continue to host regular Staffrooms, although less frequently. 18 months ago, we needed a chance to talk three times a week, but now we meet two or three times a month instead. You can find current Staffroom dates at www.globalgeg.org/events. If you take one thing away from this article, however, it is this: do not underestimate the power of connections, and of sharing your story.

Cat Lamin is a Raspberry Pi Certified Educator, CAS Master Teacher, and Google Certified Innovator who works as a freelance trainer and coach, supporting schools with digital strategy and enabling educators to use technology more effectively. For running this regular mental health staffroom, she was awarded a Mental Health Champion Award from Edufuturist.

Share your thoughts about Hello World with me!

Your insights are invaluable to help us make Hello World as useful as it can be for computing educators around the globe. Hello World is a magazine for educators from educators — so if you are interested in having a 20-minute chat with me about what you like about the magazine, and what you would like to change, then please sign up here. I look forward to speaking with you.

Download Hello World for free

The brand-new issue of our free Hello World magazine for computing educators focuses on all things health and well-being.

Cover of issue 17 of Hello World.

It is full of inspiring stories and practical ideas for teaching your learners about computing in this context, and supporting them to use digital technologies in beneficial ways.

Download the new issue of Hello World for free today:

To never miss a new issue, you can subscribe to Hello World for free. Also check out the first-ever special edition of Hello World, The Big Book of Pedagogy. It focuses on approaches to teaching computing in the classroom, and you can download the special edition for free.

Wherever you are in the world, you can listen to our Hello World podcast too! Each episode, we explore a new topic with some of the computing educators who’ve written for the magazine.

The post Cat Lamin on building a global educator family | Hello World #17 appeared first on Raspberry Pi.

Computer science education is a global challenge

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/brookings-report-global-computer-science-education-policy/

For the last two years, I’ve been one of the advisors to the Center for Universal Education at the Brookings Institution, a US-based think tank, on their project to survey formal computing education systems across the world. The resulting education policy report, Building skills for life: How to expand and improve computer science education around the world, pulls together the findings of their research. I’ll highlight key lessons policymakers and educators can benefit from, and what elements I think have been missed.

Woman teacher and female students at a computer

Why a global challenge?

Work on this new Brookings report was motivated by the belief that if our goal is to create an equitable, global society, then we need computer science (CS) in school to be accessible around the world; countries need to educate their citizens about computer science, both to strengthen their economic situation and to tackle inequality between countries. The report states that “global development gaps will only be expected to widen if low-income countries’ investments in these domains falter while high-income countries continue to move ahead” (p. 12).

Student using a Raspberry Pi computer

The report makes an important contribution to our understanding of computer science education policy, providing a global overview as well as in-depth case studies of education policies around the world. The case studies look at 11 countries and territories, including England, South Africa, British Columbia, Chile, Uruguay, and Thailand. The map below shows an overview of the Brookings researchers’ findings. It indicates whether computer science is a mandatory or elective subject, whether it is taught in primary or secondary schools, and whether it is taught as a discrete subject or across the curriculum.

A world map showing countries' situation in terms of computing education policy.
Computer science education across the world. Figure courtesy of Brookings Institution (click to enlarge).

It’s a patchy picture, demonstrating both countries’ level of capacity to deliver computer science education and the different approaches countries have taken. Analysis in the Brookings report shows a correlation between a country’s economic position and implementation of computer science in schools: no low-income countries have implemented it at all, while over 20% of high-income countries have mandatory computer science education at both primary and secondary level. 

Capacity building: IT infrastructure and beyond

Given these disparities, there is a significant focus in the report on what IT infrastructure countries need in order to deliver computer science education. This infrastructure needs to be preceded by investment (funds to afford it) and policy (a clear statement of intent and an implementation plan). Many countries that the Brookings report describes as having no computer science education may still be struggling to put these in place.

A young woman codes in a computing classroom.

The recently developed CAPE (capacity, access, participation, experience) framework offers another way of assessing disparities in education. To have capacity to make computer science part of formal education, a country needs to put in place the following elements:

My view is that countries that are at the beginning of this process need to focus on IT infrastructure, but also on the other elements of capacity. The Brookings report touches on these elements of capacity as well. Once these are in place in a country, the focus can shift to the next level: access for learners.

Comparing countries — what policies are in place?

In their report, the Brookings researchers identify seven complementary policy actions that a country can take to facilitate implementation of computer science education:

  1. Introduction of ICT (information and communications technology) education programmes
  2. Requirement for CS in primary education
  3. Requirement for CS in secondary education
  4. Introduction of in-service CS teacher education programmes
  5. Introduction of pre-service teacher CS education programmes
  6. Setup of a specialised centre or institution focused on CS education research and training
  7. Regular funding allocated to CS education by the legislative branch of government

The figure below compares the 11 case-study regions in terms of how many of the seven policy actions have been taken, what IT infrastructure is in place, and when the process of implementing CS education started.

A graph showing the trajectory of 11 regions of the world in terms of computing education policy.
Trajectories of regions in the 11 case studies. Figure courtesy of Brookings Institution (click to enlarge).

England is the only country that has taken all seven of the identified policy actions, having already had nation-wide IT infrastructure and broadband connectivity in place. Chile, Thailand, and Uruguay have made impressive progress, both on infrastructure development and on policy actions. However, it’s clear that making progress takes many years — Chile started in 1992, and Uruguay in 2007 —  and requires a considerable amount of investment and government policy direction.

Computing education policy in England

The first case study that Brookings produced for this report, back in 2019, related to England. Over the last 8 years in England, we have seen the development of computing education in the curriculum as a mandatory subject in primary and secondary schools. Initially, funding for teacher education was limited, but in 2018, the government provided £80 million of funding to us and a consortium of partners to establish the National Centre for Computing Education (NCCE). Thus, in-service teacher education in computing has been given more priority in England than probably anywhere else in the world.

Three young people learn coding at laptops supported by a volunteer at a CoderDojo session.

Alongside teacher education, the funding also covered our development of classroom resources to cover the whole CS curriculum, and of Isaac Computer Science, our online platform for 14- to 18-year-olds learning computer science. We’re also working on a £2m government-funded research project looking at approaches to improving the gender balance in computing in English schools, which is due to report results next year.

The future of education policy in the UK as it relates to AI technologies is the topic of an upcoming panel discussion I’m inviting you to attend.

school-aged girls and a teacher using a computer together.

The Brookings report highlights the way in which the English government worked with non-profit organisations, including us here at the Raspberry Pi Foundation, to deliver on the seven policy actions. Partnerships and engagement with stakeholders appear to be key to effectively implementing computer science education within a country. 

Lessons learned, lessons missed

What can we learn from the Brookings report’s helicopter view of 11 case studies? How can we ensure that computer science education is going to be accessible for all children? The Brookings researchers draw our six lessons learned in their report, which I have taken the liberty of rewording and shortening here:

  1. Create demand
  2. Make it mandatory
  3. Train teachers
  4. Start early
  5. Work in partnership
  6. Make it engaging

In the report, the sixth lesson is phrased as, “When taught in an interactive, hands-on way, CS education builds skills for life.” The Brookings researchers conclude that focusing on project-based learning and maker spaces is the way for schools to achieve this, which I don’t find convincing. The problem with project-based learning in maker spaces is one of scale: in my experience, this approach only works well in a non-formal, small-scale setting. The other reason is that maker spaces, while being very engaging, are also very expensive. Therefore, I don’t see them as a practicable aspect of a nationally rolled-out, mandatory, formal curriculum.

When we teach computer science, it is important that we encourage young people to ask questions about ethics, power, privilege, and social justice.

Sue Sentance

We have other ways to make computer science engaging to all learners, using a breadth of pedagogical approaches. In particular, we should focus on cultural relevance, an aspect of education the Brookings report does not centre. Culturally relevant pedagogy is a framework for teaching that emphasises the importance of incorporating and valuing all learners’ knowledge, heritage, and ways of learning, and promotes the development of learners’ critical consciousness of the world. When we teach computer science, it is important that we encourage young people to ask questions about ethics, power, privilege, and social justice.

Three teenage boys do coding at a shared computer during a computer science lesson.

The Brookings report states that we need to develop and use evidence on how to teach computer science, and I agree with this. But to properly support teachers and learners, we need to offer them a range of approaches to teaching computing, rather than just focusing on one, such as project-based learning, however valuable that approach may be in some settings. Through the NCCE, we have embedded twelve pedagogical principles in the Teach Computing Curriculum, which is being rolled out to six million learners in England’s schools. In time, through this initiative, we will gain firm evidence on what the most effective approaches are for teaching computer science to all students in primary and secondary schools.

Moving forward together

I believe the Brookings Institution’s report has a huge contribution to make as countries around the world seek to introduce computer science in their classrooms. As we can conclude from the patchiness of the CS education world map, there is still much work to be done. I feel fortunate to be living in a country that has been able and motivated to prioritise computer science education, and I think that partnerships and working across stakeholder groups, particularly with schools and teachers, have played a large part in the progress we have made.

To my mind, the challenge now is to find ways in which countries can work together towards more equity in computer science education around the world. The findings in this report will help us make that happen.


PS We invite you to join us on 16 November for our online panel discussion on what the future of the UK’s education policy needs to look like to enable young people to navigate and shape AI technologies. Our speakers include UK Minister Chris Philp, our CEO Philip Colligan, and two young people currently in education. Tabitha Goldstaub, Chair of the UK government’s AI Council, will be chairing the discussion.

Sign up for your free ticket today and submit your questions to our panel!

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Engaging Black students in computing at UK schools — interview with Joe Arday

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/engaging-black-students-in-computing-uk-schools-joe-arday/

Joe Arday.

