Schlagwort: Online Learning

  • Evolving our online courses to help more people be computing educators

    Evolving our online courses to help more people be computing educators

    Reading Time: 4 minutes

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

    Workshop attendees at a table.

    Online courses for all adults who support young people

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

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

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

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

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

    Making our courses more relevant and accessible

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

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

    We’re currently working to: 

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

    Making our courses useful for more groups of people

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

    An educator helps two young people at a computer.

    We’re currently working to: 

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

    Making the learning from our courses sustainable

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

    Kenyan educators work on a physical computing project.

    We’re currently working to: 

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

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

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

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

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

    Website: LINK

  • Get an easy start to coding with our new free online course

    Get an easy start to coding with our new free online course

    Reading Time: 4 minutes

    Are you curious about coding and computer programming but don’t know how to begin? Do you want to help your children at home, or learners in your school, with their digital skills, but you’re not very confident yet? Then our new, free, and on-demand online course Introduction to Programming with Scratch course is a fun, creative, and colourful starting point for you.

    An illustration of Scratch coding.

    Being able to code can help you do lots of things — from expressing yourself to helping others practice their skills, and from highlighting real-world issues to controlling a robot. Whether you want to get a taste of what coding is about, or you want to learn so that you can support young people, our Introduction to Programming with Scratch course is the perfect place to start if you’ve never tried any coding before.

    Scratch course presenters Vasu and Mark.
    Your course presenters, Vasu and Mark.

    On this on-demand course, Mark and Vasu from our team will help you take your very first steps on your programming journey. 

    You can code — we’ll show you how

    On the course, you’ll use the programming language Scratch, a beginner-friendly, visual programming language particularly suitable for creating animations and games. All you need is our course and a computer or tablet with a web browser and internet connection that can access the online Scratch editor.

    You can code in Scratch without having to memorise and type in commands. Instead, by snapping blocks together, you’ll take control of ‘sprites’, which are characters and objects on the screen that you can move around with the code you create.

    A video of what Scratch coding looks like.
    This is how you build Scratch programs.

    As well as learning what you can do with Scratch, you’ll be learning basic programming concepts that are the same for all programming languages. You’ll see how the order of commands is important (sequencing), you’ll make the computer repeat actions (repetition), and you’ll write programs that do different things in different circumstances, for example responding to your user’s actions (selection). Later on, you’ll also make your own reusable code blocks (abstraction).

    You can create your own programs and share them

    Throughout the course you’ll learn to make your own programs step by step. In the final week, Mark and Vasu will show you how you can create musical projects and interact with your program using a webcam.

    A Scratch coding project.
    By the end of the course, you will create a program to control a Scratch character using your live webcam video.

    Vasu and Mark will encourage you to share your programs and join the Scratch online community. You will discover how you can explore other people’s Scratch programs for inspiration and support, and how to build on the code they’ve created.

    A Scratch coding project.
    Thousands of people share their projects in the Scratch online community — you could be one of them.

    Sign up for the course now!

    The course starts for the first time on Monday 14 February, but it is available on demand, so you can join it at any time. You’ll get four weeks’ access to the course no matter when you sign up.

    For the first four weeks that the course is available, and every three months after that, people from our team will join in to support you and help answer your questions in the comments sections.

    If you’re a teacher in England, get free extended access by signing up through Teach Computing here.

    And if you want to do more Scratch coding…

    You can find more free resources here! These are the newest Scratch pathways on our project site, which you can also share with the young people in your life:

    Website: LINK

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

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

    Reading Time: 5 minutes

    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, self-paced 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, learning at your own pace, you’ll find out 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 self-paced 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 today to take the course 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.

    Website: LINK

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

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

    Reading Time: 5 minutes

    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, self-paced 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, learning at your own pace, you’ll find out 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 self-paced 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 today to take the course 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.

    Website: LINK

  • How teachers train in Computing with our free online courses

    How teachers train in Computing with our free online courses

    Reading Time: 4 minutes

    Since 2017 we’ve been training Computing educators in England and around the world through our suite of free online courses on FutureLearn. Thanks to support from Google and the National Centre for Computing Education (NCCE), all of these courses are free for anyone to take, whether you are a teacher or not!

    An illustration of a bootcamp for computing teachers

    We’re excited that Computer Science educators at all stages in their computing journey have embraced our courses — from teachers just moving into the field to experienced educators looking for a refresher so that they can better support their colleagues.

    Hear from two teachers about their experience of training with our courses and how they are benefitting!