On the occasion of Black History Month UK, we speak to Joe Arday, Computer Science teacher at Woodbridge High School in Essex, UK, about his experiences in computing education, his thoughts about underrepresentation of Black students in the subject, and his ideas about what needs to be done to engage more Black students.

To start us off, can you share some of your thoughts about Black History Month as an occasion?

For me personally it’s an opportunity to celebrate our culture, but my view is it shouldn’t be a month — it should be celebrated every day. I am of Ghanaian descent, so Black History Month is an opportunity to share my culture in my school and my community. Black History Month is also an opportunity to educate yourself about what happened to the generations before you. For example, my parents lived through the Brixton riots. I was born in 1984, and I got to secondary school before I heard about the Brixton riots from a teacher. But my mother made sure that, during Black History Month, we went to a lot of extracurricular activities to learn about our culture.

For me it’s about embracing the culture I come from, being proud to be Black, and sharing that culture with the next generation, including my two kids, who are of mixed heritage. They need to know where they come from, and know their two cultures.

Tell us a bit about your own history: how did you come to computing education?

So I was a tech professional in the finance sector, and I was made redundant when the 2008 recession hit. I did a couple of consulting jobs, but I thought to myself, “I love tech, but in five years from now, do I really want to be going from job to job? There must be something else I can do.”

At that time there was a huge drive to recruit more teachers to teach what was called ICT back then and is now Computing. As a result, I started my career as a teacher in 2010. As a former software consultant, I had useful skills for teaching ICT. When Computing was introduced instead, I was fortunate to be at a school that could bring in external CPD (continued professional development) providers to teach us about programming and build our understanding and skills to deliver the new curriculum. I also did a lot of self-study and spoke to lots of teachers at other schools about how to teach the subject.

What barriers or support did you encounter in your teaching career? Did you have role models when you went into teaching?

Not really — I had to seek them out. In my environment, there are very few Black teachers, and I was often the only Black Computer Science teacher. A parent once said to me, “I hope you’re not planning to leave, because my son needs a role model in Computer Science.” And I understood exactly what she meant by that, but I’m not even a role model, I’m just someone who’s contributing to society the best way I can. I just want to pave the way for the next generation, including my children.

My current school is supporting me to lead all the STEM engagement for students, and in that role, some of the things I do are running a STEM club that focuses a lot on computing, and running new programmes to encourage girls into tech roles. I’ve also become a CAS Master Teacher and been part of a careers panel at Queen Mary University London about the tech sector, for hundreds of school students from across London. And I was selected by the National Centre for Computing Education as one of their facilitators in the Computer Science Accelerator CPD programme.

But there’s been a lack of leadership opportunities for me in schools. I’ve applied for middle-leadership roles and have been told my face doesn’t fit in an interview in a previous school. And I’m just as skilled and experienced as other candidates: I’ve been acting Head of Department, acting Head of Year — what more do I need to do? But I’ve not had access to middle-leadership roles. I’ve been told I’m an average teacher, but then I’ve been put onto dealing with “difficult” students if they’re Black, because a few of my previous schools have told me that I was “good at dealing with behaviour”. So that tells you about the role I was pigeonholed into.

It is very important for Black students to have role models, and to have a curriculum that reflects them.

Joe Arday

I’ve never worked for a Black Headteacher, and the proportion of Black teachers in senior leadership positions is very low, only 1%. So I am considering moving into a different area of computing education, such as edtech or academia, because in schools I don’t have the opportunities to progress because of my ethnicity.

Do you think this lack of leadership opportunities is an experience other Black teachers share?

I think it is, that’s why the number of Black teachers is so low. And as a Black student of Computer Science considering a teaching role, I would look around my school and think, if I go into teaching, where are the opportunities going to come from?

Black students are underrepresented in computing. Could you share your thoughts about why that’s the case?

There’s a lack of role models across the board: in schools, but also in tech leadership roles, CEOs and company directors. And the interest of Black students isn’t fostered early on, in Year 8, Year 9 (ages 12–14). If they don’t have a teacher who is able to take them to career fairs or to tech companies, they’re not going to get exposure, they’re not going to think, “Oh, I can see myself doing that.” So unless they have a lot of interest already, they’re not going to pick Computer Science when it comes to choosing their GCSEs, because it doesn’t look like it’s for them.

But we need diverse people in computing and STEM, especially girls. As the father of a boy and a girl of mixed heritage, that’s very important to me. Some schools I’ve worked in, they pushed computer science into the background, and it’s such a shame. They don’t have the money or the time for their teachers to do the CPD to teach it properly. And if attitudes at the top are negative, that’s going to filter down. But even if students don’t go into the tech industry, they still need digital skills to go into any number of sectors. Every young person needs them.

It is very important for Black students to have role models, and to have a curriculum that reflects them. Students need to see themselves in their lessons and not feel ignored by what is being taught. I was very fortunate to be selected for the working group for the Raspberry Pi Foundation’s culturally relevant teaching guidelines, and I’m currently running some CPD for teachers around this. I bet in the future Ofsted will look at how diverse the curriculum of schools is.

What do you think tech organisations can do in order to engage more Black students in computing?

I think tech organisations need to work with schools and offer work experience placements. When I was a student, 20 years ago, I went on a placement, and that set me on the right path. Nowadays, many students don’t do work experience, they are school leavers before they do an internship. So why do so many schools and organisations not help 14- or 15-year-olds spend a week or two doing a placement and learning some real-life skills?

A mentor explains Scratch code using a projector in a coding club session.

And I think it’s very important for teachers to be able to keep up to date with the latest technologies so they can support their students with what they need to know when they start their own careers, and can be convincing doing it. I encourage my GCSE Computer Science students to learn about things like cloud computing and cybersecurity, about the newest types of technologies that are being used in the tech sector now. That way they’re preparing themselves. And if I was a Headteacher, I would help my students gain professional certifications that they can use when they apply for jobs.

What is a key thing that people in computing education can do to engage more Black students?

Teachers could run a STEM or computing club with a Black History Month theme to get Black students interested — and it doesn’t have to stop at Black History Month. And you can make computing cross-curricular, so there could be a project with all teachers, where each one runs a lesson that involves a bit of coding, so that all students can see that computing really is for everyone.

What would you say to teachers to encourage them to take up Computer Science as a subject?

Because of my role working for the NCCE, I always encourage teachers to join the NCCE’s Computer Science Accelerator programme and to retrain to teach Computer Science. It’s a beautiful subject, all you need to do is give it a chance.

Thank you, Joe, for sharing your thoughts with us!

Joe was part of the group of teachers we worked with to create our practical guide on culturally relevant teaching in the computing classroom. You can download it as a free PDF now to help you think about how to reflect all your students in your lessons.

The post Engaging Black students in computing at UK schools — interview with Joe Arday appeared first on Raspberry Pi.

Hello World’s first-ever special edition is here!

Post Syndicated from Gemma Coleman original https://www.raspberrypi.org/blog/hello-world-big-book-of-computing-pedagogy/

Hello World, our free magazine for computing and digital making educators, has just published its very first special edition: The Big Book of Computing Pedagogy!

“When I started to peruse the draft for The Big Book of Computing Pedagogy, I was simply stunned.”

Monica McGill, founder & CEO of CSEDResearch.org

Cover of The Big Book of Computing Pedagogy.

This special edition focuses on practical approaches to teaching computing in the classroom, and includes some of our favourite pedagogically themed articles from previous issues of Hello World, as well as a few never-seen-before pieces. It is structured around twelve pedagogical principles, first developed by us as part of our work related to the National Centre for Computing Education in England. These twelve principles are based on up-to-date research around the best ways of approaching the teaching and learning of computing.

A girl doing a physical computing project with Raspberry Pi hardware.

Grounded in research and practice

Computing education is still relatively new, and it’s a field that’s constantly changing and adapting. Despite leaving school less than ten years ago, I remember my days in the computer lab being limited to learning about how to add animations on PowerPoints and trying out basic Excel formulas (and yes, there was still the odd mouse with a ball knocking about!).

A tweet praising The Big Book of Computing Pedagogy.
The Big Book of Computing Pedagogy — a big hit with educators!

Computing education research is even younger, and we are proud to be an important part of this growing space. As an organisation, we engage in rigorous original research around computing education and learning for young people, and we share all of our research work through blogs, reports, research seminars, and academic publications. We’re particularly proud to have partnered with the University of Cambridge to establish the Raspberry Pi Computing Education Research Centre

12 principles of computing pedagogy: lead with concepts; structure lessons; make concrete; unplug, unpack, repack; work together; read and explore code first; foster program comprehension; model everything; challenge misconceptions; create projects; get hands-on; add variety.
Our special edition of Hello World is organised around twelve pedagogical principles.

The Big Book of Computing Pedagogy represents another way in which we bring research and practice to computing educators in an accessible and engaging way. The book aims to be an educator’s companion to learning about tried and tested approaches to teaching computing.

A tweet praising The Big Book of Computing Pedagogy.
The perfect morning read for computing educators.

It includes articles on techniques for fostering program comprehension, advice for bringing physical computing to your classroom, and introductions to frameworks for structuring your computing lessons. As with all Hello World content, we’re bridging the gap between research and practice by giving you accessible chunks of research, followed by stories of trusty educators who have tried out the approaches in their classroom or educational space.

A tweet praising The Big Book of Computing Pedagogy.
Teachers are jumping for joy at this special edition.

Monica McGill, founder and CEO of CSEDResearch.org, says about Hello World’s latest offering, “When I started to peruse the draft for The Big Book of Computing Pedagogy, I was simply stunned. I found the ready-to-consume content to be solidly based on research evidence and tried-and-true best practices from teachers themselves. This resource provides valuable insights into introducing computing to students via unplugged activities, integrating the Predict–Run–Investigate–Modify–Make (PRIMM) pedagogical model, and introducing physical devices for computing — all written in a way that teachers can adopt and use in their own classrooms.”