    Moving from Languages to IT to Computing

    Rebecca Connell started out as a Modern Foreign Languages teacher, but now she is Head of Computing at The Cowplain School, a 11–16 secondary school in Hampshire.

    Computing teacher Rebecca Connell
    Computing teacher Rebecca finds our courses “really useful in building confidence and taking [her] skills further”.

    Although she had plenty of experience with Microsoft Office and was happy teaching IT, at first she was daunted by the technical nature of Computing:

    “The biggest challenge for me has been the move away from an IT to a Computing curriculum. To say this has been a steep learning curve is an understatement!”

    However, Rebecca has worked with our courses to improve her coding knowledge, especially in Python:

    “Initially, I undertook some one-day programming courses in Python. Recently, I have found the Raspberry Pi courses to be really useful in building confidence and taking my skills further. So far, I have completed Programming 101 — great for revision and teaching ideas — and am now into Programming 102.”

    GCSE Computing is more than just programming, and our courses are helping Rebecca develop the rest of her Computing knowledge too:

    “I am now taking some online Raspberry Pi courses on computer systems and networks to firm up my knowledge — my greatest fear is saying something that’s not strictly accurate! These courses have some good ideas to help explain complex concepts to students.”

    She also highly rates the new free Teach Computing Curriculum resources we have developed for the NCCE:

    “I really like the new resources and supporting materials from Raspberry Pi — these have really helped me to look again at our curriculum. They are easy to follow and include everything you need to take students forward, including lesson plans.”

    And Rebecca’s not the only one in her department who is benefitting from our courses and resources:

    “Our department is supported by an excellent PE teacher who delivers lessons in Years 7, 8, and 9. She has enjoyed completing some of the Raspberry Pi courses to help her to deliver the new curriculum and is also enjoying her learning journey.”

    Refreshing and sharing your knowledge

    Julie Price, a CAS Master Teacher and NCCE Computer Science Champion, has been “engaging with the NCCE’s Computer Science Accelerator programme, [to] be in a better position to appreciate and help to resolve any issues raised by fellow participants.”

    Computing teacher Julie Price
    Computer science teacher Julie Price says she is “becoming addicted” to our online courses!

    “I have encountered new learning for myself and also expressions of very familiar content which I have found to be seriously impressive and, in some cases, just amazing. I must say that I am becoming addicted to the Raspberry Pi Foundation’s online courses!”

    She’s been appreciating the open nature of the courses, as we make all of the materials free to use under the Open Government Licence:

    “Already I have made very good use of a wide range of the videos, animations, images, and ideas from the Foundation’s courses.”

    Julie particularly recommends the Programming Pedagogy in Secondary Schools: Inspiring Computing Teaching course, describing it as “a ‘must’ for anyone wishing to strengthen their key stage 3 programming curriculum.”

    Join in and train with us

    Rebecca and Julie are just 2 of more than 140,000 active participants we have had on our online courses so far!

    With 29 courses to choose from (and more on the way!), from Introduction to Web Development to Robotics with Raspberry Pi, we have something for everyone — whether you’re a complete beginner or an experienced computer science teacher. All of our courses are free to take, so find one that inspires you, and let us support you on your computing journey, along with Google and the NCCE.

    If you’re a teacher in England, you are eligible for free course certification from FutureLearn via the NCCE.

    Website: LINK

  • Making the best of it: online learning and remote teaching

    Making the best of it: online learning and remote teaching

    Reading Time: 7 minutes

    As many educators across the world are currently faced with implementing some form of remote teaching during school closures, we thought this topic was ideal for the very first of our seminar series about computing education research.

    Image by Mudassar Iqbal from Pixabay

    Research into online learning and remote teaching

    At the Raspberry Pi Foundation, we are hosting a free online seminar every second Tuesday to explore a wide variety of topics in the area of digital and computing education. Last Tuesday we were delighted to welcome Dr Lauren Margulieux, Assistant Professor of Learning Sciences at Georgia State University, USA. She shared her findings about different remote teaching approaches and practical tips for educators in the current crisis.

    Lauren’s research interests are in educational technology and online learning, particularly for computing education. She focuses on designing instructions in a way that supports online students who do not necessarily have immediate access to a teacher or instructor to ask questions or overcome problem-solving impasses.

    A vocabulary for online and blended learning

    In non-pandemic situations, online instruction comes in many forms to serve many purposes, both in higher education and in K-12 (primary and secondary school). Much research has been carried out in how online learning can be used for successful learning outcomes, and in particular, how it can be blended with face-to-face (hybrid learning) to maximise the impact of both contexts.