We’ve been thrilled to see the reaction of educators to this special edition, with many teachers already using it as a reference guide and for a spot of CPD. Why not join them and download it for free today?

Subscribe now to get each new Hello World — whether regular issue or special edition — straight to your digital inbox, for free! And if you’re based in the UK and do paid or unpaid work in education, you can subscribe for free print issues.

PS Have you listened to our Hello World podcast yet? A new episode has just come out, and it’s great! Listen and subscribe wherever you get your podcasts.

The post Hello World’s first-ever special edition is here! appeared first on Raspberry Pi.

Take part in the UK Bebras Challenge 2021 for schools!

Post Syndicated from Duncan Maidens original https://www.raspberrypi.org/blog/uk-bebras-challenge-2021-for-schools/

The annual UK Bebras Computational Thinking Challenge is back to provide fun, brain-teasing puzzles for schools from 8 to 19 November!

The UK Bebras Challenge 2021 runs from 8 to 19 November.

In the free Bebras Challenge, your students get to practise their computational thinking skills while solving a set of accessible, puzzling, and engaging tasks over 40 minutes. It’s tailored for age groups from 6 to 18.

“I just want to say how much the children are enjoying this competition. It is the first year we have entered, and I have students aged 8 to 11 participating in my Computing lessons, with some of our older students also taking on the challenges. It is really helping to challenge their thinking, and they are showing great determination to try and complete each task!”

– A UK-based teacher

Ten key facts about Bebras

  1. It’s free!
  2. The challenge takes place in school, and it’s a great whole-school activity
  3. It’s open to learners aged 6 to 18, with activities for different age groups
  4. The challenge is made up of a set of short tasks, and completing it takes 40 minutes
  5. The closing date for registering your school is 4 November
  6. Your learners need to complete the challenge between 8 and 19 November 2021
  7. All the marking is done for you (hurrah!)
  8. You’ll receive the results and answers the week after the challenge ends, so you can go through them with your learners and help them learn more
  9. The tasks are logical thinking puzzles, so taking part does not require any computing knowledge
  10. There are practice questions you can use to help your learners prepare for the challenge, and throughout the year to help them practice their computational thinking

Do you want to support your learners to take on the Bebras Challenge? Then register your school today!

Remember to sign up by 4 November!

The benefits of Bebras

Bebras is an international challenge that started in Lithuania in 2004 and has grown into a worldwide event. The UK became involved in Bebras for the first time in 2013, and the number of participating students has increased from 21,000 in the first year to more than half a million over the last two years! Internationally, nearly 2.5 million learners took part in 2020 despite the disruptions to schools.

On the left, a drawing of a bracelet made of stars and moons.
On the left, a bracelet design from an activity for ages 10–12. On the right, a password checker from an activity for ages 14–16.

Bebras, brought to you in the UK by us and Oxford University, is a great way to give your learners of all age groups a taste of the principles behind computing by engaging them in fun problem-solving activities. The challenge results highlight computing principles, so Bebras can be educational for you as a teacher too.

Throughout the year, questions from previous years of the challenge are available to registered teachers on the bebras.uk website, where you can create self-marking quizzes to help you deliver the computational thinking part of the curriculum for your classes.

You can register your school at bebras.uk/admin.

Learn more about our work to support learners with computational thinking.

The post Take part in the UK Bebras Challenge 2021 for schools! appeared first on Raspberry Pi.

Learn the fundamentals of AI and machine learning with our free online course

Post Syndicated from Michael Conterio original https://www.raspberrypi.org/blog/fundamentals-ai-machine-learning-free-online-course/

Join our free online course Introduction to Machine Learning and AI to discover the fundamentals of machine learning and learn to train your own machine learning models using free online tools.

Drawing of a machine learning robot helping a human identify spam at a computer.

Although artificial intelligence (AI) was once the province of science fiction, these days you’re very likely to hear the term in relation to new technologies, whether that’s facial recognition, medical diagnostic tools, or self-driving cars, which use AI systems to make decisions or predictions.

By the end of this free online course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.

Machine learning — a brief overview

You’ll also often hear about AI systems that use machine learning (ML). Very simply, we can say that programs created using ML are ‘trained’ on large collections of data to ‘learn’ to produce more accurate outputs over time. One rather funny application you might have heard of is the ‘muffin or chihuahua?’ image recognition task.

Drawing of a machine learning ars rover trying to decide whether it is seeing an alien or a rock.

More precisely, we would say that a ML algorithm builds a model, based on large collections of data (the training data), without being explicitly programmed to do so. The model is ‘finished’ when it makes predictions or decisions with an acceptable level of accuracy. (For example, it rarely mistakes a muffin for a chihuahua in a photo.) It is then considered to be able to make predictions or decisions using new data in the real world.

It’s important to understand AI and ML — especially for educators

But how does all this actually work? If you don’t know, it’s hard to judge what the impacts of these technologies might be, and how we can be sure they benefit everyone — an important discussion that needs to involve people from across all of society. Not knowing can also be a barrier to using AI, whether that’s for a hobby, as part of your job, or to help your community solve a problem.

some things that machine learning and AI systems can be built into: streetlamps, waste collecting vehicles, cars, traffic lights.

For teachers and educators it’s particularly important to have a good foundational knowledge of AI and ML, as they need to teach their learners what the young people need to know about these technologies and how they impact their lives. (We’ve also got a free seminar series about teaching these topics.)

To help you understand the fundamentals of AI and ML, we’ve put together a free online course: Introduction to Machine Learning and AI. Over four weeks in two hours per week, you’ll learn how machine learning can be used to solve problems, without going too deeply into the mathematical details. You’ll also get to grips with the different ways that machines ‘learn’, and you will try out online tools such as Machine Learning for Kids and Teachable Machine to design and train your own machine learning programs.

What types of problems and tasks are AI systems used for?

As well as finding out how these AI systems work, you’ll look at the different types of tasks that they can help us address. One of these is classification — working out which group (or groups) something fits in, such as distinguishing between positive and negative product reviews, identifying an animal (or a muffin) in an image, or spotting potential medical problems in patient data.

You’ll also learn about other types of tasks ML programs are used for, such as regression (predicting a numerical value from a continuous range) and knowledge organisation (spotting links between different pieces of data or clusters of similar data). Towards the end of the course you’ll dive into one of the hottest topics in AI today: neural networks, which are ML models whose design is inspired by networks of brain cells (neurons).

drawing of a small machine learning neural network.

Before an ML program can be trained, you need to collect data to train it with. During the course you’ll see how tools from statistics and data science are important for ML — but also how ethical issues can arise both when data is collected and when the outputs of an ML program are used.

By the end of the course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.

Sign up to the course today, for free

The Introduction to Machine Learning and AI course is open for you to sign up to now. Sign-ups will pause after 12 December. Once you sign up, you’ll have access for six weeks. During this time you’ll be able to interact with your fellow learners, and before 25 October, you’ll also benefit from the support of our expert facilitators. So what are you waiting for?

Share your views as part of our research

As part of our research on computing education, we would like to find out about educators’ views on machine learning. Before you start the course, we will ask you to complete a short survey. As a thank you for helping us with our research, you will be offered the chance to take part in a prize draw for a £50 book token!

Learn more about AI, its impacts, and teaching learners about them

To develop your computing knowledge and skills, you might also want to:

If you are a teacher in England, you can develop your teaching skills through the National Centre for Computing Education, which will give you free upgrades for our courses (including Introduction to Machine Learning and AI) so you’ll receive certificates and unlimited access.

The post Learn the fundamentals of AI and machine learning with our free online course appeared first on Raspberry Pi.

Inspiring learners about computing through health and well-being projects | Hello World #17

Post Syndicated from Gemma Coleman original https://www.raspberrypi.org/blog/inspiring-learners-computing-health-well-being-projects-hello-world-17/

Your brand-new issue of the free Hello World magazine for computing educators focuses on all things health and well-being, featuring useful tools for educators, great ideas for schools, and inspiring projects, ideas, and resources from teachers around the world!

Cover of issue 17 of Hello World.

One such project was created by the students of James Abela, Head of Computing at Garden International School in Kuala Lumpur, Raspberry Pi Certified Educator, founder of the South East Asian Computer Science Teachers Association, and author of The Gamified Classroom:

Protecting children from breathing hazardous air

In 2018, Indonesia burned approximately 529,000 hectares of land. That’s an area more than three times the size of Greater London, or almost the size of Brunei. With so much forest being burned, the whole region felt the effects of the pollution. Schools frequently had to ban outdoor play and PE lessons, and on some days schools were closed completely. Many schools in the region had an on-site CO2 detector to know when pollution was bad, but by the time the message could get out, children had already been breathing in the polluted air for several minutes.

A forest fire.
The air pollution from a forest fire gets dispersed by winds and can spread way beyond the area of the fire.

My Year 12 students (aged 16–17) followed the news and weather forecasts intently, and we all started to see how the winds from Singapore and Sumatra were sending pollution to us in Kuala Lumpur. We also realised that if we had measurements from around the city, we might have some visibility as to when pollution was likely to affect our school.

Making room for student-led projects

I’ve always encouraged my students to do their own projects, because it gives programming tasks meaning and creates something that they can be genuinely proud of. The other benefit is that it is something to talk about in university essays and interviews, especially as they often need to do extensive research to solve the problems central to their projects.

This project was […] a genuine passion project in every sense of the word.

James Abela

This project was much more than this: it was a genuine passion project in every sense of the word. Three of my students approached me with the idea of tracking CO2 to give schools a better idea of when there was pollution and which way it was going. They had had some experience of using Raspberry Pi computers, and knew that it was possible to use them to make weather stations, and that the latest versions had wireless LAN capability that they could use. I agreed to support them during allocated programming time, and to help them reach out to other schools.