    In her seminar talk, Lauren helped us to understand the different ways in which online learning can take place, by sharing with us vocabulary to better describe different ways of learning with and through technology.

    Lauren presented a taxonomy for classifying types of online and blended teaching and learning in two dimensions (shown in the image below). These are delivery type (technology or instructor), and whether content is received by learners, or actually being applied in the learning experience.

    Lauren Margulieux seminar slide showing her taxonomy for different types of mixed student instruction

    In Lauren’s words: “The taxonomy represents the four things that we control as instructors. We can’t control whether our students talk to each other or email each other, or ask each other questions […], therefore this taxonomy gives us a tool for defining how we design our classes.”

    This taxonomy illustrates that there are a number of different ways in which the four types of instruction — instructor-transmitted, instructor-mediated, technology-transmitted, and technology-mediated — can be combined in a learning experience that uses both online and face-to-face elements.

    Using her taxonomy in an examination (meta-analysis) of 49 studies relating to computer science teaching in higher education, Lauren found a range of different ways of mixing instruction, which are shown in the graph below.

    • Lecture hybrid means that the teaching is all delivered by the teacher, partly face-to-face and partly online.
    • Practice hybrid means that the learning is done through application of content and receiving feedback, which happens partly face-to-face or synchronously and partly online or asynchronously.
    • Replacement blend refers to instruction where lecture and practice takes place in a classroom and part of both is replaced with an online element.
    • Flipped blend instruction is where the content is transmitted through the use of technology, and the application of the learning is supported through an instructor. Again, the latter element can also take place online, but it is synchronous rather than asynchronous — as is the case in our current context.
    • Supplemental blend learning refers to instruction where content is delivered face-to-face, and then practice and application of content, together with feedback, takes place online — basically the opposite of the flipped blend approach.

    Lauren Margulieux seminar slide showing learning outcomes of different types of mixed student instruction

    Lauren’s examination found that the flipped blend approach was most likely to demonstrate improved learning outcomes. This is a useful finding for the many schools (and universities) that are experimenting with a range of different approaches to remote teaching.

    Another finding of Lauren’s study was that approaches that involve the giving of feedback promoted improved learning. This has also been found in studies of assessment for learning, most notably by Black and Wiliam. As Lauren pointed out, the implication is that the reason blended and flipped learning approaches are the most impactful is that they include face-to-face or synchronous time for the educator to discuss learning with the students, including giving feedback.

    Lauren’s tips for remote teaching

    Of course we currently find ourselves in the midst of school closures across the world, so our only option in these circumstances is to teach online. In her seminar talk, Lauren also included some tips from her own experience to help educators trying to support their students during the current crisis:

    • Align learning objectives, instruction, activities, assignments, and assessments.
    • Use good equipment: headphones to avoid echo and a good microphone to improve clarity and reduce background noise.
    • Be consistent in disseminating information, as there is a higher barrier to asking questions.
    • Highlight important points verbally and visually.
    • Create ways for students to talk with each other, through discussions, breakout rooms, opportunities to talk when you aren’t present, etc.
    • Use video when possible while talking with your students.
      Give feedback frequently, even if only very brief.

    Although Lauren’s experience is primarily from higher education (post-18), this advice is also useful for K-12 educators.

    What about digital equity and inclusion?

    All our seminars include an opportunity to break out into small discussion groups, followed by an opportunity to ask questions of the speaker. We had an animated follow-up discussion with Lauren, with many questions focused on issues of representation and inclusion. Some questions related to the digital divide and how we could support learners who didn’t have access to the technology they need. There were also questions from breakout groups about the participation of groups that are typically under-represented in computing education in online learning experiences, and accessibility for those with special educational needs and disabilities (SEND). While there is more work needed in this area, there’s also no one-size-fits-all approach to working with students with special needs, whether that’s due to SEND or to material resources (e.g. access to technology). What works for one student based on their needs might be entirely ineffective for others. Overall, the group concluded that there was a need for much more research in these areas, particularly at K-12 level.

    Much anxiety has been expressed in the media, and more formally through bodies such as the World Economic Forum and UNESCO, about the potential long-lasting educational impact of the current period of school closures on disadvantaged students and communities. Research into the most inclusive way of supporting students through remote teaching will help here, as will the efforts of governments, charities, and philanthropists to provide access to technology to learners in need.