Circuit design of the CO2 sensor using just Raspberry Pi, designed on circuito.io

I was able to offer students support with this project because I flip quite a lot of the theory in my class. Flipped learning is a teaching approach in which some direct instruction, for example reading articles or watching specific videos, is done at home. This enables more class time to be used to answer questions, work through higher-order tasks, or do group work, and it creates more supervised coding time.

I was able to offer students support with this project because I flip quite a lot of the theory in my class.

James Abela

I initially started doing this because when I set coding challenges for homework, I often had students who confessed they spent all night trying to solve it, only for me to glance at the code and notice a missing colon or indentation issue. I began flipping the less difficult theory for students to do as homework, to create more programming time in class where we could resolve issues more quickly. This then evolved into a system where students could work much more at their own pace and eventually led to a point at which older students could, in effect, learn through their own projects, such as the pollution monitor.

Building the pollution monitor

The students started by looking at existing weather station projects — for example, there is an excellent tutorial on the Raspberry Pi Foundation’s projects site. Students discovered that wind data is relatively easy to get over a larger area, but the key component would be something to measure CO2. […]

Check out issue 17 of Hello World to read the rest of James’s article and find out all the details about the hardware and software his students used for this passion project. He says:

This project really helped these students to decide whether they enjoyed the hardware side of computing, and solving real-world issues really encouraged them to see computing as a practical subject. This is a message that has really resonated with other students, and we’ve since doubled the number of students taking A level computer science.

James Abela

Download the new Hello World for free!

Issue 17 of Hello World is bursting with inspiring ideas for teaching your learners about computing in the context of health and well-being. And you’ll find lots more great content in its 100 pages!

James’s article is also a wonderful example of an educator empowering their students to build a tech project they care about. You’ll discover more insights and practical tips on making computing relevant to all your learners in the following articles of the new Hello World issue:

  • Inspiring Young People With Contexts They Care About
  • Computing for all: Designing a Culturally Relevant Curriculum
  • Going Back to Basics: Part 2 — a follow-on from issue 16 about how to take beginner digital makers through their first physical computing projects

Download the new issue of Hello World for free today:

If you’re an educator based in the UK, you can subscribe to receive each new issue in print completely free! And wherever you are in the world, don’t forget to listen to the Hello World podcast, where each episode we dive into a new topic from the magazine with some of the computing educators who’ve written for us.

The post Inspiring learners about computing through health and well-being projects | Hello World #17 appeared first on Raspberry Pi.

Engaging Black students in computing at school — interview with Lynda Chinaka

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/engaging-black-students-in-computing-school-lynda-chinaka/

Lynda Chinaka.

On the occasion of Black History Month UK, we speak to Lynda Chinaka, Senior Lecturer in Computing in Education at the University of Roehampton, about her experiences in computing education, her thoughts about underrepresentation of Black students in the subject, and her ideas about what needs to be done to engage more Black students.

Lynda, to start us off, can you share your thoughts about Black History Month?

Black history is a really important topic, obviously, and I think that, when Black History Month was first introduced, it was very powerful — and it continues to be in certain places. But I think that, for where we are as a society, it’s time to move past talking about Black history for only one month of the year, albeit an important, focused celebration. And certainly that would include integrating Black history and Black figures across subjects in school. That would be a very useful way to celebrate the contributions that Black people have made, and continue to make, to society. Children need to be taught a history in which they are included and valued. Good history is always a matter of different perspectives. Too often in schools, children experience a single perspective.  

Please tell me a bit about your own history: how did you come to computing education as a field? What were the support or barriers you encountered?

In terms of my journey, I’ve always been passionate about Computing — formerly ICT. I’ve been a Computing subject lead in schools, moving on into senior management. Beyond my career in schools, I have worked as an ICT consultant and as a Teacher Leader for a London authority. During that time, my interest in Computing/ICT led me to undertake an MA in Computing in Education at King’s College London. This led me to become a teacher trainer in my current role. In some sense, I’m carrying on the work I did with the local authorities, but in a university setting. At the University of Roehampton, I teach computing to BA Primary Education and PGCE students. Training teachers is something that I’m very much interested in. It’s about engaging student teachers, supporting them in developing their understanding of Computing in the primary phases. Students learn about the principles of computing, related learning theories, and how children think and learn. Perhaps more importantly, I am keen to instil a love of the subject and broaden their notions about computing.

A teacher attending Picademy laughs as she works through an activity

In terms of the support I’ve received, I’ve worked in certain schools where Computing was really valued by the Headteacher, which enabled me to promote my vision for the subject. Supportive colleagues made a difference in their willingness take on new initiatives that I presented. I have been fortunate to work in local authorities that have been forward-thinking; one school became a test bed for Computing. So in that sense, schools have supported me. But as a Black person, a Black woman in particular, I would say that I faced barriers throughout my career. And those barriers have been there since childhood. In the Black community, people experience all sorts of things, and prejudice and barriers have been at play in my career.

Prejudice sometimes is very overt. An example I think I can share because it prevented me from getting a job: I went for an interview in a school. It was a very good interview, the Headteacher told me, “It was fantastic, you’re amazing, you’re excellent,” the problem was that there weren’t “enough Black pupils”, so she “didn’t see the need…”. And this is a discussion that was shared with me. Now in 2021 a Headteacher wouldn’t say that, but let’s just wind the clock back 15 years. These are the kinds of experiences that you go through as a Black teacher.

So what happens is, you tend to build up a certain resilience. People’s perceptions and low expectations of me have been a hindrance. This can be debilitating. You get tired of having to go through the same thing, of having to overcome negativity. Yes, I would say this has limited my progress. Obviously, I am speaking about my particular experiences as a Black woman, but I would say that these experiences are shared by many people like me.

An educator teaches students to create with technology.

But it’s my determination and the investment I’ve made that has resulted in me staying in the field. And a source of support for me is always Black colleagues, they understand the issues that are inherent within the profession. 

Black students are underrepresented in Computing as a subject. Drawing on your own work and experiences, could you share your thoughts about why that’s the case?

There need to be more Black teachers, because children need to see themselves represented in schools. As a Black teacher, I know that I have made a difference to Black children in my class who had a Black role model in front of them. When we talk about the poor performance of Black pupils, we need to be careful not to blame them for the failures of the education system. Policy makers, Headteachers, teachers, and practitioners need to be a lot more self-aware and examine the impact of racism in education. People need to examine their own policies and practice, especially people in positions of power.

A lot of collective work needs to be done.

Lynda Chinaka

Some local authorities do better than others, and some Headteachers I’ve worked with have been keen to build a diverse staff team. Black people are not well-represented at all in education. Headteachers need to be more proactive about their staff teams and recruitment. And they need to encourage Black teachers to go for jobs in senior management.

An educator helps a young person with a computing problem.

In all settings I taught in, no matter how many students of colour there were, these students would experience something in my classroom that their white counterparts had experienced all their lives: they would leave their home and come to school and be taught by someone who looks like them and perhaps speaks the same language as them. It’s enormously affirming for children to have that experience. And it’s important for all children actually, white children as well. Seeing a Black person teaching in the classroom, in a position of power or influence — it changes their mindset, and that ultimately changes perspectives.

So in terms of that route into Computing, Black students need to see themselves represented.

Why do you think it’s important to teach young people about Computing?

It’s absolutely vital to teach children about Computing. As adults, they are going to participate in a future that we know very little about, so I think it’s important that they’re taught computer science approaches, problem solving and computational thinking. So children need to be taught to be creators and not simply passive users of technology.

A Coolest Projects participant

One of the things some of my university students say is, “Oh my goodness, I can’t teach Computing, all the children know much more than me.”, but actually, that’s a little bit of a myth, I think. Children are better at using technologies than solving computing problems. They need to learn a range of computational approaches for solving problems. Computing is a life skill; it is the future. We saw during the pandemic the effects of digital inequity on pupils.

What do you think needs to change in computing education, the tech sector, or elsewhere in order to engage more Black students in Computing?

In education, we need to look at the curriculum and how to decolonise it to really engage young people. This also includes looking out for bias and prejudice in the things that are taught. Even when you’re thinking about specific computer science topics. So for example, the traditional example for algorithm design is making a cup of tea. But tea is a universal drink, it originates in China, and as a result of colonialism made its way to India and Kenya. So we drink tea universally, but the method (algorithm) for making tea doesn’t necessarily always include a china tea pot or a tea bag. There are lots of ways to introduce it, thinking about how it’s prepared in different cultures, say Kenya or the Punjab, and using that as a basis for developing children’s algorithmic thinking. This is culturally relevant. It’s about bringing the interests and experiences children have into the classroom.

Young women in a computing lesson.

For children to be engaged in Computing, there needs to be a payoff for them. For example, I’ve seen young people developing their own African emojis. They need to see a point to it! They don’t necessarily have to become computer scientists or software engineers, but Computing should be an avenue that opens for them because they can see it as something to further their own aims, their own causes. Young people are very socially and politically aware. For example, Black communities are very aware of the way that climate change affects the Global South and could use data science to highlight this. Many will have extended family living in these regions that are affected now.

So you don’t compromise on the quality of your teaching, and it require teachers to be more reflective. There is no quick fix. For example, you can’t just insert African masks into a lesson without exploring their meaning in real depth within the culture they originate from.

So in your Computing or Computer Science lessons, you need to include topics young people are interested in: climate change, discrimination, algorithms and algorithmic bias in software, surveillance and facial recognition. Social justice topics are close to their hearts. You can get them interested in AI and data science by talking about the off-the-shelf datasets that Big Tech uses, and about what impact these have in terms of surveillance and on minority communities specifically. 