    At the Raspberry Pi Foundation, we offer lots of free resources for students, educators, and parents to help them engage with computing education during the current school closures and beyond.

    How should the education community move forward?

    Lauren’s seminar made it clear to me that she was able to draw on decades of research studies into online and hybrid learning, and that we should take lessons from these before jumping to conclusions about the future. In both higher education (tertiary, university) and K-12 (primary, secondary) education contexts, we do not yet know the educational impact of the teaching experiments we have found ourselves engaging in at short notice. As Charles Hodges and colleagues wrote recently in Educause, what we are currently engaging in can only really be described as emergency remote teaching, which stands in stark contrast to planned online learning that is designed much more carefully with pedagogy, assessment, and equity in mind. We should ensure we learn lessons from the online learning research community rather than making it up as we go along.

    Today many writers are reflecting on the educational climate we find ourselves in and on how it will impact educational policy and decision-making in the future. For example, an article from the Brookings Institution suggests that the experiences of home teaching and learning that we’ve had in the last couple of months may lead to both an increased use of online tools at home, an increase in home schooling, and a move towards competency-based learning. An article by Jo Johnson (President’s Professorial Fellow at King’s College London) on the impact of the pandemic on higher education, suggests that traditional universities will suffer financially due to a loss of income from international students less likely to travel to universities in the UK, USA, and Australia, but that the crisis will accelerate take-up of online, distance-learning, and blended courses for far-sighted and well-organised institutions that are ready to embrace this opportunity, in sum broadening participation and reducing elitism. We all need to be ready and open to the ways in which online and hybrid learning may change the academic world as we know it.

    Next up in our seminar series

    If you missed this seminar, you can find Lauren’s presentation slides and a recording of her talk on our seminars page.

    Next Tuesday, 19 May at 17:00–18:00 BST, we will welcome Juan David Rodríguez from the Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado (INTEF) in Spain. His seminar talk will be about learning AI at school, and about a new tool called LearningML. To join the seminar, simply sign up with your name and email address and we’ll email the link and instructions. If you attended Lauren’s seminar, the link remains the same.

    Website: LINK

  • Prepare to run a Code Club on FutureLearn

    Prepare to run a Code Club on FutureLearn

    Reading Time: 2 minutes

    Prepare to run a Code Club with our newest free online course, available now on FutureLearn!

    FutureLearn: Prepare to Run a Code Club

    Ready to launch! Our free FutureLearn course ‘Prepare to Run a Code Club’ starts next week and you can sign up now: https://www.futurelearn.com/courses/code-club

    Code Club

    As of today, more than 10000 Code Clubs run in 130 countries, delivering free coding opportunities to approximately 150000 children across the globe.

    A child absorbed in a task at a Code Club

    As an organisation, Code Club provides free learning resources and training materials to supports the ever-growing and truly inspiring community of volunteers and educators who set up and run Code Clubs.

    FutureLearn

    Today we’re launching our latest free online course on FutureLearn, dedicated to training and supporting new Code Club volunteers. It will give you practical guidance on all things Code Club, as well as a taste of beginner programming!

    Split over three weeks and running for 3–4 hours in total, the course provides hands-on advice and tips on everything you need to know to run a successful, fun, and educational club.

    “Week 1 kicks off with advice on how to prepare to start a Code Club, for example which hardware and software are needed. Week 2 focusses on how to deliver Code Club sessions, with practical tips on helping young people learn and an easy taster coding project to try out. In the final week, the course looks at interesting ideas to enrich and extend club sessions.”
    — Sarah Sherman-Chase, Code Club Participation Manager

    The course is available wherever you live, and it is completely free — sign up now!

    If you’re already a volunteer, the course will be a great refresher, and a chance to share your insights with newcomers. Moreover, it is also useful for parents and guardians who wish to learn more about Code Club.

    Your next step

    Interested in learning more? You can start the course today by visiting FutureLearn. And to find out more about Code Clubs in your country, visit Code Club UK or Code Club International.

    Code Club partners from across the globe gathered together for a group photo at the International Meetup

    We love hearing your Code Club stories! If you’re a volunteer, are in the process of setting up a club, or are inspired to learn more, share your story in the comments below or via social media, making sure to tag @CodeClub and @CodeClubWorld.

    You might also be interested in our other free courses on the FutureLearn platform, including Teaching Physical Computing with Raspberry Pi and Python and Teaching Programming in Primary Schools.

    Website: LINK