Can you talk a bit about the different terms used to describe this kind of approach to education, ‘culturally relevant teaching’ and ‘decolonising the curriculum’?

‘Culturally relevant’ is easier to sit with. ‘Decolonising the curriculum’ provokes a reaction, but it’s really about teaching children about histories and perspectives on curricula that affect us all. We need to move towards a curriculum that is fit for purpose where children are taught different perspectives and truth that they recognise. Even if you’re in a school without any Black children at all, the curriculum still needs to be decolonised so that children can actually understand and benefit from the many ways that topics, events, subjects may be taught.

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

When we think about learning in terms of being culturally relevant and responsive, this is about harnessing children’s heritage, experiences, and viewpoints to engage learners such that the curriculum is meaningful and includes them. The goal here is to promote long-term and consistent engagement with Computing.

What is being missed by current initiatives to increase diversity and Black students’ engagement?

Diversity initiatives are a good step, but we need to give it time. 

The selection process for subjects at GCSE can sometimes affect the uptake of computing. Then there are individual attitudes and experiences of pupils. It has been documented that Black and Asian students have often been in the minority and experience marginalisation, particularly noted in the case of female students in GCSE Computer Science.

ITE (Initial Teacher Education) providers need to consider their partnerships with schools and support schools to be more inclusive. We need more Black teachers, as I said. We also need to democratise pathways for young people getting into computing and STEM careers. Applying to university is one way — there should be others.

Schools could also develop partnerships with organisations that have their roots in the Black community. Research has also highlighted discriminatory practices in careers advice, and in the application and interview processes of Russell Group universities. These need to be addressed.

A students in a computer science lecture.

There are too few Black academics at universities. This can have an impact on student choice and decisions about whether to attend an institution or not. Institutions may seem unwelcoming or unsympathetic. Higher education institutions need to eliminate bias through feedback and measuring course take-up. 

Outside the field of education, tech companies could offer summer schemes, short programmes to stimulate interest amongst young Black people. Really, the people in leadership positions, all the people with the power, need to be proactive.

A lot of collective work needs to be done. It’s a whole pipeline, and everybody needs to play a part.

What in your mind is a key thing right now that people in computing education who want to engage more Black students should do?

You can present children with Black pioneers in computing and tech. They can show Black children how to achieve their goals in life through computing. For example, create podcasts or make lists with various organisations that use data science to further specific causes.

It’s not a one-off, one teacher thing, it’s a project for the whole school.

Lynda Chinaka

Also, it’s not a one-off, one teacher thing, it’s project for the whole school. You need to build it into a whole curriculum map, do all the things you do to build a new curriculum map: get every teacher to contribute, so they take it on, own it, research it, make those links to the national curriculum so it’s relevant. Looking at it in isolation it’s a problem, but it’s a whole school approach that starts as a working group. And it’s senior management that sets the tone, and they really need to be proactive, but you can start by starting a working group. It won’t be implemented overnight. A bit like introducing a school uniform. Do it slowly, have a pilot year group. Get parents in, have a coffee evening, get school governors on board. It’s a whole staff team effort.

People need to recognise the size of the problem and not be discouraged by the fact that things haven’t happened overnight. But people who are in a position of influence need to start by having those conversations, because that’s the only way that change can happen, quite frankly.

Lynda, thank you for sharing your insights with us!

Lynda was one of the advisors in the group we worked with to create our recently published, practical guide on culturally relevant teaching. You can download it as a free PDF now. We hope it will help you kickstart conversations in your setting.

The post Engaging Black students in computing at school — interview with Lynda Chinaka appeared first on Raspberry Pi.

Perspectives on supporting young people in low-income areas to access and engage with computing

Post Syndicated from Hayley Leonard original https://www.raspberrypi.org/blog/young-people-low-income-areas-computing-uk-usa-guyana/

The Raspberry Pi Foundation’s mission is to make computing and digital making accessible to all. To support young people at risk of educational disadvantage because they don’t have access to computing devices outside of school, we’ve set up the Learn at Home campaign. But access is only one part of the story. To learn more about what support these young people need across organisations and countries, we set up a panel discussion at the Tapia Celebration of Diversity in Computing conference.

Two young African women work at desktop computers.

The three panelists provided a stimulating discussion of some key issues in supporting young people in low-income areas in the UK, USA, and Guyana to engage with computing, and we hope their insights are of use to educators, youth workers, and organisations around the world.

The panellists and their perspectives

Our panellists represent three different countries, and all have experience of teaching in schools and/or working with young people outside of the formal education system. Because of the differences between countries in terms of access to computing, having this spread of expertise and contexts allowed the panelists to compare lessons learned in different sectors and locations.

Lenlandlar Singh

Panelist Lenandlar Singh is a Senior Lecturer in the Department of Computer Science at the University of Guyana. In Guyana, there is a range of computing-related courses for high school students, and access to optional qualifications in computer science at A level (age 17–18).

Yolanda Payne.

Panelist Yolanda Payne is a Research Associate at the Constellations Center at Georgia Tech, USA. In the US, computing curricula differ across states, although there is some national leadership through associations, centres, and corporations.

Christina Watson.

Christina Watson is Assistant Director of Design at UK Youth*, UK. The UK has a mandatory computing curriculum for learners aged 5–18, although curricula vary across the four home nations (England, Scotland, Wales, Northern Ireland).

As the moderator, I posed the following three questions, which the panelists answered from their own perspectives and experiences:

  • What are the key challenges for young people to engage with computing in or out of school, and what have you done to overcome these challenges?
  • What do you see as the role of formal and non-formal learning opportunities in computing for these young people?
  • What have you learned that could help other people working with these young people and their communities in the future?

Similarities across contexts

One of the aspects of the discussion that really stood out was the number of similarities across the panellists’ different contexts. 

The first of these similarities was the lack of access to computing amongst young people from low-income families, particularly in more rural areas, across all three countries. These access issues concerned devices and digital infrastructure, but also the types of opportunities in and out of school that young people were able to engage with.

Two girls code at a desktop computer while a female mentor observes them.

Christina (UK) shared results from a survey conducted with Aik Saath, a youth organisation in the UK Youth network (see graphs below). The results highlighted that very few young people in low-income areas had access to their own device for online learning, and mostly their access was to a smartphone or tablet rather than a computer. She pointed out that youth organisations can struggle to provide access to computing not only due to lack of funding, but also because they don’t have secure spaces in which to store equipment.

Lenandlar (Guyana) and Christina (UK) also discussed the need to improve the digital skills and confidence of teachers and youth workers so they can support young people with their computing education. While Lenandlar spoke about recruitment and training of qualified computing teachers in Guyana, Christina suggested that it was less important for youth workers in the UK to become experts in the field and more important for them to feel empowered and confident in supporting young people to explore computing and understand different career paths. UK Youth found that partnering with organisations that provided technical expertise (such as us at the Raspberry Pi Foundation) allowed youth workers to focus on the broader support that the young people needed.

Both Yolanda (US) and Lenandlar (Guyana) discussed the restrictive nature of the computing curriculum in schools, agreeing with Christina (UK) that outside of the classroom, there was more freedom for young people to explore different aspects of computing. All three agreed that introducing more fun and relevant activities into the curriculum made young people excited about computing and reduced stereotypes and misconceptions about the discipline and career. Yolanda explained that using modern, real-life examples and role models was a key part of connecting with young people and engaging them in computing.

What can teachers do to support young people and their families?

Yolanda (US) advocated strongly for listening to students and their communities to help understand what is meaningful and relevant to them. One example of this approach is to help young people and their families understand the economics of technology, and how computing can be used to support, develop, and sustain businesses and employment in their community. As society has become more reliant on computing and technology, this can translate into real economic impact.

A CoderDojo coding session for young people.

Both Yolanda (US) and Lenandlar (Guyana) emphasised the importance of providing opportunities for digital making, allowing students opportunities to become creators rather than just consumers of technology. They also highly recommended providing relevant contexts for computing and identifying links with different careers.

The panellists also discussed the importance of partnering with other education settings, with tech companies, and with non-profit organisations to provide access to equipment and opportunities for students in schools that have limited budgets and capacity for computing. These links can also highlight key role models and help to build strong relationships in the community between businesses and schools.

What is the role of non-formal settings in low-income areas?

All of the panellists agreed that non-formal settings provided opportunities for further exploration and skill development outside of a strict curriculum. Christina (UK) particularly highlighted that these settings helped support young people and families who feel left behind by the education system, allowing them to develop practical skills and knowledge that can help their whole family. She emphasised the strong relationships that can be developed in these settings and how these can provide relatable role models for young people in low-income areas.

A young girl uses a computer.

Tips and suggestions

After the presentation, the panelists responded to the audience’s questions with some practical tips and suggestions for engaging young people in low-income communities with computing:

How do you engage young people who are non-native English speakers with mainly English computing materials?

  • For curriculum materials, it’s possible to use Google Translate to allow students to access them. The software is not always totally accurate but goes some way to supporting these students. You can also try to use videos that have captioning and options for non-English subtitles.
  • We offer translated versions of our free online projects, thanks to a community of dedicated volunteer translators from around the world. Learners can choose from up to 30 languages (as shown in the picture below).
The Raspberry Pi Foundation's projects website, with the drop-down menu to choose a human language highlighted.
Young people can learn about computing in their first language by using the menu on our projects site.

How do you set up partnerships with other organisations?

  • Follow companies on social media and share how you are using their products or tools, and how you are aligned with their goals. This can form the basis of future partnerships.
  • When you are actively applying for partnerships, consider the following points:
    • What evidence do you have that you need support from the potential partner?
    • What support are you asking for? This may differ across potential partners, so make sure your pitch is relevant and tailored to a specific partner.
    • What evidence could you use to show the impact you are already having or previous successful projects or partnerships?

Make use of our free training resources and guides

For anyone wishing to learn computing knowledge and skills, and the skills you need to teach young people in and out of school about these topics, we provide a wide range of free online training courses to cover all your needs. Educators in England can also access the free CPD that we and our consortium partners offer through the National Centre for Computing Education.

To help you support your learners in and out of school to engage with computing in ways that are meaningful and relevant for them, we recently published a guide on culturally relevant teaching.

We also support a worldwide network of volunteers to run CoderDojos, which are coding clubs for young people in local community spaces. Head over to the CoderDojo website to discover more about the free materials and help we’ve got for you.

We would like to thank our panellists Lenandlar Singh, Yolanda Payne, and Christina Watson for sharing their time and expertise, and the Tapia conference organisers for providing a great platform to discuss issues of diversity, equality, and inclusion in computing.


*UK Youth is a leading charity working across the UK with an open network of over 8000 youth organisations. The charity has influence as a sector-supporting infrastructure body, a direct delivery partner, and a campaigner for social change.

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Introducing raspberrypi.com

Post Syndicated from Philip Colligan original https://www.raspberrypi.org/blog/introducing-raspberrypicom/

I am delighted to announce the launch of raspberrypi.com — a new website dedicated to Raspberry Pi computers and associated technologies. Head on over to find all about our low-cost, high-performance PCs, add-on boards or HATs, microcontrollers, accessories, and much more. 

As well as being able to learn about and purchase the full range of hardware products, on the new website you can download our latest software, find detailed technical documentation, connect with the community on the forums, and read the latest news about Raspberry Pi technologies and how they’re being used to change the world. 

What’s changing at raspberrypi.org

This website (raspberrypi.org) will continue to be the home for the Raspberry Pi Foundation and all of our educational initiatives to help young people learn about computers and how to create with digital technologies.

That includes online resources to help young people learn how to code, information about our networks of Code Clubs and CoderDojos, training and support for teachers and other educators, and access to the world’s leading-edge research into computing education.

You’ll still be able to find loads of resources about Raspberry Pi computers in education, and cool opportunities for young people to learn how to code and create with Raspberry Pi technologies, whether that’s our space programme Astro Pi, or building robots with Raspberry Pi Pico.

Why the change?

When raspberrypi.org was first launched as a WordPress blog in 2011, we were talking about a low-cost, programmable computer that was being designed for education. 

Fast-forward a decade, and we are now speaking about an increasingly broad range of technology and education products and services to industry, hobbyists, educators, researchers, and young people. While there is lots of overlap between those communities and their interests, it is becoming increasingly difficult to address everyone’s needs on one website. So this change is really all about making life easier for you. 

We will continue to provide lots of links and connections between the two sites to make sure that you can easily find what you’re looking for. As ever, we’d love to hear your feedback in the comments below. 

Connect with us on our new social media channels

Alongside the changes to the websites, we’re also launching new social channels that are focused on the Foundation’s educational initiatives. We look forward to seeing you there.

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New free resources for young people to become independent digital makers

Post Syndicated from Rik Cross original https://www.raspberrypi.org/blog/free-coding-resources-children-young-people-digital-making-independence/

Our mission at the Raspberry Pi Foundation is to help learners get creative with technology and develop the skills and confidence they need to make things that matter to them using code and physical computing. One of the ways in which we do this is by offering learners a catalogue of more than 250 free digital making projects! Some of them have been translated into 30 languages, and they can be used with or without a Raspberry Pi computer.

Over the last 18 months, we’ve been developing an all-new format for these educational projects, designed to better support young people who want to learn coding, whether at home or in a coding club, on their digital making journey.

An illustration of the 3-2-1 structure of the new Raspberry Pi Foundation coding project paths.
Our new free learning content for young people who want to create with technology has a 3-2-1 structure (click the image to enlarge)

Supporting learners to become independent tech creators

In the design process of the new project format, we combined:

  • Leading research
  • Experience of what works in Code Clubs, CoderDojos, and other Raspberry Pi programmes
  • Feedback from the community

While designing the new format for our free projects, we found that, as well as support and opportunities to practise while acquiring new skills and knowledge, learners need a learning journey that lets them gradually develop and demonstrate increasing independence.

Therefore, each of our new learning paths is designed to scaffold learners’ success in the early stages, and then lets them build upon this learning by providing them with more open-ended tasks and inspirational ideas that learners can adapt or work from. Each learning path is made up of six projects, and the projects become less structured as learners progress along the path. This allows learners to practise their newly acquired skills and use their creativity and interests to make projects that matter to them. In this way, learners develop more and more independence, and when they reach the final project in the path, they are presented with a simple project brief. By this time they have the skills, practice, and confidence to meet this brief any way they choose!

The new content structure

When a learner is ready to develop a new set of coding skills, they choose one of our new paths to embark on. Each path is made up of three different types of projects in a 3-2-1 structure:

  • The first three Explore projects introduce learners to a set of skills and knowledge, and provide step-by-step instructions to help learners develop initial confidence. Throughout these projects, learners have lots of opportunity to personalise and tinker with what they’re creating.
  • The next two Design projects are opportunities for learners to practise the skills they learned in the previous Explore projects, and to express themselves creatively. Learners are guided through creating their own version of a type of project (such as a musical instrument, an interactive pet, or a website to support a local event), and they are given code examples to choose, combine, and customise. No new skills are introduced in these projects, so that learners can focus on practising and on designing and creating a project based on their own preferences and interests.
  • In the final one Invent project, learners focus on completing a project to meet a project brief for a particular audience. The project brief is written so that they can meet it using the skills they’ve learned by following the path up to this point. Learners are provided with reference material, but are free to decide which skills to use. They need to plan their project and decide on the order to carry out tasks.

As a result of working through a path, learners are empowered to make their own ideas and create solutions to situations they or their communities face, with increased independence. And in order to develop more skills, learners can work through more paths, giving them even more choice about what they create in the future.

More features for an augmented learning experience

We’ve also introduced some new features to add interactivity, choice, and authenticity to each project in a path:

  • Real-world info box-outs provide interesting and relevant facts about the skills and knowledge being taught.
  • Design decision points allow learners to make choices about how their project looks and what it does, based on their preferences and interests.
  • Debugging tips throughout each project give learners guidance for finding and fixing common coding mistakes.
  • Project reflection steps solidify new knowledge and provide opportunities for mastery by letting learners revisit the important learnings from the project. Common misconceptions are highlighted, and learners are guided to the correct answer.
  • At the start of each project, learners can interact with example creations from the community, and at the end of a project, they are encouraged to share what they’ve made. Thus, learners can find inspiration in the creations of their peers and receive constructive feedback on their own projects.
  • An open-ended upgrade step at the end of each project offers inspiration for young people to give them ideas for ways in which they could continue to improve upon their project in the future.

Access the new free learning content now

You can discover our new paths on our projects site right now!

We’ll be adding even more content soon, including completely new Python programming and web development paths!

As always, we’d love to know what you think: here’s a feedback form for you to share comments you have about our new content!

For feedback specific to an individual project, you can use the feedback link in the footer of that project’s page as usual.

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Free computer science courseware and hardware for American educators

Post Syndicated from original https://www.raspberrypi.org/blog/free-computer-science-courseware-hardware-for-american-educators/

Today we’re announcing two brand-new, fantastic, free online courses for educators in the USA. And to kickstart their learning journey, we are giving qualified US-based educators the chance to get a free Raspberry Pi Pico microcontroller hardware kit. This is all thanks to our partners at Infosys Foundation USA, who are committed to expanding access to computer science and maker education in public schools across the United States.

In a classroom, a teacher and a student look at a computer screen while the student types on the keyboard.
Bring computer science to your students with the help of our new free online courses.

You can find both new courses on the Pathfinders Online Institute platform, which supports US classroom educators to bring high-quality computer science and maker education content to their kindergarten through 12th grade students. And best of all, the platform is completely free!

Learn how to teach the essentials of programming

The first course we’ve created for you is called Programming essentials in Scratch. It supports teachers to introduce the essentials of programming to fourth to eighth grade students. The course covers the key concepts of programming, such as variables, selection, and iteration. In addition to learning how to teach programming effectively, teachers will also discover how to inspire their students and help them create music, interactive quizzes, dance animations, and more.

A girl sits by a desktop computer, with her Scratch coding project showing on the screen.
Scratch is a block-based programming language and ideal for teaching key programming concepts.

Discover how to teach physical computing

Our second new course for you is called Design, build, and code a rover with Raspberry Pi Pico. It gives teachers of fourth to eighth grade students everything they need to start teaching physical computing in their classroom. Teachers will develop their students’ knowledge of the subject by using basic circuits, coding a Raspberry Pi Pico microcontroller to work with motors and LEDs, and designing algorithms to navigate a rover through a maze. By the end of the course, teachers will have all the resources they need to inspire students and help them explore practical programming, system design, and prototyping.

On a wooden desktop, electronic components, a Raspberry Pi Pico, and a motor next to a keyboard.
Take our free course to learn how to build and code a rover with your students.

Get one of 1,000 free hardware kits

And thanks to the generous support of Infosys Foundation USA, we’re able to provide qualified educators with a FREE kit of materials to participate in the Design, build, and code a rover with Raspberry Pi Pico course. We’re especially excited about this because the kit includes our first-ever microcontroller, Raspberry Pi Pico. This offer is available to 1,000 US-based K–12 public or charter school teachers on a first-come, first-served basis.

To claim your kit, just create a free account on Pathfinders Online Institute and start the course. On the first page of the course, you’ll receive instructions on how to apply for a free kit.

A soldered Raspberry Pi Pico on a breadboard.
The first 1,000 qualified educators who sign up for Design, build, and code a rover with Raspberry Pi Pico receive all a free hardware kit.

If you’re not a qualified educator, or if you’ve missed out on the opportunity to get the free hardware, we still welcome you to join the course! You can find the materials yourself, or purchase the kit from our partners at PiShop.us.

Thank you to Infosys Foundation USA

All of us at the Raspberry Pi Foundation want to thank the Infosys Foundation USA team for collaborating with us on this new resource and learning opportunity for educators. We appreciate and share their commitment to support computer science and maker education.

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We’re sending Raspberry Pi computers to space for the European Astro Pi Challenge

Post Syndicated from Olympia Brown original https://www.raspberrypi.org/blog/astro-pi-2021-news-rocket-launch-hardware/

We’re super excited to announce that the European Astro Pi Challenge is back for another year of amazing space-based coding adventures.

This time we are delighted to tell you that we’re upgrading the Raspberry Pi computers on the International Space Station (ISS) and adding new hardware to expand the range of experiments that young people can run in space!

What’s new with Astro Pi?

The first Astro Pi units were taken up to the ISS by British ESA astronaut Tim Peake in December 2015 as part of the Principia mission. Since then, 54000 young people from 26 countries have written code that has run on these specially augmented Raspberry Pi computers.

Working with our partners at the European Space Agency, we are now upgrading the Astro Pi units to include:

  • Raspberry Pi 4 Model B with 8GB RAM
  • Raspberry Pi High Quality Camera
  • Google Coral machine learning accelerator
  • Colour and luminosity sensor
  • Passive infrared sensor
Astro Pi MK II hardware.
The augmented Raspberry Pi computers we are sending up to the International Space station, in all their glory

The units will continue to have a gyroscope; an accelerometer; a magnetometer; and humidity, temperature, and pressure sensors.

Astro Pi MK II hardware with Coral machine learning accelerator.
The little device on the left is the Google Coral machine learning accelerator

The new hardware makes it possible for teams to design new types of experiments. With the Raspberry Pi High Quality Camera they can take sharper, more detailed images, and, for the first time, teams will be able to get full-colour photos of the beauty of Earth from space. This will also enable teams to investigate plant health thanks to the higher-quality optical filter in conjunction with the IR-sensitive camera. Using the Coral machine learning accelerator, teams will also be able to develop machine learning models that allow high-speed, real-time processing.

Getting into space

The Astro Pi units, in their space-ready cases of machined aluminium, will travel to the ISS in December on the SpaceX Dragon Cargo rocket, launching from Kennedy Space Center. Once the resupply vehicle docks with the ISS, the units will be unpacked and set up ready to run Astro Pi participants’ code in 2022.

Getting the units ready for launch has been a significant effort from lots of people. Once we worked with our friends at ESA to agree on the new features and hardware, we commissioned the design of the new case from Jon Wells. Manufacturing was made significantly more challenging by the pandemic, not least because we weren’t able to attend the factory and had to interact over video calls.

ESA astronaut Samantha Cristoforetti aboard the ISS. Credit: ESA

Once we had the case and hardware ready, we could take on the huge battery of tests that are required before any equipment can be used on the ISS. These included the vibration test, to ensure that the Astro Pi units would survive the rigours of the launch; thermal testing, to make sure that units wouldn’t get too hot to touch; and stringent, military-grade electromagnetic emissions and susceptibility tests to guarantee that the Astro Pi computers wouldn’t interfere with any ISS systems, and would not themselves be affected by other equipment that is on board the space station.

Huge thanks to Jon Wells and our collaborators at Airbus, Google, MidOpt, and Shearline Precision Engineering for everything they’ve done to get us to the point where we were able to ship the new Astro Pi units to the Aerospace Logistics Technology Engineering Company (ALTEC) in Italy for final preparations before their launch.

There are two Astro Pi missions for young people to choose from: Mission Zero and Mission Space Lab. Young people can participate in one or both of the missions! Participation is free and open for young people up to age 19 in ESA member states (exceptions listed on the Astro Pi website).

Mission Zero

In Mission Zero, young people write a simple Python program that takes a sensor reading and displays a message on the LED screen. This year, participation in Mission Zero also gives young people the opportunity to vote for the names of the two new computers. Mission Zero can be completed in around an hour and is open to anyone aged 7 to 19 years old. Every eligible entry is guaranteed to run on board the ISS and participants will receive an official certificate with the exact time and location of the ISS when their program ran.

Mission Zero opens today and runs until 18 March 2022.

Mission Space Lab

Mission Space Lab is for teams of young people who want to run their own scientific experiments on the Astro Pi units aboard the ISS. It runs over eight months in four phases, from idea registration to data analysis. 

Have a look at the winning teams from last year for amazing examples of what teams have investigated in the past. But remember — the new Astro Pi computers offer exciting new ways of investigating life in space and on Earth. We can’t wait to see what ideas participants come up with this year. 

To start, Mission Space Lab team mentors just need to send us their team’s experiment idea by 29 October 2021.

Follow our progress

You can keep updated with all of the latest Astro Pi news, including the build-up to the rocket launch in December, by following the Astro Pi Twitter account.

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Celebrating the community: Toshan

Post Syndicated from Katie Gouskos original https://www.raspberrypi.org/blog/community-stories-toshan-coding-mentor/

Today we bring you the fourth film in our series of inspirational community stories! Incredible young people from the community have collaborated with us to create these videos, where they tell their tech stories in their own words.

Toshan, an Indian teenager in Bangalore.
Toshan had community support when he started learning to code, so now he mentors other young people at his CoderDojo club.

Watch the new film to meet a “mischievous” tech creator who is helping other young people in his community to use technology to bring their ideas to life.

This is Toshan

Toshan’s story takes place in his hometown of Bangalore, India, where his love for electronics and computing sent him on a journey of tech discovery! 

Help us celebrate Toshan by liking and sharing his story on Twitter, Linkedin, or Facebook!

Toshan (16) first encountered coding aged 12, thanks to his computing teacher Miss Sonya. Describing his teacher, he says: “The unique thing is, she just doesn’t stop where the syllabus ends.” The world of digital making and Raspberry Pi computers that Miss Sonya introduced him to offered Toshan “limitless opportunities”, and he felt inspired to throw himself into learning.

“If we help people with their ideas, they might bring something new into the world.”

Toshan

Having found help in his local community and the online Raspberry Pi Foundation community that enabled him to start his tech journey, Toshan decided to pass on his skills: he set up a CoderDojo for other young people in Bangalore when he was 14. Toshan says, “I wanted to give something back.” Mentoring others as they learn coding and digital making helped his confidence grow. Toshan loves supporting the learners at his Dojo with problem-solving because “if we help people with their ideas, they might bring something new into the world.”

Toshan, an Indian teenager, with his mother and father.

Supported by his mum and dad, Toshan’s commitment to helping others create with technology is leading him to extend his community beyond the city he calls home. Through his YouTube channel, he reaches people outside of Bangalore, and he has connected with a worldwide community of like-minded young tech creators by taking part in Coolest Projects online 2020 with an automated hand sanitiser he built.

Toshan’s enthusiasm and love for tech are already motivating him to empower others, and he has only just begun! We are delighted to be a part of his journey and can’t wait to see what he does next.

Help us celebrate Toshan by liking and sharing his story on Twitter, Linkedin, or Facebook!

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Cloudflare Helps K-12s Go Back to School

Post Syndicated from Nandini Jayarajan original https://blog.cloudflare.com/cloudflare-helps-k12-go-back-to-school/

Cloudflare Helps K-12s Go Back to School

Cloudflare Helps K-12s Go Back to School

While Federal funding programs focus on providing connectivity to students and staff, security is often an afterthought and reallocating funds to protect the network can become a challenge. We are excited to announce our Back to School initiative to further support our mission to provide performance and security with no trade-offs.

From start to finish, education customers will work with our dedicated Public Sector team, well-versed in the specific technical environments and business needs for K-12 districts. Your IT team will have access to 24/7/365 technical support, emergency response and support during under attack situations, and ongoing training to continuously help improve your security posture and business continuity plans.

Attacks Against K-12 Schools On The Rise

Public schools in the United States, especially K-12s, saw a record-breaking increase in cybersecurity attacks. The K-12 Cyber Incident Map cataloged 408 publicly-disclosed school incidents, including a wide range of cyber attacks; from data breaches to ransomware, phishing attacks, and denial-of-service attacks. This is an 18 percent increase over 2019 and continues the upward trend in attacks since the K-12 Cyber Incident Map started tracking incidents in 2016. To support our public education partners, Cloudflare has created a tailored onboarding experience to help education entities receive enterprise-level security services at an affordable price.

Cloudflare Helps K-12s Go Back to School
Source: https://k12cybersecure.com/year-in-review/‌‌

The public school system serves over 50 million students and employs nearly 6.7 million people, making it the largest industry by employment in the United States. This government-funded, free education system creates a market size of nearly $806 billion. Schools partner with technology companies for student resources and overall operations, and use SaaS applications and cloud deployments to control costs. Investing in these products and services allowed schools to transition to remote learning during the pandemic and continue educating students.

Despite their reliance on connectivity and technology, school districts rarely invest enough in cybersecurity to combat the high risk of attacks. Cybercriminals see public schools as ‘soft targets’ as they hold a lot of valuable data.

Ransomware attacks make data vulnerable to exposure and block access to a school district’s network. Baltimore County, Maryland schools experienced an attack in November 2020 that shut down schools for two days for 111,000 students, and cost the school system over $8 million to recover.

In September 2020, Toledo Public Schools in Ohio experienced a data breach by the Maze ransomware cartel. Maze posted 9 GB of compressed data that included sensitive student and employee data from at least 2008 to 2017. Less than six months later, in February 2021, parents received identity theft and credit fraud notifications involving their children.

Phishing attacks also continue to be a headache for K-12 school districts. The median amount stolen in attacks are \$2 million and, in 2020, \$9.8 million was stolen from a single school district.

Between the high rate of cybersecurity attacks in 2020 and into the first half of 2021, things are not slowing down, and education entities will continue to be targeted, whether it be directly or indirectly.

The Move to Modern

As it became a focus for K-12 Districts to modernize and move physical infrastructure into a more flexible, scalable solution, many school districts were looking for a way to offload DNS onto a cloud-based offering. Leveraging Cloudflare’s global anycast network, we’re able to provide a single management console to handle application needs: Managed DNS with built-in DNSSEC, DDoS mitigation, and Web Application Firewall. You can learn more on how Mount Pleasant School District in Texas consolidated their web assets in our case study.

Where The Need Has Shifted

The pandemic has exposed network security gaps in education, leaving a few main areas open to vulnerability — namely open/exposed ports that allow malicious actors to stay under the radar and end-of-life software that no longer receives security updates or bug fixes.

As attackers become more sophisticated, it has become imperative that districts implement comprehensive network layer solutions to prevent outages, data breaches, and other cyber-related incidents. The Federal Bureau of Investigation (FBI), the Cybersecurity and Infrastructure Security Agency (CISA), and the Multi-State Information Sharing and Analysis Center (MS-ISAC) released a Joint Cybersecurity Advisory that provides recommendations for K-12 for stopping threats and attacks.

How Cloudflare One Can Help

Cloudflare One is a network-as-a-service solution designed to replace a patchwork of appliances with a single network that provides cloud-based security, performance, and control through one user interface.

While districts may be receiving DDoS protection from their upstream ISP, there are a few common issues we see with this setup:

  • ISPs typically use the same commodity devices that were being deployed up to 20 years ago in data centers.
  • The devices are typically set up in an “on demand” fashion so that if you begin to experience a DDoS attack they will need to first be notified before assisting. In many cases, if that appliance is overloaded or unable to withstand the size or complexity of an attack, healthy traffic may be dropped as well.
  • There is limited visibility into the source of the attack and a lack of control around putting security measures in place for future incidents.

As compared to hardware boxes and on-premise appliances, Cloudflare’s service is “always on”. This means we’re agile and will proactively take action in the event of an attack, the time to mitigate is as small as possible, and you get the added benefit of other services being layered into the defense in depth strategy (DNS, CDN, WAF).

Within Cloudflare One, our Layer 3 DDos Mitigation solution called Magic Transit, has helped districts like Godwin Heights stay online by blocking hundreds of large DDoS attacks (just within the first few weeks!). Using anycast and BGP to announce your IP space, Cloudflare absorbs traffic destined for your network and mitigates DDoS attacks closest to the source, before sending the filtered traffic back to your network over low latency paths for fast performance.

Another focus during the pandemic has been supporting remote students and staff. This continues to challenge IT security as we think about how to not only keep our networks up and running, but how to protect students and staff while on the network from phishing attacks, malware, and ransomware.

Cloudflare for Teams is composed of Access and Gateway. Access pairs with identity management systems to protect all internal applications. Gateway is designed to secure access to the outbound Internet through DNS and URL filtering, SSL inspection, and file upload/download policies, which ultimately protects users from malware, phishing, and other security threats. This added layer of protection provides your users access to the applications they need without sacrificing security or performance.

Please inquire at [email protected] for our special Education K-12 Pricing. We look forward to supporting you.

Delivering a culturally relevant computing curriculum: new guide for teachers

Post Syndicated from Sue Sentance original https://www.raspberrypi.org/blog/culturally-relevant-computing-curriculum-guidelines-for-teachers/

In computing education, designing equitable and authentic learning experiences requires a conscious effort to take into account the characteristics of all learners and their social environments. Doing this allows teachers to address topics that are relevant to a diverse range of learners. To support computing and computer science teachers with this work, we’re now sharing a practical guide document for culturally responsive teaching in schools.

Why we need to make computing culturally relevant

Making computing culturally relevant means that learners with a range of cultural identities will be able to identify with the examples chosen to illustrate computing concepts, to engage effectively with the teaching methods, and to feel empowered to use computing to address problems that are meaningful to them and their communities. This will enable a more diverse group of learners to feel that they belong in computing and encourage them to choose to continue with it as a discipline in qualifications and careers.

Such an approach can empower all our students and support their skills and understanding of the integral role that computing can play in promoting social justice.

Yota Dimitriadi, Associate Professor at the University of Reading, member of the project working group

We introduced our work on this new document to you previously here on the blog. Check out the prblog post to find out more about the project’s funding and background, and the external working group of teachers and academics we convened to develop the guide.

Some shared definitions

To get the project off to the best start possible once we had assembled the working group, we first spent time drawing on research from the USA and discussing within the working group to come to a shared understanding of key terms:

  • Culture: A person’s knowledge, beliefs, and understanding of the world, which are affected by multiple personal characteristics, as well as social and economic factors.
  • Culturally relevant pedagogy: A framework for teaching that emphasises the importance of incorporating and valuing all learners’ knowledge, ways of learning, and heritage, and that promotes critical consciousness in teachers and learners.
  • Culturally responsive teaching: A range of teaching practices that draw on learners’ personal experiences and cultural identities to make learning more relevant to them, and that support the development of critical consciousness.
  • Social justice: The extent to which all members of society have a fair and equal chance to participate in all aspects of social life, develop to their full potential, contribute to society, and be treated as equals.
  • Equity: The extent to which different groups in society have access to particular activities or resources. To ensure that opportunities for access and participation are equal across different groups.

To bring in the voices of young people into the project, we asked teachers in the working group to consult with their learners to understand their perspectives on computing and how schools can engage more diverse groups of learners in elective computer science courses. The main reason that learners reported for being put off computing: complex or boring lessons of coding activities with a focus on theory rather than on practical outcomes. Many said that they were inspired by tasks such as producing their own games and suggested that early experiences in primary school and KS3 had been very important for their engagement in computing.

Curriculum, teaching approaches, and learning materials

The guide shows you that a culturally relevant pedagogy applies in three aspects of education, which we liken to a tree to indicate how these aspects connect to each other: the tree’s root system, the basis of culturally relevant pedagogy, is the focus of the curriculum; the tree’s trunk and branches are the teaching approaches taken to deliver the curriculum; the learning materials, represented by the tree’s crown of leaves, are the most widely visible aspect of computing lessons.

A tree with the roots labeled 'curriculum, the trunk labeled 'teaching approaches', and the crown labeled 'learning materials'.

Each aspect plays an important role in culturally relevant pedagogy:

  • Within the curriculum, it is important to think about the contexts in which computing concepts are taught, and about you make connections with issues that are meaningful to your learners
  • Equitable teaching approaches, such as open-ended, inquiry-led activities and discussion-based collaborative tasks, are key if you want to provide opportunities for all your learners to express their ideas and their identities through computing
  • Finally, inclusive representations of a range of cultures, and making learning materials accessible, are both of great importance to ensure that all your learners feel that computing is relevant to them

You can download the guide on culturally relevant pedagogy for computing teachers now to explore the resources provided:

  • You’ll find a lot more information, practical tips, and links to resources to support you to implement culturally relevant pedagogy in all these aspects of your teaching
  • The document links to different available curricula, and we have highlighted materials we’ve created for the Teach Computing Curriculum that promote key aspects of the approach
  • We’ve also included links to academic papers and books if you want to learn more, as well as to videos and courses that you can use for professional development

What was being part of the working group like?

One of the teachers who was part of the working group is Joe Arday from Woodbridge High School in Essex, UK. Joe originally worked in the technology sector and has been teaching computing for ten years. We asked him about his experience of being part of the project and how he plans to use the guide in his own classroom practice:

“It has been an absolute privilege to play a part in working towards producing the guide that my own children will be beneficiaries of when they are studying the computing curriculum throughout their education. I have been able to reflect on how to further improve my teaching practice and pedagogy to ensure that the curriculum taught is culturally diverse and caters for all learners that I teach. (Also, having the opportunity to work with academics from both the UK and US has made me think about becoming an academic in the field of computing at some point in the future!)”

Computer science teacher Joe Arday.

Joe also says: “I plan to review the computing curriculum taught in my computing department and sit down with my colleagues to work on how we can implement the guide in our units of work for Key Stages 3 to 5. The guide will also help my department to work towards one of my school’s aims to encourage an anti-racism community and curriculum in my school.“

Continuing the work

We hope you find this resource useful for your own practice, and for conversations within your school and network of fellow educators! Please spread the word about the guide to anyone in your circles who you think might benefit.

We plan to keep working with learners on their perspectives on culturally relevant teaching, and to develop professional development opportunities for teachers, initially in conjunction with a small number of schools. As always with our research projects, we will investigate what works well and share all our findings widely and promptly.

Many thanks to the teachers and academics in the working group for being wonderful collaborators, to the learners who contributed their time and ideas, and to Hayley Leonard and Diana Kirby from our team for all the time and energy they devoted to this project!

Working group

Joseph Arday, FCCT, Woodbridge High School, Essex, UK

Lynda Chinaka, University of Roehampton, UK

Mike Deutsch, Kids Code Jeunesse, Canada

Dr Yota Dimitriadi, University of Reading, UK

Amir Fakhoury, St Anne’s Catholic School and Sixth Form College, Hampshire, UK

Dr Samuel George, Ark St Alban’s Academy, West Midlands, UK

Professor Joanna Goode, University of Oregon, USA

Alain Ndabala, St George Catholic College, Hampshire, UK

Vanessa Olsen-Dry, North Cambridge Academy, Cambridgeshire, UK

Rohini Shah, Queens Park Community School, London, UK

Neelu Vasishth, Hampton Court House, Surrey, UK

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